Category: algorithm

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What is the difference between a heuristic and a machine learning algorithm?

What is the difference between a heuristic and a machine learning algorithm?

What is the difference between a heuristic and a machine learning algorithm?

Machine learning algorithms and heuristics can often be mistaken for each other, but there are distinct differences between the two. Machine learning algorithms seek to replicate processes and patterns previously used to solve various types of problems and can remember these processes for future problem solving. Heuristics, on the other hand, are creative approaches that attempt to solve problems with novel solutions. An algorithm pre-defined by programmers relies on structured data such as numerical values, while a heuristic requires verbal instructions from users such as expressions or conditions that describe an ideal solution. Machine learning algorithms and heuristics both offer useful approaches to problem solving, but it’s important to understand the difference in order to properly apply them.

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A heuristic is a type of problem-solving approach that involves using practical, trial-and-error methods to find solutions to problems. Heuristics are often used when it is not possible to use a more formal, systematic approach to solve a problem, and they can be useful for finding approximate solutions or identifying patterns in data.

A machine learning algorithm, on the other hand, is a type of computer program that is designed to learn from data and improve its performance over time. Machine learning algorithms use statistical techniques to analyze data and make predictions or decisions based on that analysis.

There are several key differences between heuristics and machine learning algorithms:

  1. Purpose: Heuristics are often used to find approximate or suboptimal solutions to problems, while machine learning algorithms are used to make accurate predictions or decisions based on data.

  2. Data: Heuristics do not typically involve the use of data, while machine learning algorithms rely on data to learn and improve their performance.

  3. Learning: Heuristics do not involve learning or improving over time, while machine learning algorithms are designed to learn and adapt based on the data they are given.

  4. Complexity: Heuristics are often simpler and faster than machine learning algorithms, but they may not be as accurate or reliable. Machine learning algorithms can be more complex and time-consuming, but they may be more accurate and reliable as a result.

Overall, heuristics and machine learning algorithms are different approaches to solving problems and making decisions. Heuristics are often used for approximate or suboptimal solutions, while machine learning algorithms are used for more accurate and reliable predictions and decisions based on data.

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What is machine learning and how does Netflix use it for its recommendation engine?

What is machine learning and how does Netflix use it for its recommendation engine?

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.

2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams
2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams

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.

What is machine learning and how does Netflix use it for its recommendation engine?
What is machine learning and how does Netflix use it for its recommendation engine?

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:

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.

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What are the top 10 algorithms every software engineer should know by heart?

What is the single most influential book every Programmers should read

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.

What are the top 10 algorithms every software engineer should know by heart?
QuickSort Algorithm Implementation with Python method1

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.

Binary search with python

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 True

Driver Program to test above function

print(“true”) if isPrime(11) else print(“false”)
print(“true”) if isPrime(14) else print(“false”)

This code is contributed by Smitha Dinesh Semwal

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.

O(n) Rotational Cipher in Python
O(n) Rotational Cipher

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:

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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.

What are the top 10 algorithms every software engineer should know by heart?
QuickSort Algorithm Implementation with Python method1

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

2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams
2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams


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

The historical past of the Instagram Algorithm

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!

Using “Write Path Classifiers” Instagram analyzed Your Posts till 2019.

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.


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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!

How The New Algorithm Works!

The new algorithm uses 3 Crucial ways to source content for Your Instagram Explore feed!

1. Calculation of Engagement

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.

2. Content Sourcing for Explore Page

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.

3. Ranking Step 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.

4. Sensitivity Control

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.

5 Instagram Hashtags Algorithm Doesn’t Exist

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.

What I learned about Stories Algorithm

“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!

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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!

The New Reels Algorithm

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

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Tiktok algorithm 2022 – 2023,

  1. 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

  1. The very first video plays a huge role in your future. -Quality content -Unique but similar to your niche

  • 9-15 seconds maximum!!

