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Will No-Code and AI ever make us all software developers?
In recent years, there has been a growing trend of “no-code” platforms and tools that allow users to create complex applications without a single line of code. At the same time, artificial intelligence is becoming more and more advanced, capable of completing tasks that were once considered impossible for machines to do. So, the question is: will no-code platforms and AI ever make us all software developers? Let’s take a look.
The Pros of No-Code Platforms
No-code platforms have a number of advantages. First and foremost, they lower the barrier to entry for people who want to create software but don’t have the skills or knowledge to do so. Second, they allow for rapid prototyping and iteration; with no need to write code from scratch, you can quickly put together a working prototype of your idea and make changes on the fly. Finally, no-code platforms can be a great way to learn about coding; by using them, you can get a feel for how coding works and what it’s like to work with code, without actually having to write any code yourself.
The Cons of No-Code Platforms
Of course, no-code platforms also have their disadvantages. One major downside is that they can be inflexible; if you want to add a new feature or make a change that’s outside the scope of what the platform allows, you’re out of luck. Additionally, no-code platforms can be expensive; while there are some free options available, many of the best no-code platforms come with a hefty price tag. Finally, because no-code platforms remove the need to write code, they can foster a false sense of security among users who think they know more about coding than they actually do. This can lead to problems down the road if those users ever need to hire a developer or collaborate with one on a project.
The Pros of AI
When it comes to artificial intelligence, there are also some clear advantages. First and foremost, AI is incredibly fast; it can process large amounts of data much faster than any human could hope to. Second, AI is unbiased; because it relies on data instead of human opinion, it can make decisions that are free from personal biases or prejudices. Finally, AI is scalable; as more data is fed into an AI system, it only gets smarter and more accurate over time.
The Cons of AI
AI also has its drawbacks. One major downside is that AI systems require a lot of data to function properly; without enough data points, they simply won’t work. Additionally, AI systems can be opaque; because they rely on complex algorithms that are often inscrutable even to their creators, it can be difficult (if not impossible) to understand how or why an AI system came to a particular decision. Finally, AI systems can be brittle; if something changes in the real world (e.g., a new law is passed), an AI system might not be able to adapt quickly enough and could become obsolete overnight.
The No-Code Movement
No-code platforms like Bubble, Webflow, and Carrd have been gaining in popularity in recent years. And it’s not hard to see why; they allow users to create complex websites and apps without a single line of code required. All you need is a basic understanding of how the platform works, and you can build just about anything you can imagine.
Of course, there are some limitations to what you can do with no-code platforms. They’re not quite as flexible as traditional development environments, so if you want to do something truly unique or complex, you’ll likely need to hire a developer to do it for you. But for most people, no-code platforms are more than sufficient for their needs.
AI-Powered Development Tools
In addition to no-code platforms, there are also a number of AI-powered development tools that allow non-developers to build software without any coding required. These tools range from simple website builders to full-fledged app development suites. And while they’re not quite as easy to use as no-code platforms, they’re still relatively user-friendly and require no coding knowledge whatsoever.
The Future of Software Development?
So will we all be software developers in the future? It’s hard to say for sure. No-code platforms and AI-powered development tools are certainly making it easier for non-developers to create complex websites and apps. But whether or not that will lead to everyone becoming a developer is impossible to predict. Only time will tell.
This is an interesting take from Harry Dewulf on Quora:
Have you ever heard of Microsoft Query?
Microsoft Query (in several forms) still exists and is still in use today. It’s the living embodiment of the infamous definition of madness oft (wrongly) attributed to Einstein that it’s doing the same thing over and over, and expecting different results.
There’s a reason people keep doing the same thing, even though it doesn’t give the intended results. Some strategies just look so much like they will solve the problem that it’s almost impossible to believe that they don’t. So people prefer to disbelieve the results than believe the solution can’t work. This isn’t insanity. It’s a perfectly sensible feature of inductive reasoning which is that the more times you try, the more likely you are to get the result you want. You’d be insane to argue with that. So you have to do quite a difficult (for many people, it seems) piece of reasoning: separate strategies and techniques susceptible to improvement by practice from those that are not.
Of course, in the case of Microsoft Query, there’s a powerful economic motivator.
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People want to believe that you can carry out analytical operations on data without having to use computer code.
The idea of this is just sufficiently removed from simple repetition of the same failed strategy that many people will never realise that they are repeating the same action expecting different results.
The idea is that it’s easier to define complex relationships between data structures visually than verbally.
The theory being that drawing lines between visual representations of tables is easier than writing the words of an SQL statement.
People who don’t routinely work with data genuinely think that the choice is between the visual and the verbal, and they imagine that data analysts visualize data, so it must surely be easier to represent those visualizations directly, right?
The problem is that although we often call it a visualization, when you are imagining a data structure…
… okay. This is going to get weird but come with me on it.
The set of all integers is a one-dimensional space.
Add a dimension and you get a graph with coordinates that we normally represent as two numbers. Those two numbers give a location on a flat plane. So you can plot points on a graph, and maybe join them up with your choice of line of best fit.
Add a dimension and you get 3D. You can still just about represent that as an image, if you have a good understanding of the mammalian visual system. You know about perspective, right?
So what if you need a fourth dimension?
Coordinates in 1 dimensional space are expressed like this: 5
Coordinates in 2 dimensional space like this: 2,5
Coordinates in 3 dimensional space like this: 1,2,5
… and if you’re with me so far, you’ll know that the first two numbers refer to locations horizontally, and the third vertically. 3D printers, CAD programs, Blender, 3 point geometry, vectors in three dimensional space, etc.
All this can be represented by images that look meaningful to the human visual system, which is handy, because that’s what they are for.
But typical data structures can have dozens of dimensions.
Even the simplest ones usually have more than 4. Consider the database that underlies every Enterprise Management System. It has tables for products, clients and orders. You’ve already used up 3 dimensions right there. Supposing you need to create a proposal that demonstrates your ability to provide a subset of your product range to multiple client locations, taking account of vendor and resource availability and seasonal variations? That sort of thing is child’s play compared with evaluating the data from a clinical trial to determine if a new medical device is safe and effective, yet you’re already working with a minimum of five dimensions.
So sure, when thinking about data structures, we frequently “visualize” them, but not as cute 2d images that seem like 3d images “projected inside your mind.” Visualizing data structures so you can design queries for complex datasets is sometimes so difficult it has to be done iteratively. Processing time becomes a factor of query design. You can finish up with a sequence of queries, each of which is multi-dimensional.
Often, the only way to describe them is through the SQL statements that represent them. There will NEVER be a way of representing that as images, because the best that images can ever do is be 2 dimensions that fool your visual system into thinking there are 3 dimensions of space and one of time.
Microsoft Query persists because there will always be people who wishfully think that they can learn to analyse data without learning the “texty part;” without learning to process data (these days, mostly with Python it seems) and without learning to query data with SQL.
No-Code and low-code are wishful thinking except when they are teaching aids (as such, I will admit, they can be a good early stepping stone).
So no, no-code will manacle you, and you’ll love your manacles right up until you need to reach for the door handle.
Conclusion:
So what’s the verdict? Will no-code platforms and AI eventually make us all software developers? It’s hard to say for sure. However, one thing is certain: both no-code platforms and AI have their pros and cons. As such, it’s important to weigh those pros and cons carefully before deciding whether or not either one is right for you.
No one can say for sure whether or not the rise of no-code platforms and AI-powered development tools will ultimately lead to everyone becoming a software developer. But one thing is certain; these trends are making it easier than ever for non-developers to create complex websites and apps without any coding required. So whatever the future may hold, one thing is clear; the landscape of software development is changing, and changing fast.
With the rise of no-code platforms and AI, some people are wondering if we’ll ever see a future where everyone is a software developer. While it’s true that these technologies have made it easier than ever to create digital products, there are still some limitations that prevent them from becoming ubiquitous. In this blog post, we have explored the reasons why no-code and AI probably won’t make us all software developers—at least not anytime soon.
1. No-code platforms still require some technical knowledge.
2. AI is still in its early stages and has a long way to go before it can replace human developers.
3. The demand for software developers is still high, and there aren’t enough no-code/AI solutions to meet that demand.
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How AI is Impacting Smartphone Longevity – Best Smartphones 2023
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How AI is Impacting Smartphone Longevity – Best Smartphone 2023
We are in an age where our smartphones are becoming more and more advanced. With every new release, there are new features and capabilities that we never thought possible. But as our smartphones become more powerful, they also become more fragile. So, how can we make sure that our smartphones last longer? The answer may lie in artificial intelligence.
How AI Can Help Improve Smartphone Longevity
One of the ways AI can help improve smartphone longevity is through battery optimization. Battery optimization is the process of making sure that your smartphone’s battery is being used in the most efficient way possible. AI can help by learning your usage patterns and making adjustments accordingly. For example, if you typically use your phone for browsing the web and checking social media in the morning, AI can make sure that your battery is charged enough to last throughout the day.
Another way AI can help improve smartphone longevity is by helping to prevent hardware damage. We’ve all had that moment where we drop our phone and hold our breath, hoping that it doesn’t break. But with AI, your phone may one day be able to sense when it’s about to be dropped and make adjustments accordingly. For example, it could move to a position where it’s less likely to be damaged or it could activate a shock-absorbent case.
Our smartphones are only going to become more and more advanced in the years to come. And as they become more advanced, we need to find ways to make sure that they last longer. Artificial intelligence may be the key to achieving this goal. Through battery optimization and prevention of hardware damage, AI has the potential to greatly improve smartphone longevity.
The Best Smartphones of 2022-2023
It’s that time of year again! The time when we start to think about which smartphone will be the best for the upcoming year. With so many options on the market, it can be hard to decide which one is right for you. But don’t worry, we’re here to help. In this blog post, we’ll be taking a look at the best smartphones of 2022-2023, so you can make an informed decision about which one is right for you.
Apple iPhone 14 and 14 Pro max
As always, Apple released its new iPhone 14 in 2022. The iPhone 14 has a 6.1-inch OLED display, 5G connectivity, and a faster A15 processor. The camera is also said to be getting an upgrade with a new sensor that will improve low-light performance. The battery life is also better than previous models. If you’re looking for the best of the best, the iPhone 14 Pro max is sure to be one of the best smartphones of the year.
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Samsung Galaxy S30 and S30 Plus
Samsung’s Galaxy S30 is also expected to be released at the end of 2022. The S30 is rumored to have a 6.7-inch OLED display, 5G connectivity, and a Qualcomm Snapdragon 875 processor. The camera is said to be getting an upgrade as well with a new 108MP sensor. The battery life is also expected to be better than previous models. If you’re looking for a great Android option, the Galaxy S30 should be at the top of your list.
OnePlus 9 and 9 Pro
OnePlus is expected to release its new OnePlus 9 in March of 2023. The OnePlus 9 is rumored to have a 6.7-inch OLED display, 5G connectivity, and a Qualcomm Snapdragon 888 processor. The camera is said to be getting an upgrade with a new 50MP sensor. The battery life is also expected to be better than previous models. If you’re looking for a great Android option that won’t break the bank, the OnePlus 9 should be at the top of your list.
Conclusion:
There are a lot of great smartphones coming out in 2022-2023. It’s important to do your research so you can find the one that’s right for you. We hope this blog post has been helpful in your search for the perfect smartphone!
Below are the Best Smartphones in 2022 – 2023
How AI is Transforming Smartphone Longevity
In the past few years, artificial intelligence (AI) has become one of the most popular buzzwords in the tech industry. But what is AI, and how is it being used to transform our smartphones? We’ll take a look at how AI is changing the smartphone landscape and what that means for the future of mobile devices.
What is AI?
AI is a broad term that encompasses a wide range of technologies, including machine learning, natural language processing, and computer vision. Essentially, AI is any software that can perform tasks that would traditionally require human intelligence, such as understanding and responding to spoken questions or identifying objects in images.
How is AI being used in smartphones?
One of the most common ways that AI is being used in smartphones is through the use of virtual assistants. Virtual assistants are software programs that can perform tasks or provide information on behalf of users. Apple’s Siri, Google’s Assistant, and Amazon’s Alexa are all examples of virtual assistants that are powered by AI.
Virtual assistants are becoming more and more common as they become more accurate and efficient at completing tasks. In addition to performing basic tasks like setting alarms and sending text messages, virtual assistants are also being used to book appointments, make restaurant reservations, and even hail taxis. As virtual assistants become more capable, it’s likely that we’ll see even more innovative uses for them in the future.
Another way that AI is being used in smartphones is through the use of camera features. Many newer smartphones now come with features like portrait mode and scene detection that use AI to improve the quality of photos. For example, portrait mode uses AI to identify faces in an image and then blur the background to create a professional-looking photo. Scene detection uses AI to identify the type of scene being photographed (e.g., low light, action shot) and then adjust the camera settings accordingly to help users get the best possible photo.
What does the future hold for AI in smartphones?
As AI continues to evolve, we can expect to see even more amazing innovations in the world of smartphone technology. Some experts predict that eventually, AI will be used to create “smart cases” that will be able to detect when a phone has been dropped and automatically deploy airbags to protect it from damage. Others believe that AI will be used to create “augmented reality” experiences that will allow users to view digital information superimposed over their real-world surroundings. Whatever the future may hold, one thing is for sure: AI is going to change the way we use our smartphones forever.
Conclusion:
AI is quickly becoming one of the most important technologies in the smartphone industry. With its ability to power virtual assistants and improve camera features, AI is transforming our mobile devices in ways we never thought possible. As AI continues to evolve, we can only imagine what new innovations it will bring to our phones in the years to come!
Best smartphone camera 2022 – 2023
Sony: Smartphone cameras will surpass DSLR image quality by 2024
Xperia 1 III – 5G Smartphone with 120Hz 6.5″ 21:9 4K HDR OLED display with triple camera and four focal lengths- XQBC62/B
Golden hour shot with the iPhone 14 Pro
Do the best smartphone cameras beat entry level cameras now?
I’ve seen photos of the iPhone 14 Pro, the S22 Ultra, and the Xiaomi Mi11 Ultra, and I was quite shocked on how they looked. I saw entry level cameras like the ZX-1 reviewed, and I was much less impressed. Sometimes, they looked worse than the smartphone counterpart.
Smartphones nowadays use a huge amount of hidden AI software tricks to make an image appear better than it actually is because they have to compensate for the small, and low-quality, sensors and lenses. For example, many of them take multiple pictures at different exposure settings every time you press the shutter and merge them to get a final pic with better shadow and highlight detail, and to reduce the graininess among other things. With a good quality camera, and even most entry-level cameras you don’t need to do any of that because the sensors and lenses are much bigger and better. You still can do those things if you want, but you’ll usually need to do it manually (most photographers are perfectionists who want full control over those things).
For a beginner you might find that pictures taken on an entry-level camera initially looks worse than the ones taken on a modern smartphone, but that’s actually because you’re not doing it right. To get the best out of a dedicated camera you need to learn a bit more about how cameras work, what their weaknesses are and how to compensate for them. You’ll also need to do a bit more work after you’ve finished taking the pictures.
Smartphones are great for people who want to take snaps, basically point and shoot cameras, loads of stitching, HDR stacking and all done in a millisecond. Mind you give a pro a tool and they know what to do with it.
Cameras allow far greater control over your overall photograph and believe it or not do have a longer life cycle than a flagship phone.
Personally I enjoy taken snaps with my smartphone, but if I want to do photography I’ll bring one of my cameras out.
I agree the convenience of a smartphone is great, but it doesn’t beat the experience of shooting with a camera and lens.
To answer your question: I’d stick with the smartphone now, review all you pictures taken this year and catagorize them (street, product, portrait, macro etc) and determine what specific photography is for you and buy your first camera and lens.
Best budget smartphone 2022 – 2023
Smartphone 101 – Pick a smartphone for me – android or iOS – Apple iPhone or Samsung Galaxy or Huawei or Xaomi or Google Pixel
How much is an iPad in 2022 – 2023
Best Rugged Smartphone 2022 – 2023
Cheap is 100% not the answer as they tend to be less rigid in the body with much weaker screens. The hands down best by a mile product I have used, and continue to use, is the iPhone Mini. Don’t skimp on the otter box case, which keeps all the little bits of concrete, rocks, and dust out of the charge port. Seriously the mini conveniently fits in any of your pockets even with the otter box. Also because it is a bit smaller, it doesn’t get torqued on or bent nearly as easily. Think about how flimsy a longer piece of rebar is compared to a shorter chunk, that principle I’m sure applies to your phone’s screen as well.
Have I mentioned how nice it is to be able to reach the whole screen with 1 hand compared to these giant tablet sized phones? Yeah, it’s great.
The only downside for the iPhone mini is probably the need to charge every night as a smaller phone has a smaller battery, however it does charge very fast.
I should also mention I have been a lifelong android user, and I’m definitely in the shit with concrete work, and the mini has taken all the abuse for nearly 2 years without any damage and it is obviously light years better than any cheap 150$ phones you may be tempted to settle for.
Best Nokia Smartphone 2022 – 2023
Nokia boss predicts when we will move away from smartphones, and the arrival of 6G.
Headquartered in Finland, Nokia builds telecoms networks that enable phones and other internet-enabled devices to communicate with one another.
Asked when he thinks the world will move away from using smartphones to using smart glasses and other devices that are worn on the face, Nokia CEO Pekka Lundmark said it will definitely happen by the time 6G arrives in 2030.
U.S. tech giants such as Meta, Google and Microsoft are working on new augmented reality headsets that could one day replace the smartphone.
He did not specify exactly what he was referring to but some companies, such as Elon Musk’s Neuralink, are working on producing electronic devices that can be implanted into the brain and used for communication with machines and other people. On a more basic level, chips can be implanted into people’s fingers and used to unlock things.
Best iPhones 2022 – 2023
Best Android smartphone 2022- 2023
Google Pixel 6 and 6 Pro reviews
XDA-Developers – Pixel 6 Pro review
9to5Google – Pixel 6 Pro review, Pixel 6 Pro video review
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Android Police – Pixel 6 review, Pixel 6 Pro review
Android Central – Pixel 6 review, Pixel 6 Pro review, Pixel 6 and 6 Pro video review
Android Authority – Pixel 6 Pro review
Engadget – Pixel 6 and 6 Pro review, Pixel 6 and 6 Pro video review
Wired – Pixel 6 and 6 Pro review
CNET – Pixel 6 review, Pixel 6 Pro review, Pixel 6 video review
Gizmodo – Pixel 6 and 6 Pro review
Tech Crunch – Pixel 6 Pro review
Stuff – Pixel 6 Pro review
Pocket-lint – Pixel 6 review, Pixel 6 Pro review, Pixel 6 video review
Mashable – Google Pixel 6 and 6 Pro review
News.com.au – Pixel 6 Pro review
Videos
Dave2D – Pixel 6 Pro Review
The Tech Chap – Pixel 6 Pro review
Tech Spurt – Pixel 6 review, Pixel 6 and 6 Pro camera review
MobileTechReview – Google Pixel 6 Pro Review
HowtoMen – Pixel 6 Pro review
JSL Review – Pixel 6 Pro review
Mike O’Brien – Pixel 6 Pro review
Anthony Lipani – Pixel 6 Pro camera review (focuses mainly on video)
Joshua Vergara – Pixel 6 Pro real world camera test
Lee Zavitz – Pixel 6 Pro Cameras-Good and Bad
Julia Trotti – Pixel 6 Pro Camera review
MrWhosetheBoss – Camera comparison between the Pixel 6 Pro and iPhone 13 Pro Max
SuperSAF – Camera comparison between the Pixel 6 Pro and iPhone 13 Pro Max
AuthenTech Ben Schmanke – Camera comparison between the Pixel 6 Pro and iPhone 13 Pro Max
Tim Schofield – Pixel 6 Pro initial impressions after one week
Short Circuit – Pixel 6 Pro impressions
ETA Prime – Pixel 6 Pro Gaming and Emulation
TK Bay – Pixel 6 Pro Gaming and Media
Juan Bagnell – Pixel 6 Pro Creator Benchmarks
MKBHD goes hands-on with Nothing Phone
Best Smartwatch 2022 – 2023
Here could be different items for any other source on the internet, but this one is framed according to Buyers-Value:
Apple Watch Series 5 (Health Monitoring)
Fitbit Versa 4 (All rounder People)
Garmin Watches (Fenix, Forerunner)
Pebble. Good watches, community driven, strong support, amazing sensors.
But then Fitbit bought them and basically locked down any possible advancement with their patents, slowing down development of smartwatches for years
Nowadays: Garmin watches are my personal favorite. They tend to have better metrics than other companies and so far they refuse to use a “pay per month” program like Fitbit and Oura swapped to.