  1. After upload, wait about a few hours, before your second video

  2. 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

  1. Your videos needs to be captivating or strange, this way users spends more time on it.

  2. 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.

  1. 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

  1. 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

  1. 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)

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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.

Post image

Twitter

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?

Read more

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?

https://www.palsprograms.org/

What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?

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What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?

What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?

What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?

Machine Learning and Artificial Intelligence are changing Algorithmic Trading. Algorithmic trading is the use of computer programs to make trading decisions in the financial markets. These programs are based on a set of rules that take into account a variety of factors, including market conditions and the behavior of other traders. In recent years, machine learning and artificial intelligence have begun to play a role in algorithmic trading. Here’s a look at how these cutting-edge technologies are changing the landscape of stock market trading.

What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?
What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?

Machine Learning in Algorithmic Trading

Machine learning is a type of artificial intelligence that allows computer programs to learn from data and improve their performance over time. This technology is well-suited for algorithmic trading because it can help programs to better identify trading opportunities and make more accurate predictions about future market movements.

One way that machine learning is being used in algorithmic trading is through the development of so-called “predictive models.” These models are designed to analyze past data (such as prices, volumes, and order types) in order to identify patterns that could be used to predict future market movements. By using predictive models, algorithmic trading systems can become more accurate over time, which can lead to improved profits.

How Does Machine Learning Fit into Algorithmic Trading?

Machine learning algorithms can be used to automatically generate trading signals. These signals can then be fed into an execution engine that will automatically place trades on your behalf. The beauty of using machine learning for algorithmic trading is that it can help you find patterns in data that would be impossible for humans to find. For example, you might use machine learning to detect small changes in the price of a stock that are not apparent to the naked eye but could indicate a potential buying or selling opportunity.

Artificial Intelligence in Algorithmic Trading

Image

Artificial intelligence (AI) is another cutting-edge technology that is beginning to have an impact on algorithmic trading. AI systems are able to learn and evolve over time, just like humans do. This makes them well-suited for tasks such as identifying patterns in data and making predictions about future market movements. AI systems can also be used to develop “virtual assistants” for traders. These assistants can help with tasks such as monitoring the markets, executing trades, and managing risk.

According to Martha Stokes, Algorithmic Trading will continue to expand on the Professional Side of the market, in particular for these Market Participant Groups:

Buy Side Institutions, aka Dark Pools. Although the Buy Side is also going to continue to use the trading floor and proprietary desk traders, even outsourcing some of their trading needs, algorithms are an integral part of their advance order types which can have as many as 10 legs (different types of trading instruments across multiple Financial Markets all tied to one primary order) the algorithms aid in managing these extremely complex orders.

Sell Side Institutions, aka Banks, Financial Services. Banks actually do the trading for corporate buybacks, which appear to be continuing even into 2020. Trillions of corporate dollars have been spent (often heavy borrowing by corporations to do buybacks) in the past few years, but the appetite for buybacks doesn’t appear to be abating yet. Algorithms aid in triggering price to move the stock upward. Buybacks are used to create speculation and rising stock values.

High Frequency Trading Firms (HFTs) are heavily into algorithms and will continue to be on the cutting edge of this technology, creating advancements that other market participants will adopt later.

Hedge Funds also use algorithms, especially for contrarian trading and investments.

Corporations do not actually do their own buybacks; they defer this task to their bank of record.

Professional Trading Firms that offer trading services to the Dark Pools are increasing their usage of algorithms.

Smaller Funds Groups use algorithms less and tend to invest similarly to the retail side.

The advancements in Artificial Intelligence (AI), Machine Learning, and Dark Data Mining are all contributing to the increased use of algorithmic trading.

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Computer programs that automatically make trading decisions use mathematical models and statistical analysis to make predictions about the future direction of prices. Machine learning and artificial intelligence can be used to improve the accuracy of these predictions.

1. Using machine learning for stock market prediction: Machine learning algorithms can be used to predict the future direction of prices. These predictions can be used to make buy or sell decisions in an automated fashion.

2. Improving the accuracy of predictions: The accuracy of predictions made by algorithmic trading programs can be improved by using more data points and more sophisticated machine learning algorithms.

3. Automating decision-making: Once predictions have been made, algorithmic trading programs can automatically make buy or sell decisions based on those predictions. This eliminates the need for human intervention and allows trades to be made quickly and efficiently.

4. Reducing costs: Automated algorithmic trading can help reduce transaction costs by making trades quickly and efficiently. This is because there are no delays caused by human decision-making processes.

Leveraging Artificial Intelligence To Build Algorithmic Trading Strategies

To conclude:

Machine learning and artificial intelligence are two cutting-edge technologies that are beginning to have an impact on algorithmic trading. By using these technologies, traders can develop more accurate predictive models and virtual assistants to help with tasks such as monitoring the markets and executing trades. In the future, we can expect machine learning and AI to play an even greater role in stock market trading. If you are interested in using machine learning and AI for algorithmic trading, we recommend that you consult with a professional who has experience in this area.

CAVEAT by Ross:

Can artificial intelligence or machine learning predict the future of the stock market?

Can it predict?

Yes, to a certain extent. And let’s be honest, all you care about is that it predicts it in such a way you can extract profit out of your AI/ML model.

Ultimately, people drive the stock market. Even the models they build, no matter how fancy they build their AI/ML models..


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And people in general are stupid, and make stupid mistakes. This will always account for “weird behavior” on pricing of stocks and other financial derivatives. Therefore the search of being able to explain “what drives the stock market” is futile beyond the extend of simple macro economic indicators. The economy does well. Profits go up, fellas buy stocks and this will be priced in the asset. Economy goes through the shitter, firms will do bad, people sell their stocks and as a result the price will reflect a lower value.

The drive for predicting markets should be based on profits, not as academia suggests “logic”. Look back at all the idiots who drove businesses in the ground the last 20/30 years. They will account for noise in your information. The focus on this should receive much more information. The field of behavioral finance is very interesting and unfortunately there isn’t much literature/books in this field (except work by Kahneman).

Best and worst performing currencies in 2022. Russian Ruble is number one – Russian Stock Market Today

r/economy - Best and worst performing currencies in 2022. Russian Ruble is numba one.

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What are the top 100 Free IQ Test Questions and Answers – Train and Elevate Your Brain

Free IQ Test Questions and Answers - Train Your Brain

What are the top 100 Free IQ Test Questions and Answers – Train and Elevate Your Brain

An Intelligence Quotient or “IQ” is a score derived from one of several standardized tests designed to assess human intelligence. The term “IQ” was coined by William Stern in 1912 as a proposed method of scoring children’s performance on the new Binet-Simon intelligence scale.

Ever since, there has been much debate over what exactly IQ tests measure, how accurate and reliable they are, and what purpose they serve. However, there is no denying that IQ scores can have major implications for an individual’s life chances, including their educational opportunities and career prospects.

Mensa IQ Test Master Creates IQ test questions from uploaded images, offers feedback, and converses.

IQ tests are often used for selecting students for gifted and talented programs or for entrance into schools for the intellectually gifted. They may also be used to identify individuals who are at risk of developmental delays or learning disabilities. In some cases, IQ scores are used to predict job performance or to screen job applicants.

  1. The first Mensa IQ test is called the Culture Fair Intelligence Test, or CFIT. This test is designed to minimize the influence of cultural biases on a person’s score. The CFIT is made up of four subtests, each of which measures a different type of cognitive ability.
  2. The second Mensa IQ test is called the Stanford-Binet Intelligence Scale, or SBIS. The SBIS is a revision of an earlier intelligence test that was used by the US military to screen recruits during World War I. Today, the SBIS is commonly used to diagnose learning disabilities in children.
  3. The third Mensa IQ test is called the Universal Nonverbal Intelligence Test, or UNIT. As its name suggests, the UNIT is a nonverbal intelligence test that can be administered to people of all ages, regardless of their native language.
  4. The fourth and final Mensa IQ test is called the Wright Scale of Human Ability, or WSHA. The WSHA was developed by William Herschel Wright, a British psychologist who also served as the first president of Mensa International. Like the other tests on this list, the WSHA consists of four subtests that measure different aspects of cognitive ability.