EU to enforce mandatory USB-C connector for mobile devices incl. phones in 2024
- YouTube issueby /u/Error_Code54 (r/iPhone) on April 22, 2024 at 5:48 pm
iOS 17.4.1 on an iPhone 13 occasionally when playing a yoube video it only shows up on like 1/8 of the screen. Rotating phone brings it back to normal. Didn’t have this issue on the last version of iOS 16. Anyone else experience this? submitted by /u/Error_Code54 [link] [comments]
- Camera App Suggestions and Comparison | iPhone 15 Proby /u/SwordFish9105 (r/iPhone) on April 22, 2024 at 5:43 pm
I'm pretty happy with the iPhone 15 Pro default camera app, but I want to have some extra control over the ISO and Shutter Speed in certain circumstances. I bought the ProCamera app (https://apps.apple.com/us/app/procamera-professional-camera/id694647259) but after a few days of experimenting I concluded that the focus is not that good on this app. I did everything ... manual (+peak) focus, auto focus .. I see the focus is worse compared to the default iPhone camera app. See the photo comparison. So are there any suggestions for a camera app that is as good as the default iPhone camera app but has the ability to control the ISO and Shutter Speed? I do all this because I want to get the best quality possible so that I can print photos in a larger size. Comparison of the default iPhone 15 Pro camera app vs ProCamera app https://i.postimg.cc/VLmCDs27/comparison-iphone-15-pro-default-vs-procamera.png submitted by /u/SwordFish9105 [link] [comments]
- Sleep scheduleby /u/benc-mitchell95 (r/iPhone) on April 22, 2024 at 5:41 pm
I work shifts and wanted to set up a sleep schedule so my watch can track me, is this possible in the health app or will I have to download a separate app to do this? For reference I do two day shifts, two late shifts and two night shifts, and then four days off meaning that my rotation is every ten days. Therefore I end up going to bed at different times every two days. I can’t see a way to set this up however I am new to iPhone so it could be me being dense. submitted by /u/benc-mitchell95 [link] [comments]
- This is what the future iPhone 16 and iPhone 16 Pro Max will look like.by /u/ArseniyKhilk (r/iPhone) on April 22, 2024 at 5:32 pm
What do you think about new camera design? submitted by /u/ArseniyKhilk [link] [comments]
- Coming from Android, silent mode muting random media sounds is so frustratingby /u/turtlintime (r/iPhone) on April 22, 2024 at 5:21 pm
Generally I never really want my phone to beep for random notifications since I use a smart watch for notifications and I kept my android phone on vibrate or silent mode pretty much 24/7. I thought maybe that I could just keep the silent mode on 24/7, but for some reason it mutes random media sounds. For example: snapchat videos I need to mash the volume keys a few times to hear audio, a mobile game I play just refuses to make any sound with the silent switch on, and random other apps have one of these two behaviors (other than dedicated media apps like youtube) I am a bit frustrated because I can't really turn off silent mode because then it will also play sounds unless I disable sounds for every new app I make and you can't do a vibrate only mode without doing that manually for every app notification. I would totally get this behavior if it was behind a switch "silent mode also mutes some media sounds on/off" but it is frustrating we have no control over it. Does anyone else have this situation? Do you guys think it will be fixed/ is this how it has always worked? Do you have any workarounds? submitted by /u/turtlintime [link] [comments]
- Making an iPhone last longby /u/lmfaocatlover (r/iPhone) on April 22, 2024 at 5:11 pm
Any tips to make an iPhone last for 5+ with maximum efficiency? Including batty health and all? For reference: got the iPhone 15 plus variant in 128gb submitted by /u/lmfaocatlover [link] [comments]
- Can the front glass of the iPhone 15 Pro be replaced?by /u/Doroprogamer (r/iPhone) on April 22, 2024 at 5:08 pm
I can’t seem to find an answer to this question: Can the front glass of the iPhone 15 Pro be replaced Without replacing the whole screen,and if it’s possible how much will it cost to repair it officially? submitted by /u/Doroprogamer [link] [comments]
- Help with maintaining an iphoneby /u/collegeweenie (r/iPhone) on April 22, 2024 at 4:55 pm
I just need someone to help me maintain the iphone correctly as I have no idea what im doing. Every iphone I had either got smashed/camera broken/screen scratches... I mean im assuming that im doing something wrong because i cant be the only one that drops the iphone right ... and im buying the new iphone 15pro and i really dont want to mess it up this time.. Do I need to buy specific hardware or grabs? submitted by /u/collegeweenie [link] [comments]
- Apple ID wrong phone numberby /u/connorftw88088 (r/iPhone) on April 22, 2024 at 4:51 pm
I got a notification today that asks me to review my Apple ID phone number and it asks to confirm that this phone number is still my number. Problem is that it says my dad's phone number is the one connected to the account. I don't know why its saying that and I don't know how to change it. submitted by /u/connorftw88088 [link] [comments]
- Can’t track USPS packages anymore since Apple decided it was deceptive fraud.by /u/TheWanderer412 (r/iPhone) on April 22, 2024 at 4:05 pm
submitted by /u/TheWanderer412 [link] [comments]
- Why do different texts have different icons here?by /u/ew435890 (r/iPhone) on April 22, 2024 at 3:46 pm
I noticed that one of my text conversations has the red icon and the rest of them have just the microphone icon. Why are they different? submitted by /u/ew435890 [link] [comments]
- iPhone 11 A2221 & 12 iPhone 12 A2403 Regulatory informationby /u/NeoRebu (r/iPhone) on April 22, 2024 at 3:23 pm
Hello, Would anybody with these exact model numbers be able to attach a picture of the regulatory marks displayed on Legal & Regulatory? This can be located by going to Settings - General and towards the bottom, it has Legal & Regulatory. I am shipping phones overseas and need to know the regulatory markings on these phones as some countries demand them for import. I appreciate any help provided! submitted by /u/NeoRebu [link] [comments]
- Why is apple holding back all this compute power when it comes to AI - iOS can potentially destroy all competition when it comes to AIby /u/CyberCipher35 (r/iPhone) on April 22, 2024 at 1:53 pm
submitted by /u/CyberCipher35 [link] [comments]
- What is the apple subscription UKby /u/millyloui (r/iPhone) on April 22, 2024 at 1:50 pm
I seem to have £1.99 coming out of my account by Apple very regularly. I have no idea what I’ve subscribed to . Any ideas? Thanks . submitted by /u/millyloui [link] [comments]
- Face ID struggle when wearing sunglassesby /u/rickpickel (r/iPhone) on April 22, 2024 at 1:41 pm
Very new to iPhone.... came from android 2 months ago. This one is a bigger struggle than it might sound to most of you. While biking, (🚲) I'd like to use my phone at times, for exmaple change music, or manage navigation. I often bike with sunglasses.. when swiping up, face ID start to trying to recognize me.. and it just keeps going for like 5 full seconds before giving up, allowing me to type my pin. Is it not able to tell immediately that its a person wearing sunglasses and just skip the whole retyring a million times?? Or are there some other shortcut to skip face ID and go straight to pin (preferable a one-hand friendly way) Security policy and my own opinion is to not add face recongnition while wearing masks or shades. so I am really asking my question above, not how to do face ID differently. 😉 submitted by /u/rickpickel [link] [comments]
- Charging iPhone 24/7by /u/Relevant_Strike7214 (r/iPhone) on April 22, 2024 at 1:18 pm
I'm using an iPhone 12 to park 2 US eSIMs while living abroad for 2FA, but sometimes forget to keep it charged. Any real life experience on long-term effects of keeping an iPhone constantly plugged in for months or years? submitted by /u/Relevant_Strike7214 [link] [comments]
- My apps NEVER update automatically even though the settings are set toby /u/Wooden_Hunt248 (r/iPhone) on April 22, 2024 at 12:22 pm
Pissed off Iphone 13 pro max and this has always been the case submitted by /u/Wooden_Hunt248 [link] [comments]
- iPhone 12 1x Blurry when zoomedby /u/AdAshamed8351 (r/iPhone) on April 22, 2024 at 12:12 pm
I have this issue on my iPhone 12 after updating to the latest version where my 1x lens isn’t focusing on far away objects like about 5 meters away, but when I switch to .9 everything is fine with it. What seems to be causing this issue? submitted by /u/AdAshamed8351 [link] [comments]
- Gave out IMEI numberby /u/SMARTKIXD (r/iPhone) on April 22, 2024 at 10:46 am
Hi guys, I’m selling an iphone and it’s been fully reset to factory settings and this person asked for its IMEI number. I didn’t know what it was so I sent it to him but then after some digging online I found out that you’re not supposed to give it out because they can blacklist it or something. I was wondering what harm could he could do if he has the number as I’m selling the phone to someone else now. Also the phone isn’t connected to a network provider or anything. submitted by /u/SMARTKIXD [link] [comments]
- Weekly 'What Should I Buy' and Order/Shipping Threadby /u/AutoModerator (r/iPhone) on April 22, 2024 at 10:30 am
Welcome to the weekly stickied WSIB thread. Have any questions about buying, selling, trading, or giveaways? Ask away! Please remember to adhere to our rules, which can be found in the sidebar. As usual, if you have a serious issue with the subreddit, please contact the moderators directly. This thread is also for questions about preorders and shipments of devices Note: Comments are sorted by /new for your convenience. Here is an archive of all previous "What Should I Buy" threads. This is best viewed on a browser. If on mobile, type on the searchbar [title:"What Should I Buy" author:"AutoModerator"] (without the brackets, and including the quotation marks around the title and author.) submitted by /u/AutoModerator [link] [comments]
50 features in Android 13 you should know about
Runtime permission for notifications. Apps will now have to ask for permission before they can post a notification. Android 13 handles this permission differently based on what Android version the app targets and whether or not it’s newly installed or it was already installed before updating to Android 13, but this generally makes notifications opt-in rather than opt-out. Example.
New Material You dynamic color styles. Android 12 on Pixel phones introduced Google’s dynamic color engine, which grabs a color from your wallpaper to generate 5 tonal palettes. Each of these tonal palettes is comprised of 13 tonal colors of various luminances but with undefined hue and chroma values. By adjusting these values, the color engine can create a bunch of new palettes, ie. “styles.” tl;dr, Android 13 generates far more theme options based on your wallpaper, letting you pick even more colors than before to suit your style. Examples: TONAL_SPOT (default), VIBRANT, EXPRESSIVE, SPRITZ, RAINBOW, FRUIT_SALAD. (Although Google’s dynamic color engine was initially exclusive to Pixels on Android 12, it was added to AOSP in Android 12L and is thus now available by default for all OEM builds. The ThemePicker enhancements that Google made are going to be open source, so OEM devices should be able to surface the same style options that Pixels do.)
Themed Icons. The colors generated by Android’s dynamic color engine can be used to theme homescreen icons as well as in-app UI elements. If you enable the “themed icons” option in Wallpaper & Style (the location of this switch could be different on OEM devices), then apps with a monochromatic icon will have that icon be automatically themed according to the user’s wallpaper. Before versus After.
Bigger and bolder gesture nav bar. The gesture nav pill is bigger and bolder than before. This is one of the first things you’ll probably notice when booting up Android 13. I’m not sure if OEMs can/will tweak this, though. Before versus After.
Per-app language preferences. Finally, you can set the language of an app without changing the language system-wide in settings. You can access the new per-app language preferences in Settings > System > Languages & input > App Languages. Only apps that have opted-in, however, will appear in this list. Screenshot of App Language page for Google Calendar.
Photo Picker. There’s a new Photo Picker that will let you quickly pick images or videos to share with apps. Those apps then get temporary, read-only access to those media files. Apps have to add support for the Photo Picker, but this is quite easy to do and will be available through many libraries soon. Plus, the Photo Picker has already rolled out to Android 11-12L devices through a Google Play System Update, so expect to see a lot of apps add support for this in the near future. Screenshot.
Clipboard editor overlay. When you copy something to the clipboard, you’ll see an overlay in the bottom left corner, similar to when you take a screenshot. This overlay previews what you copied and can show smart actions based on the clip content (open a URL in Chrome, navigate to an address in Maps, etc.) You can also tap the clip preview to launch a text or image editor. Screenshots: 1, 2, 3
QR code scanner shortcut. Android 13 by default will show a Quick Setting tile to launch a QR code scanner. Which app provides the QR code scanner is technically configurable by OEMs, but I believe on devices with GMS, it will be set up to launch a QR code scanner provided by Google Play Services. Screenshot of QS tile. Screenshot of QR scanner.
Redesigned media player. Android 13 revamps the media player experience. You’ll notice the larger volume slider in the media output picker UI and the squiggly progress bar for all media sessions. There’s one other change that I’ll mention next. Do note that OEMs can customize the default style of notifications, so there’s no guarantee the media player will look exactly the same across devices.
New media controls UI. Apps that target Android 13 may show a different set of media controls when running on Android 13. This is because Android 13 derives what media controls to show from the PlaybackState rather than the MediaStyle notification. If you see headlines about apps being updated to support Android 13 media controls, this is what they’re referring to. Here’s a screenshot of media controls on a phone and tablet running Android 13. As you can see, this change unifies how media controls are rendered across Android platforms.
Better control over foreground services. There’s a new “active app” button in the notifications panel. Tap this and you’ll see which apps currently have a foreground service running. For example, music players and fitness trackers need to use foreground services so Android won’t kill them when they’re running in the background. Before Android 13, these foreground services took up space in your notifications panel. Now, you can swipe them away and manage them from the “active app” list. Screenshot of the “active app” button in the notifications panel. Screenshot of the “active app” list.
Game dashboard for more devices. The Game Dashboard that was originally exclusive to the Pixel 6 on Android 12 is coming to more devices on Android 13. Game Dashboard integrates achievements and leaderboards data from Play Games, has a shortcut to stream to YouTube, and has toggles to show a screenshot button, screen recorder button, DND button, and an FPS counter in the in-game floating overlay. You can also change the Game Mode to “battery saver” or “performance”, but this depends on the game. This feature is provided by Google Play Services on Android 13 and has rolled out to several Pixel devices already, but I believe it will come to non-Pixels in the future. Screenshot of Game Dashboard settings. Screenshot of Game Dashboard.
Game Mode improvements. When a game hasn’t added support for the Game Mode API, OEMs can apply game mode interventions to improve the performance of games. In Android 12, OEMs could use ANGLE instead of OpenGLES drivers or apply WindowManager backbuffer resize to reduce the GPU overload. In Android 13, there’s a new FPS override intervention, but this one is opt in. When games opt in, the system can limit the FPS that the game runs at.
Bluetooth LE Audio support. Bluetooth LE Audio is the next-gen Bluetooth standard that promises lower power consumption, higher quality audio (compared to Bluetooth Classic Audio with SBC) with the new LC3 codec, standardized support for hearing aids, location-based audio sharing, and support for broadcasting audio to many devices. Android 13 ships with a Bluetooth stack that’s certified for LE Audio Unicast support (Broadcast Audio is a WIP).
Spatial audio with head tracking support. Spatial audio provides an immersive audio experience by making it seem like the audio moves with your head. Android supports static spatial audio (where the sound seems to move as your head moves) and dynamic spatial audio (where the sound is stuck in space as your head moves). Static spatial audio works with any headphones, while dynamic spatial audio requires a headset with head tracking support. Android 12L added the audio spatializer API needed for integration with third-party apps, while Android 13 introduces the head tracking protocol needed for dynamic spatial audio.
Turn on dark mode at bedtime. Dark theme settings now has an option to have it turn on at bedtime. Your bedtime mode schedule is set by the Digital Wellbeing app. Screenshot.
Control smart home devices without unlocking the device. You can now control smart home devices from the Device Controls menu without unlocking your phone or tablet, but only if the app supports it. You first need to enable “control from locked device” in settings. Video demo.
7-day view in privacy dashboard. The “Privacy dashboard” added in Android 12 only shows sensitive permissions accessed in the last 24 hours, but on Android 13, it’ll let you see that data from the last 7 days. This hasn’t rolled out yet, though. Screenshot of “show 7 days” option in privacy dashboard.
Clipboard auto clear. Android 13 will automatically clear any clipboard item that’s older than 1 hour. I know Gboard already does this, but not everyone uses Gboard.
X-axis transition animation. Any apps that don’t use a custom transition animation seem to now use this shared X-axis transition animation.
Flashlight brightness control. Android 13 has an API to control the flashlight brightness. Yes, OEMs like Samsung have offered this feature for years, but it wasn’t standardized. The only catch is that the OEM has to implement support for this feature in the device’s camera HAL. More info on this feature. Demo + sample app.
Unified Security & Privacy settings. Android has a lot of privacy and security features strewn about in settings. Android 13’s new unified Security & Privacy settings will make it easy to find each of these features. This is not exclusive to Pixel and will be coming to other devices via a Mainline update. Here’s what it looks like.
“Vibrant” theme is now actually vibrant. There was a bug that made the color palette generated from vibrant wallpapers less vibrant than they should be. This was fixed in Android 13, and now the Vibrant theme is actually vibrant! Before versus After.
App drawer in the taskbar. Android 12L introduced the taskbar, but it didn’t have an app drawer, so you had to go to the home screen or recent apps to switch apps. Android 13 fixes this by adding an app drawer in the taskbar. (Yes, I know the Z Fold4 on 12L has an app drawer in the taskbar. Kudos to Samsung for addressing that.) Screenshot of taskbar with app drawer.
Stylus handwriting. Keyboard apps can declare that they support stylus handwriting. If so, then other apps can send a request to launch the keyboard app in its stylus handwriting mode. This is currently in testing and requires flipping a developer option called “stylus handwriting”. You can see this in action with the S22 Ultra on Android 13 + Google Chrome.
File managers can no longer access /Android/data and /Android/obb. Do you use a third-party file manager? Do you ever access files in the /Android/obb or /Android/data folders? Well I have bad news for you. You won’t be able to use your favorite file managers to access those folders anymore, since the loophole they used to do was has been closed. Yes, this was only possible through a loophole, since Scoped Storage in Android 11 was designed to block apps from accessing those folders.
Android may block the user from enabling Accessibility and Notification Listeners for sideloaded apps. Android’s Accessibility and Notification Listener APIs are really powerful, and they’re often abused by malware. Google has been cracking down on apps misusing APIs, and in Android 13, you’ll be blocked from enabling an app’s Accessibility Service or Notification Listener if you sideloaded that app from outside an app store. (There is a way to unblock access, fortunately.) The exact details are more complicated, so I recommend reading this article for the full breakdown. Screenshot of the “Restricted Setting” dialog and the toggle to allow restricted settings.
Apps can now only request one-time access to device logs. If you grant an app the ability to read system logs (ie. logcat), then in Android 13, you’ll see a confirmation dialog every time that app tries to read those logs. If you use an automation app like Tasker, you might hate this change. Screenshot of the dialog.
More granular media file permissions. Scoped Storage changed how apps access files, making it so that the READ_EXTERNAL_STORAGE permission doesn’t grant broad access to the external shared storage. Instead, it only let apps access media files (including audio, video, and image files) owned by other apps that reside in media store collections. In Android 13, apps targeting the release will have the request individual permissions to access audio files, video files, or image files owned by other apps, making media file access even more granular.
Revamped multi-user UI. There’s a couple of enhancements to the multi-user experience in Android 13. First of all, there’s a new fullscreen user profile switcher for large screen devices. There’s also a revamped UI for adding a new user that even uses the new Photo Picker to select the profile picture from your gallery. Next, there’s an optional user profile switcher shortcut that sits in the status bar, but it’s disabled by default and intended for large screen devices. Finally, there’s an optional user switcher shortcut on the keyguard, but again, this may only appear on tablets or other large screen devices.
Accessibility audio description. There’s a new toggle to enable audio descriptions globally. Instead of toggling audio descriptions on a per-app basis, media apps can read the status of this global toggle and enable audio descriptions accordingly. This is more aimed at Android TV but is also applicable to handhelds. Screenshot of the toggle.
Accessibility magnifier can now follow the text as you type. If you use the magnification feature to zoom in on text, you might like the new “follow typing” toggle that’s been added. Toggling this will make the magnification area automatically follow the text as you type. Here’s a demo of the feature.
Quick Settings tiles for color correction & one-handed mode. If you use Android’s color correction or one-handed mode feature and want quick access to toggle them, you can find new Quick Settings tiles to do so in Android 13.
Drag to launch multiple instances of an app in split-screen. Android 12 added multi-instance support, making it possible to launch two instances of the same activity. For example, you can launch two Chrome windows in split-screen mode. Android 13 builds on this by letting you drag to launch a second instance of an activity when in split-screen view, provided the activity supports it.
Take away an app’s ability to turn on the screen. There’s a new “turn screen on” permission that you can control in Settings > Apps > Special app access. It’s quite self-explanatory. Here’s a screenshot of the permission page.
Control background access of body sensors. Apps can access data from heart rate, temperature, and blood oxygen level sensors through the BODY_SENSORS permission. Prior to Android 13, apps that had this permission could access that data while running in the background. Android 13 changes this by making those apps request a new permission called BODY_SENSORS_BACKGROUND.
Apps no longer need location access to scan for nearby WiFi devices. It’s possible to track your location by collecting data on nearby Bluetooth and Wi-Fi devices over time, which is why earlier versions of Android made it so apps had to hold location permissions to read Bluetooth and Wi-Fi scan results. That got annoying and confusing for users, so Android 12 decoupled Bluetooth APIs from the location permission. Android 13 follows up by decoupling Wi-Fi scanning from location permissions.
Virtualization support. This one is really complicated, but basically, Android 13 introduces a virtual machine framework through the new Virtualization module. Google is deploying a modified version of the Linux KVM feature (pKVM to be precise) as the hypervisor, with crosvm as the virtual machine manager. Google is using this for a fairly obscure purpose (isolated compilation), but devs have figured out how to boot Linux and even Windows VMs. You’ll need a device that supports pKVM, though.
Camera2 improvements. Camera2 is the underlying API used by camera apps, and it’s getting some welcome additions in Android 13. First, it has added HDR video capture support, so third-party camera apps can finally capture HDR video, provided the OEM exposed support for this in the camera HAL. There’s a new API for preview stabilization, and viewfinder jitter has been reduced as well. These are more developer-focused improvements, but I thought you should be aware of them in case you use a third-party camera app.
Faster hyphenation. Text wrapping will be better in Android 13, as many apps will insert hyphens at the end of a line in a text field. Hyphenation seems like a simple matter, but before Android 13, it was quite taxing on the CPU. Android 13 improves hyphenation performance by as much as 200%.
Improved Japanese text wrapping. Apps that support Japanese can now wrap text by “Bunsetsu”, which is the smallest unit of words that’s coherent, instead of by character. This will make text more readable by Japanese users.
Improved line heights for non-Latin scripts. Android 13 improves support for non-Latin scripts like Tamil, Burmese, Telugu, and Tibetan. The OS uses a line height that’s adapted for each language, preventing clipping and improving the positioning of characters.
MIDI 2.0 support. MIDI 2.0 was introduced in late 2020 and adds bi-directionality so devices can communicate with each other to auto-configure themselves or exchance info on available functionality. It also makes controllers easier to use and adds 32-bit resolution support.
DNS-over-HTTP/3 support. Android 9 added encrypted DNS (ie. Private DNS) support through the DNS-over-TLS protocol. Android 13 adds support for the DNS-over-HTTP/3 protocol. This implementation offers better performance and security. Right now, Android’s DNS-over-HTTP/3 implementation only allows using Google and Cloudflare as providers. This feature has been backported to all GMS Android devices running Android 11-12L and some Android 10 devices.
Android’s Bluetooth stack becomes a Mainline module. Bluetooth vulnerabilities are pretty common, so in an effort to improve security, Android 13 turns Android’s Bluetooth stack into an updatable Project Mainline module. This means it can be updated through Google Play like other modular system components. However, I’m not sure if this module will be mandatory yet for OEMs.
Android’s ultra-wideband stack becomes a Mainline module. In a similar vein, Android’s ultra-wide band stack that was just introduced in Android 12 has been turned into a modular system component in Android 13. There aren’t many devices yet with UWB hardware, but with this + the new UWB Jetpack library, we should start seeing more apps make use of this hardware and Google expand UWB functionality in Android outside of OS updates.
Binary transparency. If you care about security, then you may be curious whether or not the binaries installed on your device match what’s included in the official factory images. Android 13’s binary transparency manager lets you easily get the VBMeta digest and build fingerprints of the partitions and modules on your device, so you can compare them with the official images. Note that while Google’s the only one doing this so far (AFAIK), there’s nothing preventing other OEMs from publishing their own transparency logs.
Dynamic System Updates become a lot faster. Dynamic System Updates (DSU) makes it easy to install a Generic System Image (GSI) without overwriting your device’s original installation or wiping your data. All you have to do is send an intent or just go to Developer Options to install one of Google’s official GSIs through the “DSU Loader” setting. Android 13 makes GSI installation through DSU faster and more interactive.
ART improvements bring lower memory use and faster runtime performance. An update to the Android Runtime (ART) module will introduce a new garbage collection algorithm based on Linux’s userfaultd feature, which may reduce the chance of the OS killing off background processes.
Wallpaper dimming. There’s a new API to dim the wallpaper, and it’s being used by the Digital Wellbeing app to darken wallpapers at bedtime so bright/vibrant wallpapers will be less blinding. Before versus After.
Bonus: The Easter egg. Of course, we can’t forget this one. There’s a new Easter egg in Android 13, because of course there is! Like usual, you access it by tapping repeatedly on the “Android version” field in Settings > About phone. When the clock appears, turn it so the hands point at 1:00. Surrounding the Android 13 logo will be a bunch of bubbles. Long press those to make a bunch of emojis appear. Long press again to cycle through the various emoji combinations.
There are quite a few posts regarding this issue but since none had the answer that ultimately fixed my issue I thought I would make my own.
Just to clarify my issue & situation: 3rd party apps would not open links that they should’ve been when clicked on from the Google search app. For example Sync not opening Reddit links, and Youtube Vanced not opening Youtube links. Anytime I would click one of these links I would be redirected to the Play Store to install the respective app. I had Youtube disabled and “opening verified links” turned off before disabling it, and I didn’t even have Reddit installed at all. Both Sync and Vanced had Open Verified Links turned on and all the options checked. I had previously reset all default apps preferences, and even got a new phone (went from Pixel 6 Pro to Pixel 7 Pro) and the issue hung around.
After a good amount of forum diving I found some random article saying to clear the storage and cache of the following 3 apps: Android System Webview, Google Play Services, and Google Services Framework, then reboot. You can do this by going into Settings > Apps > All apps > click the 3 dots in the top right and hit Show System > click on each app and go to storage and cache. Since I did all 3 I don’t actually know if it was one or all of them that fixed it unfortunately, but this fixed my almost 2 year problem.
Hopefully this helps someone else out there frustrated as hell with how Android handles links these days. Sorry for the lengthy post!
TL;DR if you’ve tried everything the way it’s supposed to work, clear the storage and cache for Android System Webview, Google Play Services, and Google Services Framework, then reboot.
Machine Learning For Dummies DuckDuckGo now lets all Android users block trackers in their apps
- Is it possible to transfer sign-in data of all the apps/emails/credit card/Apple Watch?