Below are the top 100 Free IQ Test Questions and Answers From Mensa:

What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
What are the top 100 Free IQ Test Questions and Answers – Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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Test your IQ
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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What are the top 100 Free IQ Test Questions and Answers - Train and Elevate Your Brain
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IQ Test Mensa

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IQ Test Question Asked by Mensa
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Mensa IQ Test Question Example
Mensa IQ Test Question Example

What do IQ Tests Measure?
Broadly speaking, IQ tests measure an individual’s capacity for logical reasoning, problem-solving, and abstract thought. They usually involve a mixture of verbal and nonverbal questions and tasks. Standardized IQ tests often yield a bell-shaped distribution of scores with a mean of 100 and a standard deviation of 15. This means that the vast majority of people score between 85 and 115. Scores below 70 are generally considered to represent intellectual disability, while scores above 130 are considered to represent exceptional intelligence.

How Accurate and Reliable are IQ Tests?
The accuracy and reliability of IQ tests have long been debated by researchers and psychologists. Some argue that IQ tests are an unfair measure of intelligence because they often favor those with higher socioeconomic status or who speak English as their first language. Others argue that the test items on IQ tests often tap into culturally biased knowledge, such as knowledge of famous people or classical music.

IQ tests also tend to yield lower scores for certain groups, including women, ethnic minorities, and people from lower socio-economic backgrounds. This has led some to suggest that IQ tests may be biased against certain groups. However, it is important to keep in mind that all standardized tests have some degree of bias built into them. For example, a test designed to assess knowledge of American history will necessarily be biased against people from other countries who have not had the same exposure to American history. This does not mean that the test is invalid or unreliable; it simply means that the test is not measuring something that is equally important for everyone in the world.

Conclusion:

There is no denying that IQ scores can have major implications for an individual’s life chances, including their educational opportunities and career prospects. However, there is still much debate over what exactly IQ tests measure and how accurate and reliable they are. Because of this debate, it is important to consider IQ scores within the context of other factors when making decisions about someone’s ability or potential.

There are four main Mensa IQ tests: the Culture Fair Intelligence Test (CFIT), the Stanford-Binet Intelligence Scale (SBIS), the Universal Nonverbal Intelligence Test (UNIT), and the Wright Scale of Human Ability (WSHA). Each test assesses different aspects of cognitive ability, and all four tests are used to screen candidates for membership in Mensa International, an organization for people with high intelligence quotients. Thanks for reading!

What would be an example of an IQ question that only someone with an IQ of 135+ could answer?

The questions in the online tests seems to be more difficult close to the end. The question below is the last question in the online test from Mensa Norge that claims to measure up to IQ 145. Thus, the last question should only be possible to solve for people close to IQ 145, or that knows the logic of the question.

Case for D: The first column has all the lines not present in the 2nd and 3rd columns. Hence the answer must have the sides, but not the top and bottom lines. D is the only choice that has that.

The answer is D, there alway 4 shapes in play, you can add any of 3 and you will get 4 that’s left. When adding you need to remove lines that are not unique and leave only unique. To find the answer you need to shift everything to the left so first row will be last row and do same patern. Below is how it looks like and what elements are in same group. I marked same lines with the same colors that you eliminate and basically left with unique lines that are black. Add shapes in brown rectangle to get shape in dark red rectangle, but you may switch them and add 2 brown and one red to get the other brown, in other words adding any 3 you will get last 4th.

Case for C: if you analize it from a vertical point of view , the first figure and last figure always have the same number of sides(2and2; 4and4; 3and3) , if you analize it horizontally there is a pattern , first you have 2 sides , then 4 sides and then 3 sides, on the other one you have 4 sides , then 3 sides and then 4 sides and in the last one you have 2 sides and then 4 sides , so you will logically think that if on vertical perspective the first figure always has the same number of sides than the third figure (vertically), on the horizontal perspective the last group of figures must have the same amount of sides than the first group of figures(2,4 and 3 sides respectively )so if the correct answer is C the first group of figures that has this number of sides :2 sides ,4 sides and 3 sides; will have the same number of sides than the third sequence of figures :2,4, and 3 sides(horizontally).

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I also got C, but by counting the total number of exposed sides for each row.

Row 1 gives (8+6+4) = 18

Row 2 gives (8 + 6 + 8) = 22

Row 3 gives (4 + 16 + x) = 26 (as 18, 22, 26 is an arithmetic sequence with a common difference) (shape b is 16 due to lines being cut in half)

So x (exposed sides) must equal 6, giving C as the only option

Do high IQ people find it hard to understand easy concepts somehow?

High IQ friend of mine: Makes a very high 6 figure salary coding

Also him: Doesn’t know how to open a milk carton

(The carton didn’t have the ‘lift n peel’ thing, it was plain transparent blue plastic)

He’s super smart, but the thing with the milk carton is that he’s not used to this kind of problem.


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The solution is to look where to apply force and how to apply it.

But the kind of solution he’s used to making is: Find a way to make this super complicated massive piece of code work again.

Physical world problem vs hard logical problem (that you only ever envision in your head)

Another thing might be that he’s so used to complicated problems perhaps he thought there was more to it.

Or maybe he just never saw it before (but even then it’s not hard to figure out)

What are the most effective ways to improve emotional intelligence?

Emotional intelligence is about the ability to control, Recognize, express your emotions, and handle your interpersonal connections with empathy and sensibility. There are many ways to improve emotional intelligence such as.

  1. Increasing Self-Awareness
  2. Observing your feeling
  3. Pay attention to your behaviour
  4. Question your opinions
  5. Look at yourself objectively
  6. Know your emotional triggers
  7. Understand the links between people’s emotions and behaviour
  8. Read literature to improve Empathy
  9. Try Empathize with Yourself and Others
  10. Ask for feedback
  11. Dancing, Singing, Crying, Laughter, Listening, taking care of someone or something like the elderly or a pet , plant, gardening became a hobby of mine after house plants thrived, fairy gardens, rock gardens

What is a sign of high intelligence that not many people know about?

A sign of intelligence few people know about is having a tough time understanding a question you’re being asked.

Why is that?

It’s because people with very high IQs have many meanings coming to their mind when their hear a word or a phrase.

For example, if someone asks “What do you do?” these high IQ people are likely to wonder whether they are being asked what kind of a job they do or what kind of hobbies they have, or how they would react under certain circumstances…

This need for constant precision is always present at a high IQ level, whereas for people of average IQs the most obvious and common meaning always comes to mind.

So, while not being able to understand a simple question is seen as a form of stupidity by many, it may actually be a sign of higher intelligence.

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What is a fake sign of intelligence?

 

I would say when a person feels the need to speak on every subject.

Or, just being overly talkative in general. I find that some people just like to hear themselves talk, and think that them blabbing non-stop makes them sound smart.

You generally know this is the case when they spend 20 minutes explaining something that should have only taken 30 seconds.

There were two competing awards in my high school yearbook.

  1. Talks most, says least.
  2. Talks least, says most.

It should be obvious which of those two you would want to be. There is virtue in knowing when not to talk, and just listen.

Is it possible to have a high IQ and score low on an IQ test?

I would say a person with a high IQ could have a bad day and score less than her best but it would still be far from a low score. Someone who scores low on an IQ test might have done better another day, but could never score high.