I recently transferred data from an iPhone 12 PM to a 14 PM using Apple’s Quick Start feature. Simply keep both phones near each other and follow the onscreen prompts. Took most of an hour to do 120 GB, so for 72 GB, expect at least 20-25 min.
Now transferring this way doesn’t guarantee every little thing transfers over, but a vast majority of it should (like 98-99%) including Apple Wallet items. In my case, I had to go through Face ID setup again (where you move your head in a circle) on the new phone. Afterwards, most simple apps remembered my sign-on information and didn’t prompt me to re-enter. The exception was a few financial apps, like banking apps, that prompted for my password and to trust the new device.
As for Apple Watch…
It can only be paired to one device at a time. You’ll need to unpair it first from the Apple Watch app on the iPhone 11. Then pair it to the new iPhone. Afterward, you’ll notice that your Apple Watch history/data is still intact.
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One final note about going the iCloud route…This option works too, but it’s slower. You might have had problems because you forgot to do a full backup ahead of time. In iCloud’s settings, obviously you would enable everything that you want to transfer over, but then you would need to perform a manual iCloud backup. Make sure it completes, wait a few min afterward, then start the restore on the new iPhone.
In most cases, you shouldn’t need to use both iCloud and Quick Start. Both work fine independently of one another.
- Total Cookie Protection is now available for Firefox on Android
- How to transfer Apple Health data to Google Fit? Apple Health and Google Fit are two of the most popular health and fitness applications available. While they both offer a wealth of features, Apple Health is only available on Apple devices, while Google Fit can be used on both Android and Apple devices. As a result, many users find themselves switching between the two platforms. Luckily, it is possible to transfer data between Apple Health and Google Fit. The process is relatively simple and only requires a few steps. First, open the Apple Health app and tap the “Settings” tab. Next, select “Export Health Data.” Choose “Google Fit” as the export format and tap “Export.” Finally, open the Google Fit app and go to “Settings.” Select “Import Data” and choose “Apple Health” as the file type. Your Apple Health data will now be transferred to Google Fit!
In Summary:
First, open Apple Health and tap the ‘Sources’ tab. Next, tap ‘Add Data Source’ and select ‘Google Fit’. You will then be prompted to enter your Google account credentials. Once you’ve signed in, you’ll be able to choose which data types you’d like to sync.
Next, open Google Fit and tap the ‘ Devices’ tab. Here, you should see Apple Health listed as a connected device. Tap on it and select the data types that you’d like to sync. Finally, tap ‘Sync Now’ to transfer the data.
App to make it easier to share screenshots and videos from Android to your Mac
I made a little app that makes sending photos and videos from your Android test devices to your Mac a breeze, called Ubidrop.
On every mobile team I worked in the past, our QAs always had issues with attaching photos and videos of bugs on (Jira) tickets. Sending files from Android to Macs have always been a pain and having to do that multiple times in a day can easily be a huge pain.
Ubidrop is really simple to use: you take a screenshot of your screen (or pick a file via a gallery app) and then ‘Share’ the photo to ‘Ubidrop’. Ubidrop will then find nearby devices, and then you choose the Mac you would like to share the photo to.
You can see an example and try it out for free at https://www.ubidrop.com. No credit cards or sign ups required.
How can I trace the location of my lost phone by phone number or IMEI number?
There are a few steps you can take to try to trace the location of a lost phone using the phone number or IMEI number:
Contact your phone service provider: If you have lost your phone and you know the phone number, you can try contacting your phone service provider to see if they can help you locate the phone. Some service providers have tools that can help you track the location of a lost phone, or they may be able to remotely lock or erase the phone to protect your personal information.
Use a phone tracking app: If you have previously installed a phone tracking app on your phone, such as Find My Phone or Lookout, you may be able to use the app to locate your lost phone. These apps typically allow you to remotely track the location of your phone, lock it, or erase its data.
Use the IMEI number: The IMEI (International Mobile Equipment Identity) number is a unique code that is assigned to every mobile phone. You can often find the IMEI number on the back of the phone, or you can obtain it by dialing *#06# on the phone. If you have the IMEI number and your phone was stolen, you may be able to work with law enforcement to try to locate the phone using the IMEI number.
Overall, it is important to act quickly if you have lost your phone, as this can increase the chances of being able to locate it or protect your personal information. If you are unable to locate your phone using these methods, you may want to consider purchasing a new phone and taking steps to protect your personal information.
What is an iPhone’s IMEI identifier and what are its benefits?
An iPhone’s IMEI (International Mobile Equipment Identity) identifier is a unique 15-digit number that is assigned to each mobile device. It is used to identify and track the device, and is typically used by mobile network operators to authenticate the device when it is used on their network.
The IMEI identifier has a number of benefits, including:
Device identification: The IMEI identifier can be used to identify a specific device, which can be useful for tracking and locating a lost or stolen device.
Fraud prevention: The IMEI identifier can be used to help prevent fraudulent activity, such as the use of a stolen or unauthorized device on a mobile network.
Device blocking: If a device is lost or stolen, the IMEI identifier can be used to block the device from being used on any mobile network.
Warranty tracking: The IMEI identifier can be used to track the warranty status of a device and to verify that it is eligible for repairs or other support.
Overall, the IMEI identifier is an important tool for identifying and tracking mobile devices, and is used by mobile network operators and other organizations to help ensure the security and integrity of the mobile network.
My iPhone 13 Pro Max dropped to 98% after 5 charge cycles. I’m currently at 65 charge cycles. It dropped to 99% after 60 complete charge cycles. Is this normal?
It is not uncommon for the capacity of a lithium-ion battery, like the one used in the iPhone, to decrease slightly over time as the battery goes through charge cycles. This is because each time a battery is charged and discharged, some of the materials in the battery degrade, reducing the overall capacity of the battery. It is also possible that your phone’s battery capacity decreases faster than others, but without more data on the same phone over the time, it’s hard to tell.
The battery on your iPhone 13 Pro Max is designed to retain up to 80% of its original capacity at 1000 complete charge cycles. However, this can vary depending on the way you use and charge your phone, and if your phone is consistently exposed to extreme temperatures, for example.
If you believe the battery performance on your iPhone 13 Pro Max is not normal, you can check the battery health information in the settings app, and contact apple for a warranty check or replacement.
How can I tell if somebody has access to my Samsung phone or if my calls are being forwarded or diverted?
There are a few signs that could indicate that someone has access to your Samsung phone or that your calls are being forwarded or diverted:
Unfamiliar numbers in your call log: If you see calls from numbers that you don’t recognize in your call log, it could be a sign that your calls are being forwarded or diverted to another phone.
Strange or unexpected messages: If you receive text messages or notifications that you didn’t expect or that don’t make sense, it could be a sign that someone is accessing your phone.
Battery drain or data usage: If your phone’s battery is draining faster than normal or if you are using more data than usual, it could be a sign that someone is using your phone.
Suspicious Apps or process running in the background. Sometimes spyware, malware or any sort of malicious software could be running in the background which can forward your calls, read messages and so on.
Unusual noise: If you hear strange noise or static during phone calls, it could be a sign that someone is listening in on your conversations.
It’s important to note that some of these signs could also be caused by other issues, such as a malfunctioning phone or a problem with your network or carrier.
Additionally, You can also check the call forwarding settings on your phone, these are usually found in the phone settings or in the settings of your phone’s dialer app. If you find that call forwarding is enabled, but you didn’t set it up, it could be an indication that someone has access to your phone.
If you suspect that your phone is being accessed or that your calls are being forwarded or diverted without your knowledge, it’s important to take steps to secure your phone and protect your personal information.
How do I change the battery health of a phone to a good one using ADB?
ADB, or Android Debug Bridge, is a tool that allows developers to communicate with an Android device over a USB connection. One of the things that you can do with ADB is to change the battery health status of a phone. However, this is not a recommended or a safe way to improve the battery health of a phone and can lead to negative consequences.
You can’t change the battery health of a phone using ADB, you can only report the current health status of the battery. Also, modifying the battery health status could lead to a number of issues and it could also void your device’s warranty if done incorrectly.
The proper way to improve battery health on a phone is to take good care of the battery, such as:
- Keep the phone at a moderate temperature
- Uninstall apps that are not in use
- Reduce screen brightness and timeout
- Use original charger and cable
- Avoid overcharging or letting the battery discharge fully -Try not to use the phone while charging
If you are still experiencing issues with the battery health of your phone and you suspect that it is faulty, you can contact the manufacturer or the place of purchase for a warranty check or replacement.
What is the maximum discharge rate of the battery in an average smartphone? I am speaking maximum load possible with full brightness, full volume, 100% APU utilization and maximum throughput on 4G/5G, bluetooth and wifi.
The maximum discharge rate of a battery in an average smartphone can vary depending on a number of factors, including the type of battery used, the capacity of the battery, and the power management features of the phone.
Typically, the discharge rate of a smartphone battery under heavy load can range from around 2 to 4 amperes, or 2,000 to 4,000 milliamperes (mA). This is assuming full brightness, maximum volume, 100% CPU and GPU utilization, maximum throughput on 4G/5G, Bluetooth and Wi-Fi, and all other features turned on. However, this value is highly dependent on the specific phone model, age of the battery, and the state of the battery health.
Keep in mind that this kind of usage is highly unusual and not recommended as it will drain the battery very quickly and will likely cause the phone to heat up which is not good for the device and could even damage it. Under normal usage, the discharge rate will be lower, around 1A to 2A depending on the usage scenario and the device.
It’s also important to keep in mind that as the battery ages, it’s capacity will decrease and the discharge rate will increase to reach the same level of performance, this means that the same phone will have a different maximum discharge rate as the battery ages.
Which are the best top 5 smartphones of 2023?
The market for smartphones is constantly changing, with new models and technologies being released all the time. It would be difficult for me to provide an accurate list without the most recent information.
Keep in mind that the best smartphone for you will depend on your individual needs and preferences. Some people may prioritize a high-resolution camera, while others may place more importance on a long-lasting battery or a large screen. It’s generally a good idea to research and compare different smartphones based on their features and specifications, and to read reviews from experts and users to get a better idea of their performance and reliability.
Also, you may want to consider the brand, design, price and overall customer service or post-purchase service when buying a phone. Some brands are known to have better customer service than others, and that could be a factor to take into consideration when making your decision.
From Samsung to Apple, these five smartphones offer technological features that make them a cut above the rest this year. Whether it’s the multiple cameras, long-lasting batteries or expanding storage capabilities, smartphone users from all walks of life can find something worth investing in from this list of top 5 smartphones for 2023.
How do I check if an Android phone is ever rooted?
Rooting an Android phone refers to the process of gaining administrative access to the phone’s operating system, which allows users to modify the software, install custom ROMs, and access system-level settings. If a phone has been rooted, it will have access to system files that are not available on a non-rooted device.
There are a few ways to check if an Android phone has been rooted:
Check for a “Superuser” or “SuperSU” app: One of the most common signs that an Android phone has been rooted is the presence of a “Superuser” or “SuperSU” app. This app grants administrative access to the phone’s operating system and is typically installed as part of the rooting process.
Use a Root Checker app: There are several free apps available on the Google Play Store that can check if a phone has been rooted. These apps typically check for the presence of the “su” binary or other system files that are typically present on a rooted device.
Check for modified system files: If a phone has been rooted, it may have modified system files that are not found on a non-rooted device. These files are typically located in the /system directory, and you can check for them using a file manager app or by using ADB (Android Debug Bridge) commands.
Check for tampered settings, for example, the ability to disable signature verification on the device, or if some apps are not working due to “security” issues.
Keep in mind that rooting a device void the device’s warranty and could also expose the device to security vulnerabilities, So, it’s important to weigh the benefits and risks before attempting to root your device, And if you are not familiar with the process, you should leave it to professionals.
Can the LiDAR sensor in an iPhone 14 Pro be used with one of the cameras to shoot 3D stills or videos?
LiDAR, or Light Detection and Ranging, is a technology that uses laser beams to measure the distance between a sensor and the objects in its field of view. The LiDAR sensor in an iPhone 14 Pro can be used to improve the phone’s augmented reality (AR) capabilities and to improve the camera’s autofocus and low-light performance. It can also be used to scan and measure objects in 3D and create 3D maps of the environment.
It’s possible to use LiDAR sensor in an iPhone 14 Pro with the cameras to create 3D stills and videos, as the sensor can provide depth information that can be used to create 3D models of objects and scenes. However, it’s important to note that the feature is not yet officially announced by Apple and has not been confirmed.
There are 3rd party apps that allow you to take 3D photos and videos using the LiDAR sensor on the iPhone 14 Pro, but it’s important to note that these apps are not officially endorsed by Apple and the results may vary depending on the app and the environment.
In any case, the LiDAR sensor on the iPhone 14 Pro can be a powerful tool for creating more realistic and engaging AR experiences, as well as for enhancing the phone’s photography and videography capabilities.
Does my iPhone record when my sims are removed and swapped about? Can I check back on the dates etc?
Your iPhone may not automatically record when your SIM card is removed or swapped. However, you may be able to check the dates of when your SIM card was last used or when it was last swapped by checking the following:
Check your cellular settings: You can go to Settings > Cellular > Cellular Data Options > Cellular Data Usage. You should see a list of the dates that your iPhone last used your SIM card.
Check the iTunes Backup: If you have been backing up your iPhone to iTunes, you may be able to check the dates of when your SIM card was last used or swapped in the backup data.
Check your call logs: You can go to the Phone app and check the call logs for calls made or received on your iPhone. Each call log entry includes the date and time that the call was made or received.
Check your phone’s logs: Some iPhones may have a feature that records phone logs including all the changes and events that happen on the phone. However, this feature might not be available on all phone models or versions, and the logs might have been deleted by user or the system.
Keep in mind that the above methods are not guarantees that you will be able to find the information you’re looking for, as the data might be deleted or not available, or the logs might not show the specific SIM swap events. Also, if the phone has been in the hands of someone else they may have done a factory reset or wiped the device which would also erase the logs.
What is DRM-restricted content on Apple?
DRM, or Digital Rights Management, refers to technology that is used to control and restrict the use of digital content, such as music, videos, and e-books. On Apple devices, DRM-restricted content is typically content that is protected by Apple’s FairPlay technology.
DRM-restricted content on Apple devices includes:
- Music and videos purchased from the iTunes Store
- Apple Music songs and playlists
- TV shows and movies purchased or rented from the iTunes Store
- iBooks and audiobooks purchased from the iBooks Store
- Podcasts from iTunes Store
This content is protected by digital rights management and can only be played on authorized Apple devices that are associated with your Apple ID. If you try to play this content on a device that is not authorized, you will typically receive an error message and will not be able to play the content.
Additionally, Apple DRM-restricted content can only be played using the official Apple apps, such as iTunes, Music, TV, or iBooks and not on other third-party apps or other non-apple devices.
Some users may find the DRM-restrictions on content as a limitation to their usage and flexibility, but it’s important to note that it’s in place to ensure the content rights are respected and not pirated by unauthorized parties.
Can I use a second SIM in my iPhone with an eSIM plan?
Yes, you can use a second SIM in an iPhone with an eSIM plan. eSIM technology allows you to add a second SIM to your iPhone without using a physical SIM card. Instead, the SIM information is stored electronically on the device. This means that you can have two phone numbers on one iPhone, and switch between them easily. The iPhone XS and newer models support Dual SIM. Dual SIM Dual Standby (DSDS) or Dual SIM Dual Active (DSDA) depends on the carrier and the plan. You’ll need a carrier that support eSIM or the service to switch from Physical SIM to eSIM and need to have compatible iPhone model.
How does an app work on Android Wear?
An app on Android Wear is essentially a streamlined version of the corresponding app on an Android phone, designed to take advantage of the smaller screen and other unique features of a smartwatch. When an Android app is installed on an Android Wear device, it is automatically mirrored to the watch, although developers can also create specific Android Wear versions of their apps if they prefer.
Users interact with Android Wear apps using gestures and voice commands, rather than by tapping on the screen. They can also receive notifications, such as incoming calls or messages, directly on their watch, and can respond to these notifications using voice commands or by writing with their finger.
Because smartwatch has less battery life and processing power than smartphones, app designed for Android Wear should be simple and lightweight with minimal functionality.
Smartphone 101 – Pick a Smartphone For Me
How to make your laptop last longer with AI – Best laptops in 2022 – 2023
AI Dashboard is available on the Web, Apple, Google, and Microsoft, PRO version
How to make your laptop last longer with AI
The Benefits of AI for Laptops
One of the benefits of AI is that it can help to improve the efficiency of your laptop. For example, if you frequently use certain programs or visit certain websites, AI can learn your habits and pre-load these programs or websites so that they’re ready for you when you need them. This can help to save time and improve your productivity. Additionally, AI can also help to optimize your battery life by learning your usage patterns and making adjustments accordingly.
Another benefit of AI is that it can help to protect your laptop from malware and other security threats. This is because AI is constantly learning and evolving, which means that it can quickly identify new security threats as they arise and take steps to protect your laptop from them. Additionally, AI can also help to keep your personal data safe by encrypting it and storing it in a secure location.
The Drawbacks of AI for Laptops
While there are several benefits to using AI on your laptop, there are also some drawbacks that you should be aware of. One of the main drawbacks is that AI requires a lot of processing power, which can drain your battery life quickly. Additionally, if you’re not careful, you may accidentally give away too much personal information to an AI program without realizing it. Finally, there is always the possibility that an AI program could malfunction or become corrupted, which could lead to serious problems for your laptop.
Laptop Longevity Poll: Years until failure – Most common repairs
We never hear about broken or worn out products.
The left chart is time until total failure, left chart are the most common repairs.
Data: polls on r/productfails with 200 – 300 votes. I’m well aware that this data is not representative, but this is a good start to raise awareness about product longevity and repairability.
Tools: Canva
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To conclude:
Overall, the advantages of using AI on your laptop outweigh the disadvantages. However, you should still be aware of the potential risks involved before you install any AI programs on your device. If you do decide to use AI on your laptop, be sure to install a reputable program from a trusted source.
Laptop Longevity Poll: What was the most common repairs you needed on your laptop?
Let’s collect some more data about the longevity and repairability of laptops.
What tips do you have for prolonging the life of a laptop? Any tips and tricks for common repairs?
It will always be the battery. If you’re buying a laptop, make sure it has a replaceable battery OR an easily accessible one that you can remove yourself.
I have so many laptops with zero issues, including batteries. Never leave a laptop plugged in.
Of all the ones I see here are the common issues:
- Power connectors: charging ports get pushed and pulled by people tripping over the cord or smashing the connector into their knees, the wall, or the floor.
- Hinges for the screen. Grabbing the screen by the corner, over extending, or rough treatment break screens or the small connectors internally that go to them
- Keyboards. The keys can wear and fade, or junk gets inside them and makes the keys inoperable.
Let’s collect some more data about the longevity and repairability of laptops.
What tips do you have for prolonging the life of a laptop? Any tips and tricks for common repairs?
When our laptops start to slow down or show signs of wear, it can be frustrating. The good news is that there are things you can do to prolong the life of your laptop and make it last longer. Below are some tips on how to make your laptop last longer.
- Keep your laptop clean
One of the best ways to prolong the life of your laptop is to keep it clean. Just like any other piece of technology, laptops can accumulate dust and dirt over time. This can cause the fans to work harder and eventually overheat the system. To prevent this from happening, make sure to clean your laptop regularly. You can use a damp cloth or compressed air to remove dust from the keyboard and vents. - Use a cooling pad
Another way to help keep your laptop cool is to use a cooling pad. Cooling pads help dissipate heat away from the laptop, which can prolong its lifespan. Many cooling pads also come with built-in fans, which can further help keep your laptop cool. - Avoid overheating
Overheating is one of the leading causes of laptops shutting down prematurely. To avoid overheating, make sure that you’re not blocking any of the vents on your laptop and that you’re not using it on a soft surface like a bed or couch where it can’t breathe. Additionally, if you’re going to be using your laptop for an extended period of time, consider investing in a stand that will elevate it slightly so that air can circulate more easily. - Update your software regularly
One thing that many people don’t realize is that keeping your software up-to-date can actually help prolong the life of your laptop. That’s because updates often include patches for security vulnerabilities and other bugs that could potentially cause problems down the line. So, if you want to keep your laptop running smoothly, make sure you’re staying up-to-date on all the latest software updates. - Don’t overload your laptop
Another common mistake people make is loading their laptops down with too many programs and files. This can actually put strain on the system and cause it to run slower or even crash. So, if you want to keep your laptop running at its best, only install the programs and files you need and regularly delete anything you don’t use anymore.
While there’s no guaranteed way to make your laptop last forever, following these tips can help prolong its lifespan so you can get the most out of it. Taking care of your laptop is important not only for financial reasons but also for productivity reasons. After all, a well-running laptop can mean the difference between getting work done and falling behind. So if you want to keep your laptop running smoothly for as long as possible, make sure you’re following these tips!
Below are the best laptops in 2022-2023:
How artificial intelligence is changing the laptop landscape
In recent years, we’ve seen a surge in the development of artificial intelligence (AI) and its applications. From smart speakers to self-driving cars, it seems like there’s no limit to what AI can do. But what about laptops? How is AI changing the way we use these essential devices? Let’s take a look.
One of the most significant ways AI is changing laptops is in terms of performance. With traditional laptops, the processor is the biggest determining factor in how well the device will perform. However, with AI-powered laptops, that’s no longer the case. Thanks to their ability to handle complex tasks quickly and efficiently, AI-powered laptops are able to outperform their traditional counterparts when it comes to things like video editing and rendering, 3D modeling, and even gaming.
Another area where AI is having a major impact on laptops is battery life. One of the biggest complaints about laptops has always been that they need to be plugged in constantly in order to function properly. However, with AI-powered laptops, that’s no longer an issue. Thanks to their efficient use of power, AI-powered laptops can last for hours on end without needing to be plugged in. This means you can finally say goodbye to those pesky low battery warnings!
Finally, AI is also changing the way we interact with our laptops. Thanks to voice recognition software and other advancements, it’s now possible to control your laptop entirely hands-free. This means you can finally get some work done while you’re on the go without having to worry about lugging around a heavy laptop or dealing with tangled wires. All you need is your voice!
As you can see, AI is having a major impact on laptops and how we use them. From improved performance to longer battery life, there’s no doubt that AI-powered laptops are the way of the future. So if you’re in the market for a new laptop, be sure to keep an eye out for one with AI capabilities! You won’t be disappointed.
- Switching from Windows to Apple: Which MacBook should I get?by /u/alchemy15 (Apple Macbook) on April 22, 2024 at 7:47 am
I just switched from Android to Apple phone-wise and I'm thinking of doing the same laptop-wise. Which MacBook do you think I should get considering I work remotely and I need my battery to last? I will mainly use it for work (email, google docs, hubspot, social media) and content creation. I was considering the Air M2 512GB, but I never owned a MacBook so I'm not sure.. submitted by /u/alchemy15 [link] [comments]
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https://preview.redd.it/c3ku44i8izvc1.png?width=622&format=png&auto=webp&s=21e05e7042f43abefd925bcb935fd51ef0cc268c submitted by /u/JonasMi [link] [comments]
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I spilled sugary milk all over my MacBook 5 mins ago I saw some posts online to turn it upside down so l did that put tissues and lifted and dropped it on the bed to get the milk out and it's coming out but I'm scared if milk is left it will cause mould now should I put alchohol in the keyboard and follow the same process?? No Apple care btw Sad submitted by /u/Sniperx1230 [link] [comments]
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Hey everyone! I noticed that my new M3 MacBook Air's lid wobbles slightly as show over here https://imgur.com/a/xIVkNT1 Is this considered normal? I'm still in the 14-day return window and would like to return / exchange it if this isn't the norm. Thanks. submitted by /u/MrRobot_MKV [link] [comments]
- Amazing MacBook Deal at BestBuy?by /u/Historical-Pen-2658 (Apple Macbook) on April 22, 2024 at 6:04 am
Hey there, I have been looking for a MacBook for a while now and I was planning on taking the M3 MacBook Air (Base model), which comes with 8GB ram & 256gb SSD for 1199$ (w/student’s discount). However, I stumbled on a weird deal on best buy, a M2 MacBook air with 1TB of SSD & 16GB of Ram, for only 1499$! Does anyone know whether bestbuy’s macbooks are actually reliable and not open boxes? Additionally, is the deal really worth it? submitted by /u/Historical-Pen-2658 [link] [comments]
- WHICH MACBOOK AIR?by /u/SweetAffectionate430 (Apple Macbook) on April 22, 2024 at 5:39 am
I'm into STEM, Al/ML, and programming. Need this for college. (Note: Prices mentioned are from Student Discount India) View Poll submitted by /u/SweetAffectionate430 [link] [comments]
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i haven't been able to find good results on google, it keeps switching from fair condition to check battery submitted by /u/leedleman2309 [link] [comments]
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I know that there is an "Optimized Battery Charging" option but after one week of ownership macOS still hasn't "learned" that I want to limit the damned battery to 80%. Why does Apple have to be like this? Of course they're too good to simply give you a "Limit to 80%" button, they have to backhand it through some gimmick that fails to work. Is there a known workaround? If there's some way I could programatically limit the Macbook's charging I could develop something of my own as well, but found nothing of the like. Thanks in advance! submitted by /u/VinceMiguel [link] [comments]
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Hey all, I posted this in macbookrepair, but figured I should post it here. I was doing a keyboard swap on my macbook air a2337 2020 and I accidentally pulled too hard on the backlight cable ripping out the case end port. Any shot to fix or replace this? I looked into a top case swap, but ifixit's top case images shows that it doesn't include that port at all. The first image has the port there. I didn't notice it vroke until it fell off. The second photo is currently. submitted by /u/CTRLZ0Y [link] [comments]
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I need this laptop for my university studies in computer science, planning to use it for at least six to seven years or even more. Right now, I'm into Al/ML, and programming, but I might explore other stuff like video editing in college, and in the future, I might go into some ML research thing. Option 1: • MacBook Air with M3 chip, 256GB storage, and 16GB RAM • Price: $1499 Option 2: • MacBook Air with M2 chip, 512GB storage, and 16GB RAM • Price: $1535 Option 3: • MacBook Air with M2 chip, 256GB storage, and 16GB RAM • Price: $1295 Option 4: • MacBook Air with M2 chip, 256GB storage, and 24GB RAM • Price: $1511 (Note: Prices mentioned are from Student Discount India) I'm leaning towards the M2 chip with 512/16 storage due to the slight price difference of only $35 compared to the M3 chip with 256/16. However, I'm also considering the M3 chip with 256/16 and M2 256/24 for its performance benefits. On the other hand, the M2 chip with 256/16 storage is more budget-friendly, but l'm concerned about its speed because of single NAND compared to the other options. Thanks. submitted by /u/SweetAffectionate430 [link] [comments]
- Help on a m2 air possible purchaseby /u/Raja4x78996 (Apple Macbook) on April 21, 2024 at 11:34 pm
So I don’t want the 8gb that is just bothering me I want the 16 256 and I want to know if it’s really worth to buy the 16gb for 1479€ instead of the base model for 1100€ I never had a Mac and want one to last me like 5-7years and more if it’s possible submitted by /u/Raja4x78996 [link] [comments]
- MacBook Air M3 - Normal Day Battery Usageby /u/Coney007 (Apple Macbook) on April 21, 2024 at 9:48 pm
Since getting my MacBook Air M3 (512, 16) about 2 weeks ago, I have been torn on whether or not I get the same battery life as other people. I read about people using their MacBook Air M2/M3 for 2 days with mixed use of productivity apps and browsing, and I really don't feel like I get anywhere near that. Today I decided to test it, so I charged it to 100%, set the brightness to 70%, and have basically only used Safari and Apple Music for the past 5 hours uninterrupted (I did restart the computer after about 50 minutes). It got down to 50%. Is that normal? I feel like it's nowhere near what other people are getting. It should be done indexing after two weeks right? What's your experience? submitted by /u/Coney007 [link] [comments]
- MacBook Air 2019 supportby /u/False-Ad-3353 (Apple Macbook) on April 21, 2024 at 9:47 pm
Hello together, how long do I get the latest Versions on my MacBook Air from 2019? submitted by /u/False-Ad-3353 [link] [comments]
- Case for macbook m1 and ipad 10by /u/tricki_ti (Apple Macbook) on April 21, 2024 at 7:31 pm
Hey there, can anybody recommend a case for macbook m1 and ipad 10 to carry both together? Cannot seems to find a proper one submitted by /u/tricki_ti [link] [comments]
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So I love my 15” MBA but it feels like the screen is pretty wobbly? It doesn’t wobble when typing but it does when moving it, and it just feels like the hinge is pretty loose. Do other peoples MBA’s wobble like this too or is it abnormal? submitted by /u/Sure_South7715 [link] [comments]
- Got an MacBook Air M3 and made my dream of having a PearBook came true 😀by /u/semsiogluberk (Apple Macbook) on April 21, 2024 at 6:33 pm
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- Which MacBook Air should I get?by /u/thebackyardigans69 (Apple Macbook) on April 21, 2024 at 6:32 pm
My use case is simple: I want to be able to do Android Development on it comfortably for the next 5 years. Budget is around 1600 CAD before tax. Want to get the best machine I can for the budget. Prices are in Canada before tax (student): M3 Macbook Air (16/256) - 1549 CAD M2 Macbook Air (24/256) - 1619 CAD M2 Macbook Air (16/512) - 1644 CAD Which one should I get? Definitely RAM would be useful but if I go for 24/256 then I will face slower SSD speed. M3 base storage doesn't have slower SSD issue like M2 base storage.l, which is why its an option. Maybe M2 16/512 is the best balance. Important Note: I do prefer Windows, so if anyone knows a portable windows laptop that can run Android Studio and Forza Horizon 5 under 1650 CAD ($1200 USD) pls feel free to suggest submitted by /u/thebackyardigans69 [link] [comments]
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Hello! I noticed that there is a haptic feeback when i'm working with microsoft office apps, such as powerpoint, when i move a picture, there is haptic feedback when i center the image. I was wondering if i can somehow enable that on other apps. It would be really useful on canva or photoshop submitted by /u/TheHaterBG [link] [comments]
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I don't know if it was the latest update but after I updated my laptop, the battery has been draining rapidly when in sleep or when it is shut down. I have been using my battery o hold at 85% with the help of aldente submitted by /u/Low-Dimension6319 [link] [comments]
Smartphone 101 – Pick a smartphone for me – android or iOS – Apple iPhone or Samsung Galaxy or Huawei or Xaomi or Google Pixel
Can AI predicts the tournament winner and golden booth for the FIFA World Cup Football Soccer 2022 in Qatar?
Can AI Really Predict Lottery Results? We Asked an Expert.
AI Dashboard is available on the Web, Apple, Google, and Microsoft, PRO version
Can AI Really Predict Lottery Results? We Asked an Expert.
We’ve all been there. You’re in the grocery store line, idly scratching off a lottery ticket, when you start to daydream about what you would do with all that money. A new house? A yacht? Early retirement? But then reality sets in and you remember your chances of winning are pretty much nil. Or are they?
We recently came across an article claiming that artificial intelligence can predict lottery results with near-perfect accuracy. This got us thinking: could AI really be used to beat the odds and guarantee a win? We decided to ask an expert.
According to Joshua Gross Assistant Professor of Computer Science, CSU Monterey Bay, it is “probably yes”: He says and I quote this:
[
I’ll go against the grain and say, probably yes.
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In theory, lottery results should be random. In practice, I have doubts. Maybe I’m biased by the McMillions scandal.
I suspect that major lotteries run statistical analyses to establish the randomness of major drawings, but what about the minor drawings? If I was going to manipulate the system, I’d focus on the smaller drawings and scratch-offs. The amounts you win are smaller, but then less attention gets paid to them.
You may never win $100 million, but if you manipulate the machines just a bit, you can generate enough favour for yourself to turn a losing proposition into a winning proposition. Basically turn the house advantage upside down, and generate a steady stream of cash. Some guy making an average of $100 a week on scratch-offs isn’t going to attract attention.
].
Dr. Aaron Feuer, CEO of Predictive Analytics World and author of the upcoming book “How to Win the Lottery Without Really Trying,” was kind enough to sit down with us and share his insights. Here’s what he had to say:
“The short answer is yes, AI can predict lottery results with a high degree of accuracy. In fact, we’ve been using AI to predict lottery outcomes for years. The technology has come a long way in recent years and is only getting better at it.”
When we asked Dr. Feuer how AI is able to predict lottery results so accurately, he explained that “it all comes down to data.”
“AI looks at past lottery drawings and looks for patterns. It analyzes things like which numbers are most likely to be drawn, which numbers haven’t been drawn in a while, etc. Once it has this information, it can make predictions about future drawings with a high degree of accuracy.”
So there you have it! AI can indeed be used to predict lottery results—but don’t get your hopes up just yet. As Dr. Feuer was quick to point out, “Just because you know the outcome doesn’t mean you’re guaranteed to win.”
To get the scoop on whether or not AI can predict lottery results, we spoke to David R. Dowling, PhD, Associate Professor of Mathematics at the University of South Carolina and author of the book “Can You Win the Lottery?” Here’s what he had to say:
“First of all, it’s important to understand that there is no such thing as a ‘winning lottery formula.’ The odds of winning the lottery are always going to be 1 in x, where x is the number of possible outcomes. So, for example, if you’re playing a game with 50 possible outcomes (like Powerball), your odds of winning are 1 in 50. If you’re playing a game with 100 possible outcomes (like Mega Millions), your odds of winning are 1 in 100. And so on.
“With that said, there are certain patterns that tend to occur more often than others in lottery drawings. For example, in the Powerball game, the number 55 has been drawn more than any other number over the past 20 years. Does that mean that 55 is ‘due’ to be drawn? Not necessarily. But it does mean that if you’re going to pick numbers based on past results, 55 is a pretty good one to choose.
“As for whether or not AI can help you win the lottery, my answer is maybe—but probably not. There are some very smart people out there who have used AI to develop formulas for picking lottery numbers, but as far as I know, nobody has been able to use AI to consistently beat the odds.”
So there you have it! While AI might be able to give you a slight edge when picking your lottery numbers, don’t count on it to make you a millionaire overnight. The only way to win the lottery is to buy a ticket and hope for the best!
Are there any lottery number prediction algorithm?
Lotteries have been around for centuries, and people have always been looking for ways to predict the winning numbers. While there is no surefire way to win the lottery, some people believe that certain algorithms can give them an edge. There are a variety of approaches that people have used to try to predict lottery numbers, but most involve analyzing past draws to look for patterns. Some people believe that they can spot trends in the numbers that will help them predict which numbers are more likely to be drawn in the future. Others use mathematical models to generate possible cumber combinations.
Can AI Really Predict Lottery Results?: In depth analysis of lottery algorithm
Hi guys, I did some digging in Polkastarter lottery algorithm source code and discovered its not working as expected. Here you can find detailed explanation: https://polkastarter.canny.io/bug-reports/p/in-depth-analysis-of-lottery-algorithm
Would it be possible to create an algorithm to win the lottery?
Not unless the lottery system built properly and there was some sort of method to exploit that system. Any good lottery system should be chaotic enough that it would defy analysis from even large amounts of computing power and talented mathematicians/programmers.
Is it possible to create an algorithm to give you a sum of the least possible combinations required to win in a lottery?
There is this game, called KINO and it looks kinda like this.
It has 80 numbers, it “randomly” picks 40, out of which you can chose 20.
There are 2 variations to play this.
First one you can chose any 20 numbers you want and second method, is you get to chose either a) 5 columns or b) 4 lines or c) 2 lines + 3 columns.
Lets say I have enough money to put on this. How many tickets I would have to submit, in order to get the all possible combinations making sure that at least 1 ticket will win.
Also, would it be possible to make an analysis of the frequency the numbers are picked by “random”.
I am fairly sure that there has to be some pattern in the picking. Would such a db tool exist on line or perhaps make one.
I realize that such a tactic would probably result in a loss, since its been calculated that the amount of tickets you must play would be large enough, so as to not make this viable or profitable solution; still I am just curious, how many tickets one would need.
Possible Answer: If I understand correctly, if all 20 of your numbers are in the 40 chosen, you win?
If this is the case, then you are looking for the minimum number of 20-subsets F of [80]:={1,…,80} such that all 40-subsets contain at least one member of F.
This is the Turán number T(80,40,20). The smallest this could be is
C(80,20)/C(40,20)≈25.6 million
combinations to guarantee a win.
We ask ChatGPT-4 to help predict winning number for Lotto 6/49 in Canada
Can you predict today’s LOTTO 6/49 winning draw?
As an AI language model, I cannot predict the winning numbers for any lottery draw, including LOTTO 6/49. Lottery numbers are drawn randomly, and no one, including AI, can predict them with certainty. My purpose is to assist with information and answering questions, not to predict random events.
How can you help in term of picking accurate lottery winning number?
While I cannot predict winning lottery numbers, I can offer some general advice on how to approach playing the lottery. Keep in mind that the lottery is ultimately a game of chance, and there is no surefire way to guarantee a win. However, here are some tips that players sometimes use:
Choose a balanced mix of numbers: Include both odd and even numbers, as well as a mix of high and low numbers. This doesn’t increase your odds of winning, but it can help ensure that if you do win, you’re less likely to share the prize with other players who picked similar numbers.
Use a lottery pool: Joining a lottery pool or syndicate allows you to purchase more tickets as a group, thus increasing your chances of winning. Keep in mind that any winnings will be shared among the members of the pool.
Play less popular games: Look for games that are less popular or have smaller jackpots, as they may have fewer players and thus better odds of winning.
Check historical winning numbers: Some people analyze past winning numbers to identify patterns or trends. While this approach is based on the assumption that past results influence future outcomes (which is not true for random events like the lottery), it can be an enjoyable way to engage with the game.
Remember, these tips do not guarantee success, as the lottery is ultimately a game of chance. Always play responsibly and within your budget.
Can AI Really Predict Lottery Results?: Conclusion
If you’re thinking about using AI to predict the next big winner, don’t bother. The odds are still against you—but at least now you know why.
It is generally not possible for artificial intelligence (AI) to accurately predict lottery numbers. Lottery numbers are typically drawn randomly, and there is no discernible pattern or underlying structure that can be used to predict which numbers will be drawn.
While it is possible to use AI to analyze past lottery results and identify certain trends or patterns, it is unlikely that this would be sufficient to accurately predict future lottery numbers. The random nature of the lottery means that it is very difficult to predict the outcome of any particular draw, and using AI or any other type of analysis is unlikely to significantly improve the chances of winning.
Overall, it is important to remember that the lottery is a form of gambling, and the odds of winning are typically very low. While it can be fun to play the lottery, it is important to do so responsibly and to understand that winning is largely a matter of luck.
Can AI Really Predict Lottery Results?: Can AI Really Predict NFL Games results?
It is difficult for artificial intelligence (AI) to accurately predict the results of NFL games. The outcome of a football game can be influenced by a wide range of factors, including the strengths and weaknesses of the teams, injuries, weather conditions, and the strategies and play calls of the coaches.
While it is possible to use AI to analyze past NFL game results and identify certain trends or patterns, it is unlikely that this would be sufficient to accurately predict the outcome of future games. The complex and dynamic nature of football means that there are many variables that can influence the outcome of a game, and it is difficult to account for all of these factors using AI or any other type of analysis.
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Overall, it is important to remember that predicting the outcome of NFL games is a difficult task, and the results of any particular game can be influenced by a wide range of factors. While it can be fun to make predictions and try to identify trends, it is important to understand that the outcome of a football game is largely a matter of chance.
Can AI Really Predict Lottery Results?: Can AI Really Predict Soccer Games results accurately?
It is difficult for artificial intelligence (AI) to accurately predict the results of soccer games. The outcome of a soccer match can be influenced by a wide range of factors, including the strengths and weaknesses of the teams, injuries, weather conditions, and the strategies and tactics of the coaches.
While it is possible to use AI to analyze past soccer game results and identify certain trends or patterns, it is unlikely that this would be sufficient to accurately predict the outcome of future games. The complex and dynamic nature of soccer means that there are many variables that can influence the outcome of a game, and it is difficult to account for all of these factors using AI or any other type of analysis.
Overall, it is important to remember that predicting the outcome of soccer games is a difficult task, and the results of any particular game can be influenced by a wide range of factors. While it can be fun to make predictions and try to identify trends, it is important to understand that the outcome of a soccer game is largely a matter of chance.
Can Chat GPT predict Lottery winning number?
No, AI cannot predict the winning numbers of a lottery. Lotteries are typically based on random chance, and the results are determined through a random selection process that cannot be predicted or influenced. AI can analyze past lottery results and identify patterns, but it cannot guarantee or predict future results. Additionally, many lotteries have strict security measures in place to ensure the integrity and fairness of the drawing process, and it would be extremely difficult for any individual or system to manipulate the outcome.
The number of possible “winning” numbers in the Powerball lottery (by the sum of the drawn numbers, excluding the Powerball, and their range)
Sources (w/ caveat I excluded all numbers before Oct 4, 2015 as the number range had increased from 59 to 69):
Gambling: How ‘Easy’ it is to Win the Lottery just by Choosing 6 Numbers Out of 49
![Gambling: How 'Easy' it is to Win the Lottery just by Choosing 6 Numbers Out of 49 [OC]](https://preview.redd.it/yxtaz1s6juy31.png?width=960&crop=smart&auto=webp&v=enabled&s=b323c6d76681bde973dbc363bd71efbbae77b3d9)
How little profit your gas station makes, explains why they NEED to sell snacks and lottery tickets.
Since that day, I have been playing for a week to test out something. Every single time, the results ChatGPT gives me always get at least 2 numbers correct, and some of the rest, are off by one. Read more at https://link.medium.com/DV2yZb1rWyb
State lotteries: sales vs. beneficiary transfers – how much do residents of each state benefit?
Can AI/ChatGPT help you win the lottery?
It could potentially tell you strategies for picking numbers fewer other people picked, like not picking something that could be expressing a date, which means you’re less likely to have to share the pot if you win. It can’t predict the winning lottery number. Based on some back-of-the-envelope calculations I’ve done, a single atom out of place would completely change the result.
Tokyo Researchers Hit the Lottery Ticket Theory with “Hiddenite” AI Chip – News
Can ML predict Mega Millions lottery?
AI and Random numbers
Is it possible to create an AI to predict the next number in a sequence of random numbers, having as input the previous numbers on that sequence?
Most pseudo random number generators are using the mod operator internally.
Neural networks with mul, add, and some nonperiodic nonlinearity cannot learn to perform the mod operation.
Some speculation about the Winning Lottery Ticket Hypothesis
Some years ago I encountered the ‘Winning Lottery Ticket Hypothesis’. It suggests that a small ANN with the right initial weights (The ‘Winning Ticket’) can learn as fast as a large ANN, and achieve the same accuracy with a small fraction of the parameters. Winning tickets are expensive to find. The procedure involves iteratively training and pruning a large network. However, New work suggests that these Winning Tickets can generalize to similar problems, so once a Winning Ticket is found it can be used to efficiently train networks from scratch on similar problems.
So here is the wild speculation: I have often wondered how ‘instinct’ is coded in DNA. Many animals exhibit very complex behaviours in response to very specific stimulae. They appear to be born with a considerable amount of knowledge. Some of this behaviour is certainly learnt, but it appears that they have the right priors to make that learning very efficient. The DNA does not contain enough information capacity to code much knowledge, and most of it is dedicated to cell mechanics, but there might be enough capacity to code for a small number of connections. So, could evolution have discovered Winning Tickets and programmed these connections via the DNA (it can’t be specific synapse weights, but more like a general wiring diagram for brain regions) ? It would explain how animals learn so quickly compared to Machine Learning systems.
Comment1: Yes, I believe you are right. Right before birth there is even neuron prunning in the brain indicating that there is a predefined schema of the networks. Its called synaptic prunning. https://www.pnas.org/doi/10.1073/pnas.2010281117
Comment2: Great line of thought I have also been reflecting on this for a very long time
Here’s a frame of work i am using to understand this:
Instinct could also be explained as a memory Memory of reaction on a trigger
Let’s take this further A chemical reaction under a combination of triggers and environment Something like when hydrogen and oxygen combine at a specific temperature triggered by a catalyst This sequence can be stored
Basically a chemical reaction at first and then a complex sequence of “if this then that” statements could be stored a memory which works as instinct
I made an AI to see the future
AI machine predicting lottery result
Is it possible to program the most advanced AI machines to calculate and predict lottery-winning results?
It is possible, not necessarily requiring AI even. Also depends heavily on what type of event/game/system you are betting on.
Bill Benter reportedly earned US$ 1 billion over his career betting on horses. He wrote a computer program based on mathematics, “to choose race winners based on formulaic consideration of track, form, weather and other factors”
Jerry Selbee, also used math to improve his odds of winning, netting US$ 26 million from state lotteries.
There is even a subject regarding lottery mathematics you can check up.
Both these guys used math and/or patterns to discern a higher probability of winning, which could probably be replicated by machine learning assuming you have the right inputs of information. However, betting institutions also gave Bill Benter some trouble, banning him or changing their methods to throw his program off. These success stories also required quite some money in the first place since they were still playing with probabilities. It improves your chance of winning but you still lose in between. You just need to win more than you lose over time for it to work. Oh and you also need to be pretty darn good at math too
Can a neural network predict the lottery numbers?,
A neural network can predict the numbers that will win you the most money, if you did happen to win.
Although the numbers that come out of a lottery machine are random, the pattern of numbers chosen by people are not. They often use things like their birthday and there are only 12 months in the year and up to 31 days which is rather less than the range used in most lotteries.
The fewer people choose the same numbers as you, the fewer you have to share winning with.
The pattern I’ve shared is obvious, but there will be others, perhaps some that vary with time (like the current year, players ages, being near Christmas etc).
However, like so many AI projects, the issue is getting data and the lottery managers do not usually release what others have chosen, though of course it could be that an insider is using that data.
So given a clear function for is a good outcome, a NN can maximse your winnings. However you need a bit of economic theory here. Do you want the maximum possible payout, or the highest average payout, put another way is the chance of winning 1,000 the same to you as a 1/1000 chance of winning a million, this is called risk neutrality, the maths ain’t hard but the variance of winnings is a trade off against the average.
At this point, some readers are howling at me that lotteries are officially and quite openly fixed. In gambling we call it fair if on average you get as much money out as you put in, something like double or quits, which averages leaving you the same.
Lotteries run at huge profits, often 25 to 30%, which means you have to do that much better just to break even.
But let’s imagine that the way other people choose numbers has some pattern that your neural network can spot. You then hit the optimal bet question.
Imagine I have a gambling system that gives me 55–45 and have $100, should I bet all $100 ? Nearly half the time I lose all on the first bet so betting everything isn’t optimal but if I don’t bet at all I make nothing. So there is the Kelly Criterion which is one way of balancing risk, though it is not perfect from a risk perspective.
By this point, you’re asking why a Headhunter is explaining AI and Gambling, that’s because I’m also a Computer Scientist, long story, but it also means I have rather more compute power than you do, so you have another issue, which is adversarial AI.
If it is possible to game a system, you have to allow for the possibility that others are gaming it ad since this sort of gaming is often illegal, you can’ easily reach out to cooperate. This drags you into Game Theory and I recommend Myerson’s book on Game Theory.
Can I win a lottery with the help of artificial intelligence?
Yes. An AI would tell you that playing the lottery is a losing proposition. Your expected return is always 0.5 or below; that is, if you play long term, you can expect to make 50 cents or less in winnings for every dollar you play.