What do high IQ people think of normal IQ people?

Normal IQ people rely on the volume of ideas they can understand to arrive at their own opinions. It is much easier to evaluate an idea than it is coming up with one of equal value, as a result normal IQ people gain a significant benefit from making their opinions a collage of what they evaluated as best. This provides a series of practical advantages to the normal IQ person that no longer has to rely on his bad ideas but can supplant them for the good ones of somebody else, but also gives them a number of quirks. From the perspective of very high IQ people, normal IQ people are much more consistent performers than they are, as though their opinions in isolation are all average opinions of somebody 1.5 SD above them, but have a set of opinions that looks like the monstrous chimera of someone with multiple personalities. If an high IQ person has a standard distribution of quality for his opinions ranging around his IQ, the normal IQ person has a much smaller range of opinions all of higher quality than average but patched together in such a way as to appear incomprehensible how one could champion them all. This is the main reason of the communication range, we expect your opinions to have implications for your other opinions that quite simply aren’t there. From the perspective of high IQ people normal IQ people constantly try to have their cake and eat it too.

Which professions/fields of study can a person with an IQ between 130 and 140 (but average drive) be successful in? Which should he stay away from?

 

You will probably get an answer from one of the usual suspects posting his favorite career-to-IQ chart, which omits so much crucial data that it can only be surmised that those who promote usage of it are doing so to manipulate opinion.

The graphic I’m going to post under this text is much better because it shows a range of IQs that actual people doing actual jobs have. From it you can see that some janitors have the same IQ as some doctors. So you should seek a career in doing whatever you would like to do. You are much more likely to succeed in something you want to do than something you don’t want to do, regardless of your IQ.

 

Is there a connection between high IQ and low spatial intelligence?

Not necessarily. While there is some positive correlation with high spatial intelligence (the standard IQ test includes a number of questions related to spatial intelligence), it is far from absolute. My mother is quite likely the smartest person currently living in New York City and has virtually zero spatial intelligence. Conversely, there are loadmasters and packing experts who have unbelievable spatial intelligence but only average IQs.

 

Albert Einstein is gone, and Stephen Hawking is gone. Who is the next genius?

If we had to pick an existing genius who has a gravitational impact on any research project he (or she) touches, I would venture a guess that a lot of people would pick Terence Tao (mathematician), an Australian mathematician working out of UCLA. Not only has he been a prolific theorist, he also been a major public figure and communicator of math. He is considered an once in a generation type of talent and we won’t truly fully realize his impact for another few decades once people start applying his findings. That said, his work on compressed sensing is already having implications on sensor theory.

 

How difficult is the Mensa test?

Mensa Singapore uses the Raven’s Advanced Progressive Matrices (RAPM). I sat for the test around a year-and-a-half ago and was accepted into Mensa.

Each question consisted of a 3-by-3 matrix of some black-and-white figures with an underlying pattern. The space at the bottom left corner was blank and I had to choose one out of eight options to complete the pattern. Here’s a picture I found on Google which illustrates the question format:

Since the RAPM tests only non-verbal reasoning ability, you do not need to have any content knowledge to do the questions. However, you do need to have a good working memory, as we were not allowed to make any markings on the diagrams in the question paper.

I remember finishing the test 20 minutes early. There was only one particular question towards the end which I found difficult.

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All in all, it’s nothing to worry about; I’m sure that even a sharp 12-year-old could do the test!

What is the difference between people with IQ 145 and people with an IQ of 190?

 

The usual caveat first, IQ is problematic and widely misunderstood. Almost everyone you ever meet has an IQ between about 80–120. Including the big CEOs and billionaires, politicians and teachers, leaders and successful people in general.

An IQ of 144 or so are borderline being too smart to actually function in society. They’re the serious nerds, the high functioning autistics, and can be the real problem solvers – if they are given a chance and not overlooked because they are socially inept or don’t think about the same things everyone around them does. They might have trouble just keeping a job or a relationship, or getting one that recognizes their intelligence and finds a way to put them to use.