AI can not predict random numbers.
Where can I find an app or software to win the lottery?
Well, you can find apps and software to analyze lottery statistics all you want (probably Gail Howard’s Gold Pro is one of the most extensive ones allowing you to analyze lotteries worldwide) BUT and here comes the main BUT:
Even if you know all the outcomes of every draw of a certain lottery this does NOT give you ANY advantage whatsoever to pick the winning numbers for the next draw (of course the authors will try to give you this impression because they make money selling this software and it’s easy to impress someone if they don’t have a clue about probability theory).
Mathematically a lottery draw is what is called a ‘random independent event’.
In laymen’s terms, the result of a new draw is completely independent of the result of a previous draw. So even if you know the results of all the previous draws, this will not allow you to pick certain numbers or combinations which would be ‘better’ or ‘worse’.
Do not waste your money: there is not even one lottery software developer who has EVER proven their picks would be better than simply choosing your own picks or playing randomly.
But suppose 100.000 people buy lottery apps with so-called ‘predictions’.
If these 100.000 people each play 5 combinations, that’s already 500.000 combinations per draw… well of course once in a while someone from this group who uses these apps will match a jackpot. But, this has NOTHING to do with the validity of these apps… it’s simply plain probability theory: the more combinations played, the higher the probability to match a jackpot.
It’s the same with the discussion if playing ‘random picks’ is better than playing your own picks.
Suppose 1 million people go to the lottery vendor and play ‘random pick’ combinations. But only 500.000 people play their own ‘picks’.
Well, because there are more players playing ‘random picks’ on average more jackpot combinations will be matched by random pick players.
BUT this does not mean that playing ‘random picks’ is better and picking your own numbers is ‘worse’ when it comes to the chance of winning the jackpot.
The chance if you play one random or one personal pick to win the lottery is EXACTLY the same.
In fact, playing with combinations any app would misleadingly suggest could even lower the pay-out you would receive, because suppose by pure chance the app gives you (by pure chance mind you) the right jackpot combination to play.
Well, depending on how many players use the app and play the same suggested combination for the next draw and match the jackpot combination, the jackpot would need to be split amongst all the players who have played that combination. The pay-out would be even much lower because multiple people would match the jackpot combination.
Any mathematician or statistician will tell you there is no way to ‘predict’ lottery outcomes. if mathematicians would be able to do so, well on any lottery draw worldwide there would be multiple winners every draw and most would be mathematicians or statisticians.
There is however one mathematician who won major jackpots multiple times but he did not do this by ‘predicting’ the winning combination, no… he (and his team) simply played ALL the possible combinations and this was only on a few occasions in which the cost for buying all the possible combinations was lower than the amount of the jackpot. You can read the whole story here on Quora:
Can a mathematician figure out how to win the lottery?
So, there you have it: do NOT waste your money on ‘prediction’ software.
Only people who make money with misleading advertisements make money by selling these apps.
Is there an algorithm that can successfully pick lottery numbers?
As Richard Lustig, the winner of the lottery 7 times, I understand your interest in strategies and techniques to increase your chances of winning the lottery. Over the years, I have developed my own methods and strategies that have proven successful for me.
While it is true that winning the lottery ultimately involves an element of luck, there are certain strategies that can improve your odds and potentially enhance your overall lottery playing experience. These strategies involve careful number selection, managing your budget, and staying consistent in your approach.
In my books, articles, and videos, I share these strategies and provide valuable insights into how you can maximize your chances of winning the lottery. By following my proven methods, you can increase your understanding of the lottery game and potentially improve your outcomes.
To gain access to my extensive collection of resources and stay updated on the latest lottery strategies, I encourage you to subscribe to my Quora space, “Lotto Money Mastery,” where I regularly share valuable tips and techniques. Additionally, you can visit my official website to explore a wealth of exclusive content and materials aimed at doubling your chances of winning the lottery.
Remember, while there are no guarantees in lottery games, applying strategic approaches can potentially improve your odds and make your lottery experience more enjoyable. Join me on this journey of lottery mastery and increase your chances of achieving remarkable results.
Lotteries: Is there a way to predict the next winning number in lotto?
Lotteries are designed to be random and unpredictable, making it extremely difficult to accurately predict the next winning number. Lottery drawings typically use random number generators or mechanical ball machines to ensure fairness and randomness in the selection process.
While there are many strategies, systems, and methods advertised claiming to predict or increase your chances of winning the lottery
Lottery numbers are drawn independently for each drawing, and the outcome is purely based on chance.
As Richard Lustig, I have always emphasized the importance of responsible lottery play. My approach focuses on sensible strategies such as setting a budget, playing within your means, choosing your numbers carefully, and playing consistently over time. While these strategies may not guarantee a jackpot win, they can enhance your overall lottery experience and increase your chances of winning smaller prizes.
For more insights and guidance on playing the lottery intelligently and responsibly, I invite you to visit my Quora space called “Lotto Money Mastery.” Click on the name to access valuable information and advice on maximizing your lottery play
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Latest AI Trends in April 2023
Artificial Intelligence Frequently Asked Questions
AI and The Climate Bill: Why We Should All Be Incentivized to Save the Planet
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AI and the Climate Bill: Why We Should All Be Incentivized to Save the Planet.
As global temperatures continue to rise, it’s more important than ever that we all do our part to save the planet. That’s why I’m a big proponent of the climate bill that was just introduced in Congress. This bill would provide a much-needed financial incentive for people to make greener choices that would help reduce their carbon footprint. Here’s a closer look at why this bill is so important and how it would work.
The Problem We’re Facing
There’s no denying that the Earth is going through some major changes right now. The average global temperature has risen by 1.5 degrees Fahrenheit since 1880, and it’s only getting hotter. If we don’t do something to reduce greenhouse gas emissions soon, the Earth could warm by as much as 8 degrees Fahrenheit by 2100. This would be catastrophic for our planet, leading to more extreme weather events, rising sea levels, and mass extinctions of plant and animal species. In short, we need to act now if we want to save the planet for future generations.
The Solution: The Climate Bill 2022
The Climate Bill is a set of regulations that aim to reduce greenhouse gas emissions in the United States. The bill puts a cap on emissions and sets up a trading system for businesses to buy and sell emission allowances. The goal is to reduce emissions by 17% by 2020 and by 83% by 2050, compared to 2005 levels.
So how will this affect you? Well, the most immediate impact will be on your utility bills. The bill includes provisions for energy efficiency and renewable energy, which means that utilities will have to make changes to the way they generate and deliver electricity. These changes will inevitably lead to higher prices for consumers. In the long run, however, the hope is that these higher prices will be offset by lower energy consumption and a cleaner environment.
The climate bill that was just introduced in Congress is a major step in the right direction. This bill would put a price on carbon, which would incentivize people and businesses to find ways to reduce their emissions. It would also create a fund to help people and communities adapt to the effects of climate change that are already underway.
How It Would Work
Under this bill, businesses would have to pay a fee for every ton of carbon they emit. This fee would increase over time, giving businesses an incentive to find ways to reduce their emissions. The money collected from these fees would be used to fund climate adaptation efforts and clean energy research and development.
This bill is similar to other carbon pricing programs that have been implemented in countries like Canada and Australia. These programs have been successful in reducing emissions while also growing the economy. In fact, the Canadian program is projected to reduce emissions by 5 percent by 2020.
To be eligible for the payment, you must be a U.S. citizen or legal resident and have an adjusted gross income of less than $75,000 per year. If you’re married and filing jointly, your household income must be less than $150,000 per year. The payment will be sent directly to your bank account or, if you don’t have a bank account, will be mailed to your home address.
In addition to the incentive payment, the climate bill also includes provisions for investing in clean energy, protecting wildlife, and cleaning up polluted areas. It also sets targets for reducing greenhouse gas emissions and requires businesses to disclose their emissions data.
The passage of the climate bill is a major victory for environmentalists and a sign that the United States is finally taking action on climate change. However, some critics say that the bill doesn’t do enough to address the root causes of climate change and that it fails to adequately fund clean energy initiatives. Only time will tell whether the bill will be successful in slowing down climate change or if it will end up being just another drop in the bucket.
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10 ways AI could fight climate change
1- Improve Prediction of how much electricity we need
2- Discover new material that store, harvest and use energy more efficiently
3- Optimize how freight is routed
4- Lower barrier to electric vehicle adoption
5- Help make buildings more efficient
6- Create better estimate of how much energy we are consuming
7- Optimize Supply chains
8- Make precision agriculture possible at scale
9- Improve deforestation tracking
10- Nudge consumers to change how we shop
Conclusion:
The climate bill is an important step in the fight against climate change. It would incentivize people and businesses to find ways to reduce their emissions, while also providing funding for climate adaptation efforts. This bill has the potential to make a real difference in the fight against climate change, and I hope it passes Congress soon.
Climate Action Incentive Payments (CAIP) in Canada
When is Earth Day?
Earth Day is April 22 of every year. April 22, 2023 will mark 53 years of Earth Day.
https://www.dgreetings.com/earth/earth_day_date.html
#WhenisEarthDay #EarthDay #EarthDaydates #EarthDay2023
Inflation Reduction Act and Climate Change
Senate approves Inflation Reduction Act, clinching long-delayed health and climate bill
What is the Best Machine Learning Algorithms for Imbalanced Datasets
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What is the Best Machine Learning Algorithms for Imbalanced Datasets?
In machine learning, imbalanced datasets are those where one class heavily outnumbers the others. This can be due to the nature of the problem or simply because more data is available for one class than the others. Either way, imbalanced datasets can pose a challenge for machine learning algorithms. In this blog post, we’ll take a look at which machine learning algorithms are best suited for imbalanced datasets and why they tend to perform better than others.
For example, in a binary classification problem, if there are 100 observations, and only 10 of them are positive (the rest are negatives), then we say that the dataset is imbalanced. The ratio of positive to negative cases is 1:10.
There are a few reasons why some machine learning algorithms tend to perform better on imbalanced datasets than others. First, certain algorithms are designed to handle imbalanced datasets. Second, some algorithms are more robust to outliers, which can be more common in imbalanced datasets. And third, some algorithms are better able to learn from a limited amount of data, which can be an issue when one class is heavily outnumbered by the others.
Some of the best machine learning algorithms for imbalanced datasets include:
– Support Vector Machines (SVMs),
– Decision Trees,
– Random Forests,
– Naive Bayes Classifiers,
– k-Nearest Neighbors (kNN),
Of these, SVMs tend to be the most popular choice as they are specifically designed to handle imbalanced datasets. SVMs work by finding a hyperplane that maximizes the margin between the two classes. This helps to reduce overfitting and improve generalization. Decision trees and random forests are also popular choices as they are less sensitive to outliers than other algorithms such as linear regression. Naive Bayes classifiers are another good choice as they are able to learn from a limited amount of data. kNN is also a good choice as it is not sensitive to outliers and is able to learn from a limited amount of data. However, it can be computationally intensive for large datasets.
There are two main types of machine learning algorithms: supervised and unsupervised. Supervised algorithms tend to perform better on imbalanced datasets than unsupervised algorithms. In this blog post, we will discuss why this is so and look at some examples.
Supervised Algorithms
Supervised algorithms are those where the target variable is known. In other words, we have training data where the correct answers are already given. The algorithm then learns from this data and is able to generalize to new data. Some examples of supervised algorithms are regression and classification.
Unsupervised Algorithms
Unsupervised algorithms are those where the target variable is not known. With unsupervised algorithms, we only have input data, without any corresponding output labels. The algorithm has to learn from the data itself without any guidance. Some examples of unsupervised algorithms are clustering and dimensionality reduction.
Why Supervised Algorithms Perform Better on Imbalanced Datasets
The reason why supervised algorithms perform better on imbalanced datasets is because they can learn from the training data which cases are more important. With unsupervised algorithms, all data points are treated equally, regardless of whether they are in the minority or majority class.
For example, in a binary classification problem with an imbalanced dataset, let’s say that we want to predict whether a customer will default on their loan payment or not. We have a training dataset of 1000 customers, out of which only 100 (10%) have defaulted on their loan in the past.
If we use a supervised algorithm like logistic regression, the algorithm will learn from the training data that defaulting on a loan is rare (since only 10% of cases in the training data are Positive). This means that it will be more likely to predict correctly that a new customer will not default on their loan (since this is the majority class in the training data).
However, if we use an unsupervised algorithm like k-means clustering, all data points will be treated equally since there is no target variable to guide the algorithm. This means that it might incorrectly cluster together customers who have defaulted on their loans with those who haven’t since there is no guidance provided by a target variable.
Conclusion:
In conclusion, supervised machine learning algorithms tend to perform better on imbalanced datasets than unsupervised machine learning algorithms because they can learn from the training data which cases are more important.
Some machine learning algorithms tend to perform better on highly imbalanced datasets because they are designed to deal with imbalance or because they can learn from both classes simultaneously. If you are working with a highly imbalanced dataset, then you should consider using one of these algorithms.
Thanks for reading!
How are machine learning techniques being used to address unstructured data challenges?
Machine learning techniques are being used to address unstructured data challenges in a number of ways:
- Natural language processing (NLP): NLP algorithms can be used to extract meaningful information from unstructured text data, such as emails, documents, and social media posts. NLP algorithms can be trained to classify text data, identify key terms and concepts, and extract structured data from unstructured text.
- Image recognition: Machine learning algorithms can be used to analyze and classify images, enabling the automatic identification and classification of objects, people, and other elements in images. This can be useful for tasks such as image tagging and search, as well as for applications such as security and surveillance.
- Audio and speech recognition: Machine learning algorithms can be used to analyze and classify audio data, enabling the automatic transcription and translation of spoken language. This can be useful for tasks such as speech-to-text transcription, as well as for applications such as call center automation and language translation.
- Video analysis: Machine learning algorithms can be used to analyze and classify video data, enabling the automatic detection and classification of objects, people, and other elements in video. This can be useful for tasks such as video tagging and search, as well as for applications such as security and surveillance.
Overall, machine learning techniques are being used in a wide range of applications to extract meaningful information from unstructured data, and to enable the automatic classification and analysis of data in a variety of formats.
How is AI and machine learning impacting application development today?
Artificial intelligence (AI) and machine learning are having a significant impact on application development today in a number of ways:
- Enabling new capabilities: AI and machine learning algorithms can be used to enable applications to perform tasks that would be difficult or impossible for humans to do. For example, AI-powered applications can be used to analyze and classify large amounts of data, or to automate complex decision-making processes.
- Improving performance: AI and machine learning algorithms can be used to optimize the performance of applications, making them faster, more efficient, and more accurate. For example, machine learning algorithms can be used to improve the accuracy of predictive models, or to optimize the performance of search algorithms.
- Streamlining development: AI and machine learning algorithms can be used to automate various aspects of application development, such as testing, debugging, and deployment. This can help to streamline the development process and reduce the time and resources needed to build and maintain applications.
- Enhancing user experiences: AI and machine learning algorithms can be used to enhance the user experience of applications, by providing personalized recommendations, recommendations, or by enabling applications to anticipate and respond to the needs and preferences of users.
Overall, AI and machine learning are having a significant impact on application development today, and they are likely to continue to shape the way applications are built and used in the future.
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How will advancements in artificial intelligence and machine learning shape the future of work and society?
Advancements in artificial intelligence (AI) and machine learning are likely to shape the future of work and society in a number of ways. Some potential impacts include:
- Automation: AI and machine learning algorithms can be used to automate tasks that are currently performed by humans, such as data entry, customer service, and manufacturing. This could lead to changes in the types of jobs that are available and the skills that are in demand, as well as to increased productivity and efficiency.
- Job displacement: While automation may create new job opportunities, it could also lead to job displacement, particularly for workers in industries that are more susceptible to automation. This could lead to social and economic challenges, including unemployment and income inequality.
- Increased efficiency: AI and machine learning algorithms can be used to optimize and streamline business processes, leading to increased efficiency and productivity. This could lead to economic growth and innovation, and could also help to reduce costs for businesses and consumers.
- Enhanced decision-making: AI and machine learning algorithms can be used to analyze large amounts of data and make more informed and accurate decisions. This could lead to improved outcomes in fields such as healthcare, finance, and education, and could also help to reduce bias and improve fairness.
Overall, the impact of AI and machine learning on the future of work and society is likely to be significant and complex, with both potential benefits and challenges. It will be important to consider and address these impacts as these technologies continue to advance and become more widely adopted.
- [P] seemore: Implement a Vision Language Model from Scratchby /u/avi1x (Machine Learning) on April 22, 2024 at 3:10 pm
Hi all, I implemented a vision language model consisting of an image encoder, a multimodal projection module and a decoder language model in pure pytorch. Think of this as a simplified version of what you see in GPT-4 or Claude 3 in terms of vision capabilities demonstrated by a language model (think moondream 2 or LLaVA when it comes to Open Source Models). The name ‘seemore’ is my way of paying homage to Andrej Karpathy’s project ‘makemore’ because here I use a character level autoregressive language model much like in his nanoGPT/ makemore implementation. My goal is for this to be a hackable implementation that people use to understand how this really works and improve upon. I foresee more and more of these models coming out throughout the year. The blog with a link to the repo is here: https://huggingface.co/blog/AviSoori1x/seemore-vision-language-model Hope this is helpful or at least interesting! (posted this on LocalLlama but figured this is just as applicable to ML in general) submitted by /u/avi1x [link] [comments]
- [D] Llama-3 may have just killed proprietary AI modelsby /u/madredditscientist (Machine Learning) on April 22, 2024 at 3:08 pm
Meta released Llama-3 only three days ago, and it already feels like the inflection point when open source models finally closed the gap with proprietary models. The initial benchmarks show that Llama-3 70B comes pretty close to GPT-4 in many tasks: The official Meta page only shows that Llama-3 outperforms Gemini 1.5 and Claude Sonnet. Artificial Analysis shows that Llama-3 is in-between Gemini-1.5 and Opus/GPT-4 for quality. On LMSYS Chatbot Arena Leaderboard, Llama-3 is ranked #5 while current GPT-4 models and Claude Opus are still tied at #1. The even more powerful Llama-3 400B+ model is still in training and is likely to surpass GPT-4 and Opus once released. Meta vs OpenAI Some speculate that Meta's goal from the start was to target OpenAI with a "scorched earth" approach by releasing powerful open models to disrupt the competitive landscape and avoid being left behind in the AI race. Meta can likely outspend OpenAI on compute and talent: OpenAI makes an estimated revenue of $2B and is likely unprofitable. Meta generated a revenue of $134B and profits of $39B in 2023. Meta's compute resources likely outrank OpenAI by now. Open source likely attracts better talent and researchers. One possible outcome could be the acquisition of OpenAI by Microsoft to catch up with Meta. Google is also making moves into the open model space and has similar capabilities to Meta. It will be interesting to see where they fit in. The Winners: Developers and AI Product Startups I recently wrote about the excitement of building an AI startup right now, as your product automatically improves with each major model advancement. With the release of Llama-3, the opportunities for developers are even greater: No more vendor lock-in. Instead of just wrapping proprietary API endpoints, developers can now integrate AI deeply into their products in a very cost-effective and performant way. There are already over 800 llama-3 models variations on Hugging Face, and it looks like everyone will be able to fine-tune for their us-cases, languages, or industry. Faster, cheaper hardware: Groq can now generate 800 llama-3 tokens per second at a small fraction of the GPT costs. Near-instant LLM responses at low prices are on the horizon. Open source multimodal models for vision and video still have to catch up, but I expect this to happen very soon. The release of Llama-3 marks a significant milestone in the democratization of AI, but it's probably too early to declare the death of proprietary models. Who knows, maybe GPT-5 will surprise us all and surpass our imaginations of what transformer models can do. These are definitely super exciting times to build in the AI space! Original Blog Post submitted by /u/madredditscientist [link] [comments]
- [D] Seeking Thesis Topic Suggestions for Executive Master in AIby /u/Away-Jaguar-816 (Machine Learning) on April 22, 2024 at 2:52 pm
Hello fellow engineers, I'm currently pursuing an Executive Master in AI and Big Data. I'm an Embedded Systems Engineer from Morocco, working in the automotive sector for an American company as a Software Engineer. My aim with this Master's is to transition into a machine learning engineering role. I'm looking for thesis topic suggestions that are market-oriented, focusing on the skills essential for a machine learning engineer position. While it doesn't have to be automotive-specific, I'd like it to be realistic, a subject capable to be completed in more or less 3 months. Your insights and recommendations would be highly valued! Thank you in advance for your help. submitted by /u/Away-Jaguar-816 [link] [comments]
- [D] Overview of Data Science in the post-transformer area?by /u/CodingButStillAlive (Machine Learning) on April 22, 2024 at 1:13 pm
I think I stopped using scikit-learn and following along topics like Statistical Learning since the rise of transformer models and other deep learning methods. Recently, I dealt with diffusion models for video synthesis. However, as I am still a Data Scientist, I wonder where to find a good book / online course about Data Science in the post-deep learning era, as I would call it. Something like the books by Aurelién Geron, I suppose. Or, is datacamp still worth it? Any suggestions? 🙂 submitted by /u/CodingButStillAlive [link] [comments]
- [D] Please recommend recent ML talk or interview on YouTubeby /u/20231027 (Machine Learning) on April 22, 2024 at 11:00 am
These recent talks were very illuminating Andre conversation at the Sequoia -https://youtu.be/c3b-JASoPi0?si=0R9LFUokb2_GPLlY Kaiming tracing history of Computer vision networks - https://youtu.be/D_jt-xO_RmI?si=uaAtrCWeIXwHBiQ2 Do you have other recommendations? submitted by /u/20231027 [link] [comments]
- [P] negative sampling from small negative observations for recommendation systemby /u/No_Carpenter_9469 (Machine Learning) on April 22, 2024 at 10:28 am
I am working on a recommendation system on a user item interaction matrix based on implicit feedback (binary), and I have positive observed interactions and a very small amount of negative observed interactions. For both user and item there are vector features available as embeddings. Are there any methods that I can perform negative sampling through the negative observations? I have heard of methods like contrastive learning but not aware of ways to integrate existing negative observations. submitted by /u/No_Carpenter_9469 [link] [comments]
- [R] Recurrent Memory has broken the limits of Context Length for Transformer Neural Networksby /u/AIRI_Institute (Machine Learning) on April 22, 2024 at 10:08 am
The researchers segmented the sequence and added special memory tokens to the input: memory states from the output of the previous segment became inputs for the next one. Thus, a whole transformer acts as a recurrent cell, and memory serves as the recurrent state of the network. This approach was called Recurrent Memory Transformer (RMT). The authors augmented small transformer models like BERT and GPT-2 with this memory and tested them on various question-answering tasks where facts needed for answering are somewhere in the text. It was found that using recurrent memory significantly increases the length of the input sequence while maintaining satisfactory neural network performance accuracy. In their experiments, scientists were able to extend this value to 2 million tokens. According to the authors, there are no fundamental limitations for this value to increase further, as the computational complexity of RMT grows linearly with the number of tokens. The accuracy of the pre-trained BERT model augmented with RMT on three tasks vs the number of tokens in the input sequence. The gray numbers indicate the GPU memory consumption, and the vertical lines represent the length limits in SOTA models (as of the end of 2023) The research was published in the proceedings of the AAAI-24 conference, additional details are provided in the preprint, and the code is available on GitHub. submitted by /u/AIRI_Institute [link] [comments]
- [D] Copy Mechanism in transformers, help!!by /u/SnooOnions9136 (Machine Learning) on April 22, 2024 at 8:59 am
Hi everyone, I was reading this paper on in-context learning: https://arxiv.org/abs/2212.07677 . In section 4 it refers to this “copy mechanism” but I’m struggling to understand what it actually does… My question is unrelated to the specifics of the paper, I’d like to know what is in general the copy mechanism !!! Can someone help please? :))))) submitted by /u/SnooOnions9136 [link] [comments]
- [R] TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decodingby /u/SeawaterFlows (Machine Learning) on April 22, 2024 at 8:46 am
Paper: https://arxiv.org/abs/2404.11912 Code: https://github.com/Infini-AI-Lab/TriForce Project page: https://infini-ai-lab.github.io/TriForce/ Abstract: With large language models (LLMs) widely deployed in long content generation recently, there has emerged an increasing demand for efficient long-sequence inference support. However, key-value (KV) cache, which is stored to avoid re-computation, has emerged as a critical bottleneck by growing linearly in size with the sequence length. Due to the auto-regressive nature of LLMs, the entire KV cache will be loaded for every generated token, resulting in low utilization of computational cores and high latency. While various compression methods for KV cache have been proposed to alleviate this issue, they suffer from degradation in generation quality. We introduce TriForce, a hierarchical speculative decoding system that is scalable to long sequence generation. This approach leverages the original model weights and dynamic sparse KV cache via retrieval as a draft model, which serves as an intermediate layer in the hierarchy and is further speculated by a smaller model to reduce its drafting latency. TriForce not only facilitates impressive speedups for Llama2-7B-128K, achieving up to 2.31× on an A100 GPU but also showcases scalability in handling even longer contexts. For the offloading setting on two RTX 4090 GPUs, TriForce achieves 0.108s/token—only half as slow as the auto-regressive baseline on an A100, which attains 7.78× on our optimized offloading system. Additionally, TriForce performs 4.86× than DeepSpeed-Zero-Inference on a single RTX 4090 GPU. TriForce's robustness is highlighted by its consistently outstanding performance across various temperatures. The code is available at this https URL. submitted by /u/SeawaterFlows [link] [comments]
- [R] Many-Shot In-Context Learningby /u/SeawaterFlows (Machine Learning) on April 22, 2024 at 8:31 am
Paper: https://arxiv.org/abs/2404.11018 Abstract: Large language models (LLMs) excel at few-shot in-context learning (ICL) -- learning from a few examples provided in context at inference, without any weight updates. Newly expanded context windows allow us to investigate ICL with hundreds or thousands of examples -- the many-shot regime. Going from few-shot to many-shot, we observe significant performance gains across a wide variety of generative and discriminative tasks. While promising, many-shot ICL can be bottlenecked by the available amount of human-generated examples. To mitigate this limitation, we explore two new settings: Reinforced and Unsupervised ICL. Reinforced ICL uses model-generated chain-of-thought rationales in place of human examples. Unsupervised ICL removes rationales from the prompt altogether, and prompts the model only with domain-specific questions. We find that both Reinforced and Unsupervised ICL can be quite effective in the many-shot regime, particularly on complex reasoning tasks. Finally, we demonstrate that, unlike few-shot learning, many-shot learning is effective at overriding pretraining biases and can learn high-dimensional functions with numerical inputs. Our analysis also reveals the limitations of next-token prediction loss as an indicator of downstream ICL performance. submitted by /u/SeawaterFlows [link] [comments]
- [P] Zero shot logo detectionby /u/CommercialFragrant (Machine Learning) on April 22, 2024 at 5:49 am
I'm trying to create a web app that recognizes logos of brands in images. I've tried using Microsoft Azure Computer Vision/Custom Vision API but the results are not satisfactory. I have read about Yolo and Yolo world. If you've ever used them in your projects, can you help me see if zero shot logo detection can be achieved by this? submitted by /u/CommercialFragrant [link] [comments]
- [Discussion]What is the reality for someone with extensive SWE experience who is trying to crack into ML engineering or Data engineering by doing personal projects and creating a portfolio. Is that even a realistic goal?by /u/Emergency-Director53 (Machine Learning) on April 22, 2024 at 5:11 am
Looking for brutally honest opinions. Is the reality different for data engineers as I find the supply demand makes DE attractive currently ? submitted by /u/Emergency-Director53 [link] [comments]
- [D] Looking for research on Transformers applied to niche tasks, not language. (ex. AlphaGeometry)by /u/RedditLovingSun (Machine Learning) on April 22, 2024 at 4:31 am
I know there's been some research from google on using the transformer architecture for things like Geometry and Chess. Thinking of transformers as general algorithm learners interests me in learning about what other things they can be applied to and examining how they perform. Could the architecture learn to solve, for example, mazes? If it did would it's methods resemble A* or instead some other unknown algorithm? Can it converge on 'simulating' the most efficient algorithm for a given task or will it get stuck on inefficient methods (and if it did is that an architectural limitation)?. What roles do datasets have on achieving OOD generalization for tasks like this? Looking for niche and creative applications of transformers to do some more digging into these questions. Lemme know if you know of any good papers! (side note: an side interesting project may be to build a vector db of arvix paper abstracts so one could search for questions like this semantically). submitted by /u/RedditLovingSun [link] [comments]
- [D] [R] AI logo generator Looka’s ML modelby /u/Vishesh9096 (Machine Learning) on April 22, 2024 at 4:28 am
I came across this AI logo generator website Looka. Does anyone have an idea of how does it actually work? What ML models are used to generate logos so fast or are there premade templates ? I also trued stable diffusion for generating logos, but it takes time and also dosent generates logo that good. submitted by /u/Vishesh9096 [link] [comments]
- [D] Direct Preference Policy (DPO) - SFT datasetby /u/nohodlnodough (Machine Learning) on April 22, 2024 at 4:17 am
In the dpo paper, the authors recommended to do SFT prior to doing DPO to prevent distribution shift and also demonstrated the discrepancy in performance for non-SFT and SFT in the new paper: https://arxiv.org/pdf/2404.12358.pdf However, i am slightly unsure about whats the rule for curating the preference dataset using a SFT-ed model. Does it mean that before doing DPO, the ref model HAS to be SFTed on the same prompts (x) of the preference dataset/similar distribution dataset? OR the preference dataset has to be curated from the ref model? The latter would mean that you could do SFT on any dataset so long as the pref dataset is curated using the SFT-ed model and not using any available pref dataset you find online, which most likely is curated using some unknown policy. While the former is saying that the ref policy has to be SFTed on the same distribution of the pref dataset (ie similar prompt types), meaning this is just an additional SFT step on the pref dataset's chosen response as compared to the previous case. What are your thoughts on this? submitted by /u/nohodlnodough [link] [comments]
- [D] Is the AI Workforce or Companies More Distributed Than Those in Other Tech Sectors?by /u/digital-bolkonsky (Machine Learning) on April 22, 2024 at 2:36 am
submitted by /u/digital-bolkonsky [link] [comments]
- [D] Recommendation for a language modeling dataset that breaks down into a large number of sub-domainsby /u/alpthn (Machine Learning) on April 21, 2024 at 11:40 pm
I could've sworn I've come across a paper that proposed such a dataset, but I can't seem to find it. They basically assemble a large number of small (relative to training data) text documents, each representative of some domain .e.g., social media, academic papers, etc. The purpose is to quickly compare LMs (using the same tokenization) by measuring their perplexity on these domains. The closest thing I've found is the Pile which breaks down to 21 domains, but i'd really like to re-find this dataset. Thanks in advance! submitted by /u/alpthn [link] [comments]
- [D] Why isn't GNN in high demand in industry?by /u/Snoo_72181 (Machine Learning) on April 21, 2024 at 11:04 pm
Almost no job posting for Data Scientist or ML Engineer needs GNNs. Is it because it's computationally expensive - both time and space? Or is it because preprocessing data to a graph format is not always intuitive? Or GNN awareness is still low outside of academia? submitted by /u/Snoo_72181 [link] [comments]
- Best AudioBooks?[D]by /u/ResidentMaize2535 (Machine Learning) on April 21, 2024 at 6:38 pm
Best up to date and current books to learn machine learning and AI from a technical perspective? I work in tech but would like to further my understanding. I have a general understanding of the concept. I do a lot of driving so this is a passive listen. submitted by /u/ResidentMaize2535 [link] [comments]
- [Research] A visual deep dive into Tesla’s data engine as pioneered by Andrej Karpathy.by /u/ml_a_day (Machine Learning) on April 21, 2024 at 6:18 pm
TL;DR: Tesla uses lightweight "trigger classifiers" to detect rare scenarios when their ML model underperforms. Relevant data is uploaded to a server to improve the model, which is then trained again to cover different failure modes. How Tesla Continuously and Automatically Improves Autopilot and Full Self-Driving Capability On 5M+ Cars. A visual guide: How Tesla sets up their iterative ML pipeline P.S.: I spent several hours researching and preparing a visual deep dive of Tesla’s data engine as pioneered by Andrej Karpathy. The post lays out the iterative recipe of how Tesla improves it's fully self-driving and Autopilot capabilities. https://preview.redd.it/qxmjeavmjvvc1.jpg?width=1456&format=pjpg&auto=webp&s=94cb35f71f7e57b6bcc6e0bf9f1d5f05b5c7f086 https://preview.redd.it/htz4p8vmjvvc1.jpg?width=1456&format=pjpg&auto=webp&s=a722604b59d2c6fbb8f7e605ad496bede05a238e submitted by /u/ml_a_day [link] [comments]
Google’s Carbon Copy: Is Google’s Carbon Programming language the Right Successor to C++?
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Is Google’s Carbon Programming language the Right Successor to C++?
For years, C++ has been the go-to language for high-performance systems programming. But with the rise of multicore processors and GPUs, the need for a language that can take advantage of parallelism has never been greater. Enter Carbon, Google’s answer to the problem. But is it the right successor to C++?
Google has been in the news a lot lately for their new programming language, Carbon. It’s being billed as the successor to C++, but is it really? Let’s take a closer look.
On the surface, Carbon and C++ have a lot in common. They’re both statically typed, object-oriented languages with a focus on performance. They both have a learning curve, but once you know them, you can write code that is both readable and maintainable. However, there are some key differences that make Carbon a more attractive option for modern programmers.
For one, Carbon is garbage collected. This means that you don’t have to worry about manually managing memory, which can be a pain in C++. Carbon also has better support for concurrency than C++. With the rise of multicore processors, this is an important consideration. Finally, Carbon has a more modern standard library than C++. This includes features like string interpolation and pattern matching that make common tasks easier to accomplish.
According to Terry Lambert, Carbon Programming language is probably not the successor of C++. His reason are:
“Single inheritance is a deal-breaker for me, even though the eC++ utilized by IOKit in macOS and iOS has the same restrictions.
Although it specifies stronger type enforcement, which would — in theory — also eliminate RTTI and the reflection, which eC++ has historically eliminated as well, it’s doing it via expression-defined typing, rather than explicitly eliminating it. I expect that it would also prevent use of dynamic_cast, although that’s not explicitly called out.
Let’s see if Linus approves of someone compiling the Linux kernel with Carbon, and then starting to add Carbon syntax code, into that port of Linux.”
On the surface, Carbon seems like a great choice to replace C++. It is designed to be more reliable and easier to use than C++. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon. First, it is not compatible with all operating systems. Second, it does not have all of the features of C++. Third, it is not as widely used as C++. Finally, it is still in development and has not been released yet.
These drawbacks may seem like deal breakers, but they don’t necessarily mean that Carbon is not the right successor to C++. First, while Carbon is not compatible with all operating systems, it is compatible with the most popular ones. Second, while it does not have all of the features of C++, it has the most important ones. Third, while it is not as widely used as C++, it is gaining popularity rapidly. Finally, while it is still in development, it is expected to be released soon.
What Is Carbon?
Carbon is a statically typed systems programming language developed by Google. It is based on C++ and shares a similar syntax. However, Carbon introduces several new features that make it better suited for parallelism. For example, Carbon provides first-class support for threads and synchronization primitives. It also offers a number of built-in data structures that are designed for concurrent access. Finally, Carbon comes with a toolchain that makes it easy to build and debug parallel programs.
Why Was Carbon Created?
Google’s primary motivation for developing Carbon was to improve the performance of its search engine. To do this, they needed a language that could take advantage of multicore processors and GPUs. C++ was not well suited for this purpose because it lacked support for threading and synchronization. As a result, Google decided to create their own language that would be purpose-built for parallelism.
Is Carbon The Right Successor To C++?
In many ways, yes. Carbon addresses many of the shortcomings of C++ when it comes to parallelism. However, there are some drawbacks. First, Carbon is still in its infancy and lacks many of the features and libraries that have made C++ so popular over the years. Second, because it is designed specifically for parallelism, it may be less suitable for other purposes such as embedded systems programming or network programming. Overall, though, Carbon looks like a promising successor to C++ and is worth keeping an eye on in the future.
Conclusion:
So, is Google’s new Carbon programming language the right successor to C++? We think that Google’s Carbon programming language has the potential to be a great successor to C++.
With its garbage collection, better support for concurrency, and modern standard library, Carbon has everything that today’s programmer needs.
It is designed to be more reliable and easier to use than its predecessor. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon that should be considered before making the switch from C++.
So if you’re looking for a new language to learn, we recommend giving Carbon a try.
Programming paradigms 2022-2023
Programming paradigms are a way to classify programming languages based on their features. Languages can be classified into multiple paradigms.
Some paradigms are concerned mainly with implications for the execution model of the language, such as allowing side effects, or whether the sequence of operations is defined by the execution model. Other paradigms are concerned mainly with the way that code is organized, such as grouping a code into units along with the state that is modified by the code. Yet others are concerned mainly with the style of syntax and grammar.
Common programming paradigms include:
- imperative in which the programmer instructs the machine how to change its state,
- procedural which groups instructions into procedures,
- object-oriented which groups instructions with the part of the state they operate on,
- declarative in which the programmer merely declares properties of the desired result, but not how to compute it
- functional in which the desired result is declared as the value of a series of function applications,
- logic in which the desired result is declared as the answer to a question about a system of facts and rules,
- mathematical in which the desired result is declared as the solution of an optimization problem
- reactive in which the desired result is declared with data streams and the propagation of change
Six programming paradigms that will change how you think about coding
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Practice Carbon Programming Language at Hackerrank or LeetCode or FreeCodeCamp
Leetcode and HackerRank coding tests don’t work in developer interviews.
Here’s the proof:
Research has shown that work sample tests are VERY effective at determining if someone will we a good fit for a job. But here’s the problem: Work sample tests require applicants to perform tasks or work activities that mirror the tasks employees perform on the job.
When was the last time you had to “reverse an integer” or “find the longest substring without repeating characters”. These types of tests don’t mirror the tasks that software developers perform on the job.
It’s like testing an architect by having them build a house out of playing cards. Leetcode problems are just brain teasers.
If you want to administer a work sample test, have them do a code review, build a tiny feature in your product, or read and explain some part of your product code. (Every developer knows 90% of your time is spent reading code.)
Developers are tired of Leetcode interviews. It’s time to stop wasting everyone’s time.
Malbolge 2022 2023
RegEx is just Malbolge for Strings:
What is the hardest programming language? For me, I say C++, C, and Malbolge. Out of all of these, Malbolge is the hardest
Replit Mobile App: Code on Android and iOS.
Z-Library. The world’s largest ebook library
Top 50 Programming Languages Ranked by the Number of Influenced Languages
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Benefits and Drawbacks of Working Remotely in Africa: Has Africa fully embraced hybrid teams, digital workspace and the use of remote workers?
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What are The Benefits and Drawbacks of Working Remotely in Africa?
Has Africa fully embraced hybrid teams, digital workspace and the use of remote workers?
The COVID-19 pandemic has forced many businesses to reevaluate the way they operate. For some, this has meant a shift to hybrid teams, with employees working remotely part of the time. For others, it’s meant a move to digital workspaces and an embrace of remote workers. But what does this mean for Africa? Has the continent fully embraced these changes? Let’s take a look.
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The Pros of Working Remotely in Africa
There are a number of advantages to working remotely in Africa. First, it allows businesses to tap into a larger pool of talent. With more people working remotely, businesses can hire the best employees, regardless of location. Second, it can help reduce costs. With no need for office space or equipment, businesses can save money by having employees work remotely. Finally, it can promote a better work-life balance. With no need to commute, employees can have more time for family and hobbies.
The Cons of Working Remotely in Africa
However, there are also some drawbacks to working remotely in Africa. First, there is the issue of internet connectivity. While most African countries have access to high-speed internet, there are still some areas that do not. This can make it difficult for remote workers to stay connected and productive. Second, there is the issue of time zones. With workers in different time zones, it can be difficult to schedule meetings and conference calls. Finally, there is the issue of culture.
Working remotely can be isolating, and it can be difficult to build relationships with coworkers when you’re not in the same place.
The Benefits of Hybrid Teams
A hybrid team is a mix of full-time employees and freelancers or contractors who work together to achieve a common goal. This model offers a number of benefits for businesses, including increased flexibility, reduced costs, and improved access to skills and talent.
One of the biggest advantages of hybrid teams is that they offer businesses increased flexibility. With a hybrid team, businesses can scale up or down as needed, which is ideal in today’s ever-changing business landscape. Additionally, hybrid teams allow businesses to tap into a wider pool of skills and talent. And because freelancers and contractors are typically paid by the project, businesses can save money by only paying for the work that is completed.
The Digital Workspace
The digital workspace is a new way of working that enables employees to be productive from anywhere at any time. It includes cloud-based applications and services that allow employees to access their files and applications from any device with an internet connection.
The digital workspace offers a number of benefits for businesses, including increased productivity, reduced costs, and improved collaboration. Perhaps most importantly, it gives employees the freedom to work from anywhere at any time. This is especially beneficial for employees in Africa who may not have reliable access to electricity or internet connectivity.
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Remote Workers in Africa
The COVID-19 pandemic has forced many businesses around the world to embrace remote work. In Africa, we are seeing a similar trend, with more and more businesses allowing employees to work from home or other remote locations. There are many reasons for this, but chief among them are increased productivity and reduced costs.
When done correctly, remote work can lead to increased productivity as employees are free to design their own schedules and work in environments that suit their needs. Additionally, remote work can help reduce costs by eliminating the need for office space and associated overhead costs.
The benefits of hybrid teams are well-documented. A study by Harvard Business Review found that companies with diverse teams are 35% more likely to outperform their peers. Another study by McKinsey & Company found that businesses with gender-diverse leadership teams are 21% more likely to generate above-average profits. In Africa, the benefits of hybrid teams are especially pronounced.
The African continent is home to a wide variety of cultures and languages. This diversity is an asset that can be leveraged by businesses to gain a competitive edge. By tapping into the talents of people from all corners of the continent, businesses can create products and services that appeal to a global market.
In addition, the use of remote workers allows businesses to tap into a wider pool of talent. By eliminating the need for employees to be physically present in an office, businesses can hire the best person for the job regardless of location. This has led to increased productivity and efficiency in the workplace.
Overall, working remotely in Africa has its pros and cons. However, with the right infrastructure and support in place, remote work can be a great option for businesses and employees alike.
The rise of hybrid teams has had a positive impact on Africa. By bringing together people with different skillsets and backgrounds, businesses have been able to create products and services that appeal to a global market. In addition, the use of remote workers has allowed businesses to tap into a wider pool of talent. This has led to increased productivity and efficiency in the workplace.
The COVID-19 pandemic has changed the way we live and work. In Africa, we are seeing a trend towards hybrid teams, the digital workspace, and remote workers. This new way of working offers a number of benefits for businesses, including increased flexibility, reduced costs, and improved access to skills and talent. As we continue to adapt to the new normal brought on by the pandemic, it is clear that these trends are here to stay.
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HISTORY – GEOGRAPHY – CULTURE – PEOPLE – CUISINE – ECONOMICS – LANGUAGES – MUSIC – WILDLIFE – FOOTBALL – POLITICS – ANIMALS – TOURISM – SCIENCE – ENVIRONMENT
How well do you know Africa? Test your knowledge with this Africa history and geography quiz. Africa is the world’s second largest continent, and it is home to a stunning diversity of cultures, languages, and landscapes. From the Sahara Desert to the rainforests of the Congo Basin, Africa boasts a huge variety of geography. And its history is just as rich, from ancient civilizations like Egypt and Ethiopia to European colonization and the struggle for independence. So whether you’re an Africa expert or just getting started, this quiz will help you test your knowledge of this amazing continent.
Africa is a vast and fascinating continent with a rich history and diverse culture. To test your knowledge of Africa, take this Africa History and Geography Quiz. See how much you know about the people, places, and events that have shaped Africa over the centuries.
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- Binance Executive Who Fled Nigerian Custody Arrested in Kenya, Set for Extradition |by /u/ibson7 (Africa) on April 22, 2024 at 4:23 pm
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- The Role of Mentorship in Empowering Youth: Building a Brighter Future in Ugandaby Penner Ministries (Africa on Medium) on April 22, 2024 at 3:49 pm
At Penner Ministries, we witness firsthand the transformative power of education and economic opportunity in the lives of Ugandan youth…Continue reading on Medium »
- Nigerians Like to Talk, Part 1.by Lasun (Africa on Medium) on April 22, 2024 at 2:42 pm
If you’ve lived in Nigeria for more than 5 minutes, there’s a great chance you have experienced the following scene: a group of people…Continue reading on Medium »
- A Nightmare for Sexual Minorities in Ugandaby Olivier Pilon (Africa on Medium) on April 22, 2024 at 2:15 pm
It isn’t easy to be gay in Africa. Most of its countries discriminate and persecute members of the LGBT community.Continue reading on Medium »
- I am resharing this article: "A story to be read with the lights off" — by Humphrey Kariuki.by Kelvin Keter (Africa on Medium) on April 22, 2024 at 2:14 pm
If I were to re-write this story, I would replace 'lights off,’ with ‘Internet off". What the light did to the world has been taken up…Continue reading on Medium »
- Ethiopia land violence leaves thousands homelessby /u/TheGrazmach (Africa) on April 22, 2024 at 1:53 pm
Kalkidan Yibeltal writes for BBC Africa: "Fighting over disputed land along borders of Ethiopia's Tigray and Amhara regions has displaced close to 29,000 people, the United Nations says." submitted by /u/TheGrazmach [link] [comments]
- Leveraging WhatsApp for Community Engagement: The Weaverbirds Approachby Weaverbirds (Africa on Medium) on April 22, 2024 at 12:53 pm
In part one of a two part blog post, we will begin looking at the key elements of Weaverbirds’ approach, starting with low-tech community…Continue reading on Medium »
- Youthwave game — Malik, Usman and the governmentby YouthWaveGame (Africa on Medium) on April 22, 2024 at 12:35 pm
Author : My name is Malik, a passionate student of Mass Communication at Olabisi Onabanjo University. When I’m not buried in textbooks…Continue reading on Medium »
- Chinese Supermarket in Abuja Sparks Outrage for Allegedly Refusing Sales to Nigerians |by /u/ibson7 (Africa) on April 22, 2024 at 11:46 am
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- Mumbi: The Birthgiver and the Dawn of the Kikuyu Peopleby Mwangi Kamae (Africa on Medium) on April 22, 2024 at 11:43 am
In the misty dawn of time, before the sun had carved its path across the sky, there lived a lone fig tree on a vast and silent plain. This…Continue reading on Medium »
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Africa, Global trade, Maritime, SeaportContinue reading on Medium »
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Africa, African Airlines, AviationContinue reading on Medium »
- How Web3 Revolutionizes African Financial Servicesby Web3Africa.news (Africa on Medium) on April 22, 2024 at 10:12 am
Explore how blockchain technology is transforming African financial services through real-world use cases.Continue reading on Medium »
- Non fiction books that take place in a country in Africaby /u/denys1973 (Africa) on April 22, 2024 at 2:04 am
Hi! I'm doing a project where I read books that take place in various countries. My goal is to read at least one book for every country in the world. Does anyone have recommendations for non fiction books that take place in Africa? I'm most interested in topics related to the present day. Two books I've read so far are Africa Is Not a Country and Born a Crime. Thank you! submitted by /u/denys1973 [link] [comments]
- Algeria and Tunisia Pursue Maghreb Union ‘Dream,’ Exclude Morocco From Talksby /u/Various_Ranger5684 (Africa) on April 21, 2024 at 8:08 pm
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- The radical philosophy of the Hatata: a 17th century treatise by the Ethiopian thinker Zara Yacobby /u/rhaplordontwitter (Africa) on April 21, 2024 at 3:50 pm
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- Mount Cameroon from a small village in Littoral-Cameroonby /u/Brolyisbroccoli (Africa) on April 21, 2024 at 3:39 pm
submitted by /u/Brolyisbroccoli [link] [comments]
- A Nigerian chess champion plays the royal game for 60 hours — a new global chess recordby /u/9A69C889E0122099 (Africa) on April 21, 2024 at 1:04 am
submitted by /u/9A69C889E0122099 [link] [comments]
- Nairobi, Kenyaby /u/ContributionUpper424 (Africa) on April 20, 2024 at 10:36 pm
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- Change in GDP per capita in Africa from 2014 to 2024[IMF]by /u/TajineEnjoyer (Africa) on April 20, 2024 at 4:15 pm
submitted by /u/TajineEnjoyer [link] [comments]
What is machine learning and how does Netflix use it for its recommendation engine?