This is already your crème de la crème, the top 1/6th of 1% or so. Honors students at national research universities, National Merit Scholars, and people whose college admissions were more competitive than Mensa, etc.

An IQ of 190 doesn’t practically exist. The occasional rare genius might get labelled with a number this high, but it’s meaningless at this point. This is the territory of DaVinci, Copernicus, Curie, Galileo, Einstein, Aquinas, etc.

What is the most interesting IQ study ever done?

In 1969, UCLA psychologist Dr. Robert Rosenthal did an IQ experiment.

He met with two grade-school teachers. He gave them a list of names from their new student body (20% of the class). He said that each person on that list had taken a special test and would emerge as highly intelligent within the next 12 months.

In reality, those students were chosen totally at random. As a group, they were of average intelligence.

The incredible finding is that, when they tested those children near the end of the year, each demonstrated significant increases in their IQ scores.

So what happened? Why?

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The teacher’s own behavior towards those students affected the outcomes.

They gave the fake-talented students more attention. When one raised their hand to answer a question, the teacher often followed up to get better clarification. The teachers were more positive and encouraging to those students.

Meanwhile, the teacher was much shorter with students they deemed subpar. Rosenthal speculated the teacher figured the student might be dumb, so why go the extra mile?

Dr. Rosenthal said, “When we expect certain behaviors of others, we are likely to act in ways that make the expected behavior more likely to occur.”

The opposite of the Pygmalion effect is the Golem Effect; it occurs when our negative expectations generate negative results. This is partly why internalizing stereotypes is damaging.

What can we learn from these effects? Two things.

The first thing

The children in Rosenthal’s study began to internalize the belief that they were special. They bought into the idea, “I am smart so I can do this.”

Their self-efficacy grew and evolved and they stopped indulging in self-limiting beliefs.

The act of believing something to be true can impact every aspect of our life. For example, OK Cupid’s founder, Christian Rudder, did a Pygmalion experiment with online dating.

Researchers lied to users. They reversed the matching algorithm on a select group of singles, pairing them with people who were objectively incompatible. And told them they were high probability matches.

Because the participants believed they had chemistry, they messaged each other and began flirting. They were friendlier and gave each other a shot. Some ended up together.

And now, somewhere out there, someone is banging their nemesis.

We position ourselves to thrive by surrounding ourselves with people who believe in us and hold us to a high standard.

This is why toxic people have such a devastating effect on your life.

The second: Become your own teacher or mentor

Think about a good boss versus a bad boss.

A good boss knows how to communicate and holds you to high but reasonable expectations. They give you useful feedback rather than waiting for you to make a mistake and scold you.

A bad boss does the opposite of those things.

Being an effective mentor to yourself comes down to having a growth mindset.

Someone with a fixed mindset thinks their identity is pre-determined.

They are often self-defeating.

“What’s the point. I’m stupid.”

“I’m too lazy to get in shape.”

“Nobody in my family is successful so I won’t be.”

People with a growth mindset dismiss these things. They are persistent.

They choose to march forward and keep fighting. They stay defiant in the face of difficult odds. They don’t seek out reasons they can’t win.

And they are often the most successful people in the world.

The good news? The fact that you are here reading this self-help article suggests you are likely of a growth mindset.

The takeaway is simple

  • Surround yourself with great people who hold you to a high but reasonable standard.
  • Treat yourself like another person who you are responsible for. Treat yourself like that student who is talented.
  • Have the courage to believe in yourself even if nobody else does. Become a prophet of your own success.

For a person with an IQ of 140, is speaking to normal people (IQ 100) comparable to how normal people feel when speaking to someone w/ an IQ of 60?

Not even close. It doesn’t work that way.

A person with an intelligence quotient of 60 can barely function and complete everyday mundane tasks like using a smartphone to access Quora.