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What is machine learning and how does Netflix use it for its recommendation engine?
What is an online recommendation engine?
Think about examples of machine learning you may have encountered in the past such as a website like Netflix that recommends what video you may be interested in watching next?
Are the recommendations ever wrong or unfair? We will give an example and explain how this could be addressed.
Machine learning is a field of artificial intelligence that Netflix uses to create its recommendation algorithm. The goal of machine learning is to teach computers to learn from data and make predictions based on that data. To do this, Netflix employs Machine Learning Engineers, Data Scientists, and software developers to design and build algorithms that can automatically improve over time. The Netflix recommendations engine is just one example of how machine learning can be used to improve the user experience. By understanding what users watch and why, the recommendations engine can provide tailored suggestions that help users find new shows and movies to enjoy. Machine learning is also used for other Netflix features, such as predicting which shows a user might be interested in watching next, or detecting inappropriate content. In a world where data is becoming increasingly important, machine learning will continue to play a vital role in helping Netflix deliver a great experience to its users.
Netflix’s recommendation engine is one of the company’s most valuable assets. By using machine learning, Netflix is able to constantly improve its recommendations for each individual user.
Machine learning engineers, data scientists, and developers work together to build and improve the recommendation engine.
- They start by collecting data on what users watch and how they interact with the Netflix interface.
- This data is then used to train machine learning models.
- The models are constantly being tweaked and improved by the team of engineers.
- The goal is to make sure that each user sees recommendations that are highly relevant to their interests.
Thanks to the work of the team, Netflix’s recommendation engine is constantly getting better at understanding each individual user.
How Does It Work?
In short, Netflix’s recommendation algorithm looks at what you’ve watched in the past and then makes recommendations based on that data. But of course, it’s a bit more complicated than that. The algorithm also looks at data from other users with similar watching habits to yours. This allows Netflix to give you more tailored recommendations.
For example, say you’re a big fan of Friends (who isn’t?). The algorithm knows that a lot of Friends fans also like shows like Cheers, Seinfeld, and The Office. So, if you’re ever feeling nostalgic and in the mood for a sitcom marathon, Netflix will be there to help you out.
But That’s Not All…
Not only does the algorithm take into account what you’ve watched in the past, but it also looks at what you’re currently watching. For example, let’s say you’re halfway through Season 2 of Breaking Bad and you decide to take a break for a few days. When you come back and finish Season 2, the algorithm knows that you’re now interested in similar shows like Dexter and The Wire. And voila! Those shows will now be recommended to you.
Of course, the algorithm isn’t perfect. There are always going to be times when it recommends a show or movie that just doesn’t interest you. But hey, that’s why they have the “thumbs up/thumbs down” feature. Just give those shows the old thumbs down and never think about them again! Problem solved.
Another angle :
When it comes to TV and movie recommendations, there are two main types of data that are being collected and analyzed:
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1) demographic data
2) viewing data.
Demographic data is information like your age, gender, location, etc. This data is generally used to group people with similar interests together so that they can be served more targeted recommendations. For example, if you’re a 25-year-old female living in Los Angeles, you might be grouped together with other 25-year-old females living in Los Angeles who have similar viewing habits as you.
Viewing data is exactly what it sounds like—it’s information on what TV shows and movies you’ve watched in the past. This data is used to identify patterns in your viewing habits so that the algorithm can make better recommendations on what you might want to watch next. For example, if you’ve watched a lot of romantic comedies in the past, the algorithm might recommend other romantic comedies that you might like based on those patterns.
Are the Recommendations Ever Wrong or Unfair?
Yes and no. The fact of the matter is that no algorithm is perfect—there will always be some error involved. However, these errors are usually minor and don’t have a major impact on our lives. In fact, we often don’t even notice them!
The bigger issue with machine learning isn’t inaccuracy; it’s bias. Because algorithms are designed by humans, they often contain human biases that can seep into the recommendations they make. For example, a recent study found that Amazon’s algorithms were biased against women authors because the majority of book purchases on the site were made by men. As a result, Amazon’s algorithms were more likely to recommend books written by men over books written by women—regardless of quality or popularity.
These sorts of biases can have major impacts on our lives because they can dictate what we see and don’t see online. If we’re only seeing content that reflects our own biases back at us, we’re not getting a well-rounded view of the world—and that can have serious implications for both our personal lives and society as a whole.
One of the benefits of machine learning is that it can help us make better decisions. For example, if you’re trying to decide what movie to watch on Netflix, the site will use your past viewing history to recommend movies that you might like. This is possible because machine learning algorithms are able to identify patterns in data.
Another benefit of machine learning is that it can help us automate tasks. For example, if you’re a cashier and have to scan the barcodes of the items someone is buying, a machine learning algorithm can be used to automatically scan the barcodes and calculate the total cost of the purchase. This can save time and increase efficiency.
The Consequences of Machine Learning
While machine learning can be beneficial, there are also some potential consequences that should be considered. One consequence is that machine learning algorithms can perpetuate bias. For example, if you’re using a machine learning algorithm to recommend movies to people on Netflix, the algorithm might only recommend movies that are similar to ones that people have already watched. This could lead to people only watching movies that confirm their existing beliefs instead of challenged them.
Another consequence of machine learning is that it can be difficult to understand how the algorithms work. This is because the algorithms are usually created by trained experts and then fine-tuned through trial and error. As a result, regular people often don’t know how or why certain decisions are being made by machines. This lack of transparency can lead to mistrust and frustration.
What are some good datasets for Data Science and Machine Learning?
This scene in the Black Panther trailer, is it T’Challa’s funeral?
Recommended New Netflix Movies 2022
- What made Baby Reindeer for me was the inclusion of Martha’s story at the end and I have some sympathy for her.by /u/HairyPlumbs (Netflix) on April 22, 2024 at 5:27 pm
I personally think it was a great series and it’s the only series that has kept me hooked for a long time. Many people have praised Richard for his bravery and I completely agree. However one thing I haven’t seen anyone talk about is Martha’s story when she reveals why she always calls him baby reindeer. Which is because of her abusive family and her baby reindeer teddy is the only comfort she had. I’m very lucky and have grown up with loving parents who would do anything for me. So what does this have to do with sympathy for Martha? My parents were also foster parents so I have experienced (to a small extent) both sides of the spectrum and have grew up with foster children and teenagers from poor and deprived backgrounds. So I have never personally experienced a poor family background but I have seen what it does and the impact it has on people and I have seen many personalities that stem from this too, some good like independence, some bad like extreme attachment disorder like Martha has. So the reason I feel for Martha to an extent and think baby reindeer hits a stroke of genius is because by telling her story at the end it shows that at first she comes across as a complete psycho, but then you understand why. She has actually had a terrible life, she just wanted the love and affection she never received as a child. she came from an abusive background with no one there for her, she lived on her own with no one to care for her throughout the whole series and had no one at all to help her. So when she did find someone who showed even the slightest sign of sympathy.. she clung onto them as it was all she had. Some of the things Martha did is completely wrong and inexcusable, but when he dug deep and discovered why in the voice messages and began to cry I think Donny realised himself... how alone and traumatised Martha was to the point she became mentally ill. Sometimes it’s help these people need, and if she wasn’t so traumatised by her abusive family she may never have been so troubled and have the attachment disorders she now has to live with. submitted by /u/HairyPlumbs [link] [comments]
- Why can’t we rate content?by /u/One-Drawing6470 (Netflix) on April 22, 2024 at 4:50 pm
I’ve always wondered why this isn’t available. The top shows are always skewed to the newest release and not always indicative of quality IMO. Like Rebel Moon is probably a solid 2.75-5 stars but easiest to watch. Anyone have any insight on this? submitted by /u/One-Drawing6470 [link] [comments]
- Just found out about a series called Squid Game!by /u/JAVOK1 (Netflix) on April 22, 2024 at 3:53 pm
I was scrolling through Netflix a few days ago after finishing a series called bloodhounds and I was looking for another Korean series. And after a little while I found a series called squid game that I don’t think I’ve ever seen before. I think it’s not really that popular but it’s really good, I binge watched it for 2 days and it honestly really surprised me that it’s not as popular as it’s supposed to be! I loved it and it deserves more popularity submitted by /u/JAVOK1 [link] [comments]
- Missing shows on Netflix when going between phone app, roku and laptop.by /u/rubycatts (Netflix) on April 22, 2024 at 2:46 pm
I have no idea if this is a Netflix issue, Roku issue or internet issue. We use a Roku device with our TV and the past week I noticed that there are shows missing on the Netflix app when I try to watch on the TV, but they are available if I use the Netflix app on my phone or laptop. Same wifi connection and I do not use a VPN or proxy. We have Starlink and it will connect to whatever ground station it wants and sometimes websites think I am in a completely different state in the US than where I live. This hasn't been an issue in the past. I rarely watch outside of using our home. About two weeks ago I was watching on my phone (iphone) and I did get the message saying that I was using a vpn or proxy. I don't have a vpn on my phone or use a proxy. I just closed the app and restarted and went on with whatever I was watching. I have uninstalled and reinstalled the netflix app on the roku device, restarted my internet connection, made sure all ip show in my general area. I don't have this issue with any other streaming app. Any idea on what the issue could be and how to fix it? Thanks! submitted by /u/rubycatts [link] [comments]
- Official Posters for 'Deadpool & Wolverine'by /u/MarvelsGrantMan136 (Movie News and Discussion) on April 22, 2024 at 1:12 pm
submitted by /u/MarvelsGrantMan136 [link] [comments]
- Zack Snyder’s ‘Twilight of the Gods,’ the Next Wallace & Gromit Film and the ‘Ultraman’ World Premiere Headline Netflix’s Annecy Slateby /u/misana123 (Netflix) on April 22, 2024 at 1:01 pm
submitted by /u/misana123 [link] [comments]
- Movies that pleasantly surprised you in avoiding a cliche?by /u/ArgoverseComics (Movie News and Discussion) on April 22, 2024 at 1:00 pm
I have two: The first one is David Morse in The Negotiator NOT turning out to be a corrupt cop. For the whole movie we’re left in the dark as to which cops are in on the conspiracy and we really feel like the movie is telling us David Morse is in on it, and he plays into it a little with these subtle shifty mannerisms and hotheaded attitude, where we feel like he’s trying to get Sam Jackson killed before he can reveal anything. In the hands of a lesser writer/director he would have been revealed as a bad guy. The second one is the dinner scene in Absolute Power. Clint Eastwood shows up dressed like Inspector Gadget and it’s like… really? You’re just playing right into the cloak and dagger stuff like that? I thought he was a master of disguise! And then the shooting starts and we realise he was covering up a police uniform disguise. submitted by /u/ArgoverseComics [link] [comments]
- Deadpool & Wolverine | Official Trailerby /u/MarvelsGrantMan136 (Movie News and Discussion) on April 22, 2024 at 12:55 pm
submitted by /u/MarvelsGrantMan136 [link] [comments]
- So what happened in baby reindeer and to richard gadd happened for real?by /u/gronbek (Netflix) on April 22, 2024 at 12:43 pm
Very good show. Am i understanding it correctly that what happened to richard in the show also happened to him in real life with drugs and all shit? Quite unique to see an actor playing himself in a true story in that case. submitted by /u/gronbek [link] [comments]
- The Transformation Of Jack Nicholson (Turns 87 Today)by /u/Crazy_Historian_5731 (Movie News and Discussion) on April 22, 2024 at 12:36 pm
submitted by /u/Crazy_Historian_5731 [link] [comments]
- What Are The Greatest Ground Level Action Movies?by /u/jigtwazlo (Movie News and Discussion) on April 22, 2024 at 11:40 am
I love all action cinema, but there's something about action movies where it feels like it could actually happen that is far more appealing. There's something quite bizarre about typing 'action movies like Die Hard' on Google and being met with Star Wars or Avengers. There's NOTHING wrong with those classics, but they don't have that 'almost possible' edge that an action flick starring your average Joe in a situation way over their heads might have. So avoiding sci fi or fantastical action flicks, what are the greatest ground level, almost plausible examples of action cinema? I suppose the obvious choices would be Die Hard, Lethal Weapon and there are plenty of martial arts movies but where to begin... submitted by /u/jigtwazlo [link] [comments]
- Dazed and Confusedby /u/Jojoamackinhoes (Movie News and Discussion) on April 22, 2024 at 10:36 am
Not sure if this film gets a lot of love on here, but I just want to say I absolutely fucking love it. It's in my top 3 all time along with Interstellar and The Matrix. What makes it so special to me is it really just takes you on a journey with these kids on the last day of school. I love all the characters, well maybe not Mitch but he's ok. It doesn't have much of a plot, It's just a great slice of life film that I think anyone of all ages can enjoy. So many quotebale lines, great performances all around. It doesn't even matter if your not from that time period (I'm not) but maybe it helps? I saw this movie as a young lad around 14 or so in 2004, high off my ass and it became an instant favorite. I love it stoned, sober, with friends, drinking it doesn't matter, this film holds a special place in my heart and always will so I just wanted to show some love to it. If you haven't seen it, I urge you to check it out and let me know what you think. submitted by /u/Jojoamackinhoes [link] [comments]
- Movies where the scale of the events as described as the characters are completely different to what we the audience can actually see onscreen.by /u/WexfordYouths (Movie News and Discussion) on April 22, 2024 at 8:18 am
For example, In Star Wars: The Last Jedi, the audience would expect that the war between the First Order and Resistance is this massive, galactic conflict. But by the end of the movie, the entire Resistance army fits on the Millennium Falcon. I don't think that's an exaggeration either (unless I'm misremembering), literally about 100 lads are one side of a galactic war. The scale of the movie feels completely off. Can you think of other examples of this? submitted by /u/WexfordYouths [link] [comments]
- Baby reindeer endingby /u/Typical-Foundation-6 (Netflix) on April 22, 2024 at 8:01 am
In the end is it implied that he is now going to stalk the bartender? Or simply found a person to hyperfixate? I know the show is based off several true stories and events so I feel the ending might be up to interpretation, or viewed differently than what might have actually happened. submitted by /u/Typical-Foundation-6 [link] [comments]
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What are the top 10 algorithms every software engineer should know by heart?
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What are the top 10 algorithms every software engineer should know by heart?
As a software engineer, you’re expected to know a lot about algorithms. After all, they are the bread and butter of your trade. But with so many different algorithms out there, how can you possibly keep track of them all?
Never fear! We’ve compiled a list of the top 10 algorithms every software engineer should know by heart. From sorting and searching to graph theory and dynamic programming, these are the algorithms that will make you a master of your craft. So without further ado, let’s get started!
Sorting Algorithms
Sorting algorithms are some of the most fundamental and well-studied algorithms in computer science. They are used to order a list of elements in ascending or descending order. Some of the most popular sorting algorithms include quicksort, heapsort, and mergesort. However, there are many more out there for you to explore.
Searching Algorithms
Searching algorithms are used to find an element in a list of elements. The most famous search algorithm is probably binary search, which is used to find an element in a sorted list. However, there are many other search algorithms out there, such as linear search and interpolation search.
Graph Theory Algorithms
Graph theory is the study of graphs and their properties. Graph theory algorithms are used to solve problems on graphs, such as finding the shortest path between two nodes or finding the lowest cost path between two nodes. Some of the most famous graph theory algorithms include Dijkstra’s algorithm and Bellman-Ford algorithm.
This graph has six nodes (A-F) and eight arcs. It can be represented by the following Python data structure:
graph = {'A': ['B', 'C'],
'B': ['C', 'D'],
'C': ['D'],
'D': ['C'],
'E': ['F'],
'F': ['C']}
def find_all_paths(graph, start, end, path=[]):
path = path + [start]
if start == end:
return [path]
if not graph.has_key(start):
return []
paths = []
for node in graph[start]:
if node not in path:
newpaths = find_all_paths(graph, node, end, path)
for newpath in newpaths:
paths.append(newpath)
return paths
A sample run:
>>> find_all_paths(graph, 'A', 'D')
[['A', 'B', 'C', 'D'], ['A', 'B', 'D'], ['A', 'C', 'D']]
>>># Code by Eryk Kopczyński
def find_shortest_path(graph, start, end):
dist = {start: [start]}
q = deque(start)
while len(q):
at = q.popleft()
for next in graph[at]:
if next not in dist:
dist[next] = [dist[at], next]
q.append(next)
return dist.get(end)Dynamic Programming Algorithms
Dynamic programming is a technique for solving problems that can be divided into subproblems. Dynamic programming algorithms are used to find the optimal solution to a problem by breaking it down into smaller subproblems and solving each one optimally. Some of the most famous dynamic programming algorithms include Floyd-Warshall algorithm and Knapsack problem algorithm.
Number Theory Algorithms
Number theory is the study of integers and their properties. Number theory algorithms are used to solve problems on integers, such as factorization or primality testing. Some of the most famous number theory algorithms include Pollard’s rho algorithm and Miller-Rabin primality test algorithm.
Example: A school method based Python3 program to check if a number is prime
def isPrime(n):
# Corner case
if n <= 1:
return False
# Check from 2 to n-1
for i in range(2, n):
if n % i == 0:
return False
return TrueDriver Program to test above function
print(“true”) if isPrime(11) else print(“false”)
print(“true”) if isPrime(14) else print(“false”)
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Combinatorics Algorithms
Combinatorics is the study of combinatorial objects, such as permutations, combinations, and partitions. Combinatorics algorithms are used to solve problems on combinatorial objects, such as enumeration or generation problems. Some of the most famous combinatorics algorithms include Gray code algorithm and Lehmer code algorithm.
Example: A Python program to print all permutations using library function
from itertools import permutations
Get all permutations of [1, 2, 3]
perm = permutations([1, 2, 3])
Print the obtained permutations
for i in list(perm):
print (i)
Output:
(1, 2, 3) (1, 3, 2) (2, 1, 3) (2, 3, 1) (3, 1, 2) (3, 2, 1)
It generates n! permutations if the length of the input sequence is n.
If want to get permutations of length L then implement it in this way.
Geometry Algorithms
Geometry is the study of shapes and their properties. Geometry algorithms are used to solve problems on shapes, such as finding the area or volume of a shape or finding the intersection point of two lines. Some of the most famous geometry algorithms include Heron’s formula and Bresenham’s line drawing algorithm.
Cryptography Algorithms
Cryptography is the study of encryption and decryption techniques. Cryptography algorithms are used to encrypt or decrypt data. Some of the most famous cryptography algorithms include RSA algorithm and Diffie – Hellman key exchange algorithm.
String Matching Algorithm
String matching algorithms are used t o find incidences of one string within another string or text . Some of the most famous string matching algorithms include Knuth-Morris-Pratt algorithm and Boyer-Moore string search algorithm.
Data Compression Algorithms
Data compression algorithms are used t o reduce the size of data files without losing any information . Some of the most famous data compression algorithms include Lempel-Ziv-Welch (LZW) algorithm and run – length encoding (RLE) algorithm. These are just some of the many important algorithms every software engineer should know by heart ! Whether you’r e just starting out in your career or you’re looking to sharpen your skill set , learning these algorithms will certainly help you on your way!
According to Konstantinos Ameranis, here are also some of the top 10 algorithms every software engineer should know by heart:
I wouldn’t say so much specific algorithms, as groups of algorithms.
Greedy algorithms.
If your problem can be solved with an algorithm that can make a decision now and at the end this decision will still be optimal, then you don’t need to look any further. Examples are Prim, Kruscal for Minimal Spanning Trees (MST) and the Fractional Knapsack problem.
Divide and Conquer.
Examples of this group are binary search and quicksort. Basically, you divide your problem into two distinct sub-problems, solve each one separately and at the end combine the solutions. Concerning complexity, you will probably get something recursive e.g. T(n) = 2T(n/2) + n, which you can solve using the Master theorem
Graph and search algorithms.
Other than the MST, Breadth First Search (BFS) and Depth First Search (DFS), Dijkstra and possibly A*. If you feel you want to go further in this, Bellman-Ford (for dense graphs), Branch and Bound, Iterative Deepening, Minimax, AB search.
Flows. Basically, Ford-Fulkerson.
Simulated Annealing.
This is a very easy, very powerful randomized optimization algorithm. It gobbles NP-hard problems like Travelling Salesman Problem (TSP) for breakfast.
Hashing. Properties of hashing, known hashing algorithms and how to use them to make a hashtable.
Dynamic Programming.
Examples are the Discrete Knapsack Problem and Longest Common Subsequence (LCS).
Randomized Algorithms.
Two great examples are given by Karger for the MST and Minimum Cut.
Approximation Algorithms.
There is a trade off sometimes between solution quality and time. Approximation algorithms can help with getting a not so good solution to a very hard problem at a good time.
Linear Programming.
Especially the simplex algorithm but also duality, rounding for integer programming etc.
These algorithms are the bread and butter of your trade and will serve you well in your career. Below, we will countdown another top 10 algorithms every software engineer should know by heart.
Binary Search Tree Insertion
Binary search trees are data structures that allow for fast data insertion, deletion, and retrieval. They are called binary trees because each node can have up to two children. Binary search trees are efficient because they are sorted; this means that when you search for an element in a binary search tree, you can eliminate half of the tree from your search space with each comparison.
Quicksort
Quicksort is an efficient sorting algorithm that works by partitioning the array into two halves, then sorting each half recursively. Quicksort is a divide and conquer algorithm, which means it breaks down a problem into smaller subproblems, then solves each subproblem recursively. Quicksort is typically faster than other sorting algorithms, such as heapsort or mergesort.
Dijkstra’s Algorithm
Dijkstra’s algorithm is used to find the shortest path between two nodes in a graph. It is a greedy algorithm, meaning that it makes the locally optimal choice at each step in order to find the global optimum. Dijkstra’s algorithm is used in routing protocols and network design; it is also used in manufacturing to find the shortest path between machines on a factory floor.
Linear Regression
Linear regression is a statistical method used to predict future values based on past values. It is used in many fields, such as finance and economics, to forecast future trends. Linear regression is a simple yet powerful tool that can be used to make predictions about the future.
K-means Clustering
K-means clustering is a statistical technique used to group similar data points together. It is used in many fields, such as marketing and medicine, to group customers or patients with similar characteristics. K-means clustering is a simple yet powerful tool that can be used to group data points together for analysis.
Support Vector Machines
Support vector machines are supervised learning models used for classification and regression tasks. They are powerful machine learning models that can be used for data classification and prediction tasks. Support vector machines are widely used in many fields, such as computer vision and natural language processing.
Gradient Descent
Gradient descent is an optimization algorithm used to find the minimum of a function. It is a first-order optimization algorithm, meaning that it uses only first derivatives to find the minimum of a function. Gradient descent is widely used in many fields, such as machine learning and engineering design.
PageRank
PageRank is an algorithm used by Google Search to rank websites in their search engine results pages (SERP). It was developed by Google co-founder Larry Page and was named after him. PageRank is a link analysis algorithm that assigns a numerical weighting to each element of a hyperlinked set of documents, such as the World Wide Web (WWW), with the purpose of “measuring” its relative importance within the set.(Wikipedia)
RSA Encryption
RSA encryption is a public-key encryption algorithm that uses asymmetric key cryptography.(Wikipedia) It was developed by Ron Rivest, Adi Shamir, and Len Adleman in 1977 and has since been widely used in many different applications.(Wikipedia) RSA encryption is used to secure communications between parties and is often used in conjunction with digital signatures.(Wikipedia)
Fourier Transform
The Fourier transform is an integral transform that decomposes a function into its constituent frequencies.(Wikipedia) It was developed by Joseph Fourier in 1807 and has since been widely used in many different applications.(Wikipedia) The Fourier transform has many applications in physics and engineering, such as signal processing and image compression.(Wikipedia)
Conclusion:
These are the top 10 algorithms every software engineer should know by heart! Learning these algorithms will help you become a better software engineer and will give you a solid foundation on which to build your career!
Algorithm Breaking News 2022 – 2023
Instagram algorithm 2022 – 2023
Because the inception of 2010, Instagram has proved its price. The platform that was earlier generally known as a photo-sharing hub has step by step developed itself into aneCommerce platform with Instagram Procuring. Right now most companies use Instagram as a marketing tool to extend their attain throughout the platform. Within the earlier days of Instagram, hashtags grew to become a pattern for straightforward grouping and looking. In a while, a function of product tagging was launched. It made it simpler for folks to seek for the merchandise. In 2016, Instagram algorithms made a serious change. It launched Instagram tales, reside movies, and new enterprise instruments to show their merchandise and gain more followers to their profile.
Read More; How Instagram Algorithm Works In 2022: A Social Media Marketer’s Guide
Instagram uses “Read Path Models” to rank content. It’s an algorithm used by Developers to find the best outcome in a project or a basic filtering algorithm.
Here’s How the algorithm works to rank your content on explore page and home!
First your content is published after Instagram algorithm confirms its Community Guidelines.
After that, Algorithm classifies your content based on your Post Design and Captions.
Using Photo-recognition Instagram Scans your content finds similarities between your new piece of content and your audience’s previous interactions with your old content.
The same process occurs with your post captions. Your post instantly starts reaching your most followers and as engagement rises it gets on explore page.
In words of Instagram employee, This “Write Path Classifiers” algorithm didn’t tracked most important metrics to keep the explore page. That’s why they started building a new version of the algorithm that you can read below!
The new algorithm uses 3 Crucial ways to source content for Your Instagram Explore feed!
Instagram algorithm calculates real-time engagement and upload time signals to consider your post for Explore page.
In simple words, Instagram measures how much engagement creators at your level get and how much engagement your recent posts and how’s the engagement growing since the upload time.
Tip: Look at your insights and see what time your followers are highly active and post 40-70 minutes before the peak time.
This step constitutes search queries from Instagram users related to your post.
Instagram finds targeted users to show your post to them based on their search queries. Your post will show up on top of their explore page.
A Post on “Start Your Entrepreneurship Journey” will be shown to people searching for entrepreneurship to a small query about passive income.
From those queries Instagram source content for explore page.
How long you rank on Instagram page and to what audience depends on the engagement you get when you start ranking on explore page.
After the sourcing step is passed that means your content is eligible to rank on explore page.
And during this step, tracking engagement metrics and their growth algorithm keeps your Post on Explore Page.
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Instagram announced Sensitivity control last year which impacted Instagram explore algorithm again!
What’s changed?
Instagram launched two new filters one High precision and low precision filters to maintain better content on Instagram for Different audiences.
Explore page changes every second with every refresh. So, do your content’s target audience.
With these two filters, Instagram tries to track engagement from different-different users and changes pieces of content.
In simple words, Instagram doesn’t want to show people bad content. That’s why these filters work to run explore page content through database to find if it’s suitable to run for another minute, hour or day on Instagram.
You get Hashtags reach because Instagram’s old algorithm “Write Path Classifier” is applicable to every single format of content.
Means your content ranks on hashtags based on relevancy with your Post Image and Caption.
If it’s relevant and getting enough engagement to rank on Hashtags size. You will rank on hashtags. It’s not hard to crack hashtags algorithm. The advice is don’t focus on hashtags that much, and keep your eyes on creating content for explore page.
“Instagram story views increase and decrease based on “navigation” and “interaction”.
What’s navigation?
In Instagram story insights, you will see a metric called “navigation” and below that you will see
Back- means the follower swiped back to see your last story or someone else’s story they saw before! Forward- means the follower clicked to see your next story Next story- the follower moved to see someone else’s story Exited- means the follower left the stories.
Founded: If your story have more forward and next stories. Then Instagram will push your stories to more followers as they want users to watch more stories and stay in stories tab.
Why?: After 2-3 stories they hit users with an ad!
Interactions: Polls/ Question stickers/ Quiz
When viewers interact with these story features. Instagram sees that followers are interacting more than before and that’s why they start pushing it more
How interactions like “profile visits” effect story views?
Yes, if your followers are visiting your profile through stories. Then that particular story (if its the first one) will receive more views than average as my story with 44 profile visits received the most views. So, you should do something worth a profile visit!
I didn’t get much out of the conversation about Instagram reels from employees at IG.
But the only tip was to maintain the highest quality of video while uploading because while content distribution through Instagram processors your video might lose some quality.
Acls algorithm 2022 – 2023,
Free copy/print of all the ACLS algorithms
Algorithms for Advanced Cardiac Life Support
algo-arrestTiktok algorithm 2022 – 2023,
Your first few hours on tiktok are crucial to your growth.
You gonna spend few hours on fyp, interacting with videos and creators about your niche. -After few hours, you can start to make your first video
The very first video plays a huge role in your future. -Quality content -Unique but similar to your niche
9-15 seconds maximum!!
After upload, wait about a few hours, before your second video
2nd video needs to have a hook
“You won,t believe this”
“ Nobody is talking about this, but”
“Did you know that..?”
“ X tips on how to ..”
Your hook needs to be on your first few seconds of the video
Your videos needs to be captivating or strange, this way users spends more time on it.
Your next 3 videos should be similar
Tiktok usually boosts your first videos, that’s their hook
Now you need to hook tiktok onto your account to keep boosting it.
You will lose views and engagement
Its normal, you are not shadow banned. you just have to do it on your own now.
Now its time to get more followers
Do duets/stiches/parts
this way you hook your new followers and cycle up your old videos
now you need to have schedule
3-4 posts /day works the best.
wait 3-4h before your next post
Followers >Views
If you have 10k followers then you need at least 10k views /post to keep growing fast -Don’t follow people who follow you.
How Does The Tiktok Algorithm Work? (+10 Viral Hacks To Go)
Youtube algorithm 2022 – 2023,
Google algorithm update 2022 – 2023,
https://developers.google.com/search/updates/ranking
This page lists the latest ranking updates made to Google Search that are relevant to website owners. To learn more about how Google makes improvements to Search and why we share updates, check out our blog post on How Google updates Search. You can also find more updates about Google Search on our blog.
https://blog.google/products/search/how-we-update-search-improve-results/
https://www.seroundtable.com/category/google-updates
Twitter algorithm 2022 – 2023,
Twitter, which was founded in 2006, is still one of the world’s most popular social networking sites. As of 2020, there are over 340 million active Twitter users, with over 500 million tweets posted each day.
That’s a lot of information to sort through. And, if your company is going to utilize Twitter effectively, you must first grasp how Twitter’s timeline algorithm works and then learn the most dependable techniques of getting your information in front of your target audience.
Twitter Timeline Options: Top Tweets and Most Recent Tweets(Latest)
The Twitter Timeline may be configured to show tweets in two ways:
• Top Tweet
• Recent Tweets
These modes mays be switched by clicking the Stars icon in the upper right corner of your timeline feed.
The Most Popular Tweets
Top Tweets use an algorithm to display tweets in the order that a user is most likely to be interested in. The algorithm is based on how popular and relevant tweets are. Because of the large number of tweets sent at any given time, Twitter news feed algorithms like this one were developed to protect users from becoming overwhelmed and to keep them up to date on material that they genuinely care about.
Recent Tweets
The Latest Tweets section reorders your timeline in reverse chronological order, with the most recently Tweeted Tweets at the top. It displays tweets as they are sent in real time, so more information from more people will appear, but it will not display every tweet. The algorithm will still have some say in deciding which tweets to broadcast at the time.
Ranking Signals for the Twitter Timeline Algorithm:
The following are ranking indications for the Twitter timeline algorithm:
• How recent it is
• Use of rich media (pictures, gifs, video)
• Engagement (likes, responses, retweets)
• Author prominence
• User-author relationship
• User behavior
For example, a user is more likely to see a tweet in their timeline if it comes from a person with whom they frequently interact and has a large number of likes and responses.
What exactly are Twitter Topics?
Facebook Algorithm 2022 – 2023
Facebook can tend to feel like an uphill battle for businesses. The social media platform’s algorithm isn’t very clear about how your posts end up on users’ screens. When even the sponsored posts you’re investing in aren’t working, you know there has to be something you’re missing.
Paid or unpaid, the way you post on Facebook and reach the platform’s ever-expanding audience matters. Every time a user logs on to the website or app, Facebook is learning about what that user likes seeing and what they skip past.
The social media giant has tried a lot of different algorithms over the years, ranging from focusing on the video to simply asking users what they want to see more of. Today, things look a little different, and knowing how the Facebook algorithm works can be a game-changer for businesses.
So here’s what you need to know about Facebook’s Algorithm in 2021:
Facebook is concerned with three things when its algorithm learns about user activity and begins curating their feed to these behaviors.
Following these three elements to a great post can mean huge things for your engagement and reach on Facebook. Ignoring them ends up in things like these terrible Facebook ads we wish we never saw.
First up, the accounts with which the user interacts matter. If someone is always checking up on certain friends and family members, then that’s going to mean their posts will show up sooner on their feed.
The same goes for organizations and businesses that users interact with the most. That means it’s your job to post content that encourages users to not only follow and like you but also provide users the type of content that drives engagement.
What sort of posts do best on Facebook?
Users all have their own preferences for what they like to see. At the end of the day, a mix of videos, links to blogs and web pages, and photos are good to keep things diverse and dynamic.
That said, the sort of posts that do best on your business account will depend on the final element of the Facebook algorithm that matters most: user interactions.
From sharing a post to simply giving it a like or reaction, interactions matter most when it comes to the Facebook algorithm. The social media platform wants users active and logging in as often as possible. That’s why their machine learning algorithm sees interactions as a huge plus for your account.
Comments matter too! In fact, comments serve a dual purpose for your business account on Facebook. Not only do comments drive interactions on your page, but they also give you direct feedback from the audience.
If you listen to comments and take your user’s feedback seriously, you can avoid posting content that ends up falling flat. That doesn’t just hurt your reach and engagement but it’s also a blunder on your digital brand.
Can you beat the Facebook Algorithm once and for all?
We don’t like putting negative energy into the universe, but the Facebook algorithm is sort of like a villain you need to take down to achieve your goals as a business. Understanding the Facebook algorithm can feel like a battle sometimes.
How Does Amazon’s Search Algorithm Work to Find the Right Products?
The search algorithm of Amazon is sophisticated and has a key goal. It aims to connect online shoppers with the products they are looking for as soon as possible. If you reach the top of the Search Pages, your brand visibility will improve, and sales will go up.
Not an essay but here’s a summary:
Based on a Vickrey-Clarke-Groves (VCG) auction.
Total Value = Bid*(eCTR*eCVR)+Value (info)
This creates an oCPM environment (info)
The core of this according to the auction and engineering team has more or less been the same for years.
2018/2020 are different issues. The former affecting (mostly) those who don’t understand oCPM as FB prioritizes user experience and the latter causing issues for those still relying on attribution instead of lift (info).
Audio recognition software like Shazam – how does the algorithm work?
Have a read through this mate http://coding-geek.com/how-shazam-works/
It identifies the songs by creating a audio fingerprint by using a spectrogram. When a song is being played ,shazam creates an audio fingerprint of that song (provided the noise is not high) ,and then checks if it matches with the millions of other audio fingerprints in its database, if it finds a match it sends the info. Here is a really good blog : https://www.toptal.com/algorithms/shazam-it-music-processing-fingerprinting-and-recognition
How does the PALS algorithm in 2022 actually work?
What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?
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- In C, how can I efficiently Write to multiple files based on name?by /u/uu3s (Algorithm) on October 7, 2023 at 12:10 am
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- How do I multiplying big numbers, using Karatsuba's method?by /u/uu3s (Algorithm) on October 7, 2023 at 12:08 am
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- How to test whether 2 languages are equal, when given in algebraic form?by /u/vv3st (Algorithm) on September 29, 2023 at 11:50 pm
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- How to find an st-path in a planar graph, which is adjacent to the fewest number of faces?by /u/vv3st (Algorithm) on September 29, 2023 at 11:50 pm
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- Please answer my questions on 2-chordless cycle extraction, from a failed comparability graph recognition?by /u/vv3st (Algorithm) on September 29, 2023 at 11:49 pm
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- Is it possible to boost the error probability of a Consensus protocol, over dynamic network?by /u/vv3st (Algorithm) on September 29, 2023 at 11:48 pm
submitted by /u/vv3st [link] [comments]
- How to incorporate custom Algorithm in SOLR-LUCENE, before Indexing?by /u/vv3st (Algorithm) on September 29, 2023 at 11:47 pm
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- Just some advance ai algorithmby Algorithm on June 27, 2023 at 2:57 am
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- Agglomerative Hierarchical Clustering complexityby /u/CompteDeMonteChristo (Algorithm) on April 11, 2023 at 4:19 pm
I wrote an algorithm for Agglomerative Hierarchical Clustering General agglomerative clustering methods have a time complexity of O(N³) and a memory complexity of O(N²) due to the need to calculate and recalculate full pairwise distance matrices. I'd like to calculate the complexity for it. The algorithm running on random data is empirically 60 times faster on 1000 points, 200 faster with 2000 points and 500 times faster with 3000 points. It is clearly not O(N³) I'd like to calculate or estimate the complexity of it. Could someone help me on this? You can test and get the source on this page: https://preview.redd.it/2bv8hmqj6ata1.png?width=1170&format=png&auto=webp&s=c213b338ae524f38fd3e0be9e38258d04b2b2bcc https://ganaye.com/ahc/?numberOfPoints=3000&wantedClusters=6&linkage=avg&canvasSize=500 submitted by /u/CompteDeMonteChristo [link] [comments]
- Finding Clique idsby /u/239847293847 (Algorithm) on August 31, 2020 at 2:06 pm
Hello I have the following problem: I have a few million tuples of the form (id1, id2). If I have the tuple (id1, id2) and (id2, id3), then of course id1, id2 and id3 are all in the same group, despite that the tuple (id1, id3) is missing. I do want to create an algorithm where I get a list of (id, groupid) tuples as a result. How do I do that fast? I've already implemented an algorithm, but it is way too slow, and it works the following (simplified): 1) increment groupid 2) move first element of the tuplelist into the toprocess-set 3) move first element of the toprocess-set into the processed set with the current groupid 4) find all elements in the tuplelist that are connected to that element and move them to the toprocess-set 5) if the toprocess-set isn't empty go back to 3 6) if the tuplelist is not empty go back to 1 submitted by /u/239847293847 [link] [comments]
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List of Freely available programming books - What is the single most influential book every Programmers should read
- Bjarne Stroustrup - The C++ Programming Language
- Brian W. Kernighan, Rob Pike - The Practice of Programming
- Donald Knuth - The Art of Computer Programming
- Ellen Ullman - Close to the Machine
- Ellis Horowitz - Fundamentals of Computer Algorithms
- Eric Raymond - The Art of Unix Programming
- Gerald M. Weinberg - The Psychology of Computer Programming
- James Gosling - The Java Programming Language
- Joel Spolsky - The Best Software Writing I
- Keith Curtis - After the Software Wars
- Richard M. Stallman - Free Software, Free Society
- Richard P. Gabriel - Patterns of Software
- Richard P. Gabriel - Innovation Happens Elsewhere
- Code Complete (2nd edition) by Steve McConnell
- The Pragmatic Programmer
- Structure and Interpretation of Computer Programs
- The C Programming Language by Kernighan and Ritchie
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
- Design Patterns by the Gang of Four
- Refactoring: Improving the Design of Existing Code
- The Mythical Man Month
- The Art of Computer Programming by Donald Knuth
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
- Gödel, Escher, Bach by Douglas Hofstadter
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- Effective C++
- More Effective C++
- CODE by Charles Petzold
- Programming Pearls by Jon Bentley
- Working Effectively with Legacy Code by Michael C. Feathers
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel
- Surely You're Joking, Mr. Feynman!
- Effective Java 2nd edition
- Patterns of Enterprise Application Architecture by Martin Fowler
- The Little Schemer
- The Seasoned Schemer
- Why's (Poignant) Guide to Ruby
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
- The Art of Unix Programming
- Test-Driven Development: By Example by Kent Beck
- Practices of an Agile Developer
- Don't Make Me Think
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
- Domain Driven Designs by Eric Evans
- The Design of Everyday Things by Donald Norman
- Modern C++ Design by Andrei Alexandrescu
- Best Software Writing I by Joel Spolsky
- The Practice of Programming by Kernighan and Pike
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
- Software Estimation: Demystifying the Black Art by Steve McConnel
- The Passionate Programmer (My Job Went To India) by Chad Fowler
- Hackers: Heroes of the Computer Revolution
- Algorithms + Data Structures = Programs
- Writing Solid Code
- JavaScript - The Good Parts
- Getting Real by 37 Signals
- Foundations of Programming by Karl Seguin
- Computer Graphics: Principles and Practice in C (2nd Edition)
- Thinking in Java by Bruce Eckel
- The Elements of Computing Systems
- Refactoring to Patterns by Joshua Kerievsky
- Modern Operating Systems by Andrew S. Tanenbaum
- The Annotated Turing
- Things That Make Us Smart by Donald Norman
- The Timeless Way of Building by Christopher Alexander
- The Deadline: A Novel About Project Management by Tom DeMarco
- The C++ Programming Language (3rd edition) by Stroustrup
- Patterns of Enterprise Application Architecture
- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
- Object Thinking by Dr. David West
- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
- The Timeless Way of Building by Christopher Alexander
- Design Patterns in C# by Steve Metsker
- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
- Effective Java by Joshua Bloch
- Computability by N. J. Cutland
- Masterminds of Programming
- The Tao Te Ching
- The Productive Programmer
- The Art of Deception by Kevin Mitnick
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
- Masters of Doom
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
- How To Solve It by George Polya
- The Alchemist by Paulo Coelho
- Smalltalk-80: The Language and its Implementation
- Writing Secure Code (2nd Edition) by Michael Howard
- Introduction to Functional Programming by Philip Wadler and Richard Bird
- No Bugs! by David Thielen
- Rework by Jason Freid and DHH
- JUnit in Action
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- Experimental ovarian cryopreservation could delay menopause, but experts are weighing the risksby /u/scientificamerican on April 22, 2024 at 1:50 pm
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- Man who spent 13 years in a coma woke up to tell incredible storyby /u/Maxcactus on April 22, 2024 at 10:54 am
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- Toxic: How the search for the origins of COVID-19 turned politically poisonousby /u/zsreport on April 22, 2024 at 10:29 am
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- A cheap drug may slow down aging. A study will determine if it worksby /u/Maxcactus on April 22, 2024 at 10:12 am
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- How the way you walk can tell you how well you’ll sleep tonightby /u/EmphasisCheap8611 on April 22, 2024 at 9:54 am
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Today I Learned (TIL) You learn something new every day; what did you learn today? Submit interesting and specific facts about something that you just found out here.
- TIL Brazil turned Pelé into a national treasure to stop him from leaving the country to play soccer in Europeby /u/Humblerequest_21 on April 22, 2024 at 2:13 pm
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- TIL In 2014, a 15-year-old teenager injected himself with mercury, hoping to gain superpowers like the X-Men. He mimicked Wolverine's transformation, but it ended in disaster. He nearly lost his life and realized superpowers are just fiction.by /u/y442_Ficul1983 on April 22, 2024 at 2:10 pm
submitted by /u/y442_Ficul1983 [link] [comments]
- TIL there's an annual lying contest in England called "The World's Biggest Liar." Held in Cumbria, contestants vie to tell the most convincing lie within 5 minutes. Politicians and lawyers are barred from participating due to their reputed skill in deception.by /u/MelissaJonesenNc on April 22, 2024 at 1:31 pm
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- TIL In 1984 "Baby Fae" received a baboon heart transplant at just 11 days old and survived 21 days before rejecting it.by /u/andersonfmly on April 22, 2024 at 1:07 pm
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- TIL that a version of the Golden Rule can be found on ancient Egyptian papyrus from the Egyptian late period, which states "That which you hate to be done to you, do not do to another."by /u/Desperate_Dirt_3041 on April 22, 2024 at 1:05 pm
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Reddit Science This community is a place to share and discuss new scientific research. Read about the latest advances in astronomy, biology, medicine, physics, social science, and more. Find and submit new publications and popular science coverage of current research.
- Block-based Programming for Two-Armed Robots: A Comparative Studyby /u/davidshepherd on April 22, 2024 at 3:36 pm
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- Pluto’s heart-shaped Sputnik Planitia basin might not hide an ocean after allby /u/Science_News on April 22, 2024 at 3:25 pm
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- The Neolithic revolution, the wide-scale transition to agriculture among at least seven unconnected hunter-gatherer populations, was enabled by climactic changes. Increased climatic seasonality caused hunter-gatherers to adopt a sedentary lifestyle and store food for the season of scarcity.by /u/smurfyjenkins on April 22, 2024 at 2:40 pm
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- As adults get older, they shift their perception of when old age starts. This according to a survey on 14,056 middle-aged and older adults who responses to the question: “At what age would you describe someone as old” for 8 times over a 25Y periodby /u/giuliomagnifico on April 22, 2024 at 2:25 pm
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- A study examining outcomes of a 2021 clinical trial that found psilocybin effectively treated major depressive disorder linked a stronger relationship between study participants & clinicians to lower depression scores 1 year later-pointing to the importance of the therapeutic alliance.by /u/memorialmonorail on April 22, 2024 at 2:17 pm
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Reddit Sports Sports News and Highlights from the NFL, NBA, NHL, MLB, MLS, and leagues around the world.
- Jose Mourinho: How I changed football in 20 years - and why I'm not done yetby /u/kundu123 on April 22, 2024 at 3:20 pm
Between-jobs Jose has always been different to in-work Jose. Much less stressed, bursting with ideas and watching a lot of football on television. submitted by /u/kundu123 [link] [comments]
- A racial slur and a Fort Myers High baseball team torn apartby /u/PrincessBananas85 on April 22, 2024 at 2:38 pm
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- Scottie Scheffler finishes off another win at Hilton Head to extend dominant runby /u/Oldtimer_2 on April 22, 2024 at 1:31 pm
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- Fred Weis on Joel Embiid: “Take away his nationality and ban him from entering France”by /u/kundu123 on April 22, 2024 at 12:48 pm
As Weis said: “I consider this boy a great player as much as he is a dirty guy. I hate him for the things that he did. I think he doesn’t have any respect for France and also for all the people who are asking for a French passport and don’t get it. And under the pretext that he is a great athlete, he got it. I find it scandalous, I find it embarrassing. I don’t care about his excuses, cause they are his words, and his words mean nothing”. submitted by /u/kundu123 [link] [comments]
- Ethiopian distance runner and Olympic finalist Zerfe Wondemagegn banned 5 years for dopingby /u/Oldtimer_2 on April 22, 2024 at 12:09 pm
submitted by /u/Oldtimer_2 [link] [comments]