An IQ of 60 is found at the opposite end of 140 on the intelligence spectrum and is present in less than 1% of the population.

There are plenty of average IQ individuals that are well studied, well-spoken and quite interesting.

That said, filling your head with a plethora of information and factoids doesn’t make you knowledgeable. “Knowing” comes in degrees and varieties of quality and there’s quite a hop forward between “smart” and “brilliant.”

The major difference between normies and people in the high IQ range considered gifted/genius is their capacity to think. Not ability but, capacity. There’s a difference…

Your ability to think is more of a philosophical matter and intellectual skill—at least, fundamentally. You can be taught how to think by an intelligent and wise person. And hey, if you ever find such an opportunity, take it, because very few people walking around are privileged with this type of mentorship.

That said, the brain of a genius still has it easier when it comes to the ability to think as well. For instance, I didn’t need a PhD to develop the same ability for thought as say, your college professor.

The fundamental ability is innate. I was born with it and my capacity for it is greater.

Still, the major difference is capacity.

Chances are, if you find yourself listening to, or talking to someone with profound insight and, well, brilliant ideas, that person is likely in that top 1%.

But on both sides of that interaction, there’s a give and take that is enjoyable for both parties.

A normie trying to converse and partake in an exchange of ideas with the unfortunate soul that has a 60 IQ wouldn’t be much of an interaction. It would be pretty one sided.

A normie and a 140 plus is game on and pretty fun—especially if the normie is educated and smart.

What math, physics, or logic problems can I solve to make some quick prize money?

The Coin Toss Problem

Here’s the puzzle/problem:

Let’s presume we are best friends. I live in the house next to you. I make a gaming proposition along the following lines:

You throw a coin over and over again. So long as it comes up heads, you keep throwing. When it comes up tails you stop and I pay you $$$ — depending on how many heads you threw.

If you threw a tails to start, you get $0.
If you threw a heads then a tails, you get $1.
If you threw 2 heads then a tails, you get $2.
If you threw 3 heads, you get $4.
If you threw 4 heads, you get $8.
If you threw 5 heads, you get $16.
And on and on. The payoff doubles every time you add an extra heads.

Since this game consists entirely of me giving you money (from $0 to $??) — you will have to buy an “entry” —

How much will you pay me to play this game? — *Once.*

If you can solve this problem (and it has a solution) — you are well on your way to an early retirement.

This puzzle came up at the Physics Department Christmas Party at Stanford University in 1984.* I was the first to solve it. It took me about 24hours of passive playful pondering. I was 23.

But you were asking about money? Ok, I retired at age 33, only 37 months after I began work. Coincidence?? — Not entirely. (That story is here.)

This is a *difficult* puzzle.
Hopefully you will understand it.
Hopefully it will inspire you.

By w.w. Lenzo

Solution hints to Coin Toss Problem:

AFTER 765 DAYS: the question has been viewed 20,000 times inspiring only 71 answer attempts. We have SIX CORRECT RESPONSES! (see below)

Fifty-two answers were just guesses from people who clearly did not understand the problem. One person ran a test, collecting data. Only nineteen came from people who could perceive the infinity hidden within the puzzle — so let’s imagine they have an IQ>130.

Eleven of those nineteen made an effort to crack the paradox and six have so far done so correctly.

First Prize Goes To —
* * * Peter Barnett! * * *
* * * Nat Han! * * *
* * * Davide Checchia! * * *
* * * Io Scapula! * * *
* * * Angus Sullivan! * * *
* * * Erik Rådbo! * * *

The Turning Cards Problem:

I have a stack of 100 index cards. On each card is written a unique number. Each number can be positive or negative, whole or fractional, rational or irrational (like pi). Each number is real and unique.

These cards are placed in a huge bag and tumbled around until they are thoroughly randomized. Your job is to find the card with the highest number on it. The challenge is: You are only allowed to look at the cards one at a time. You must toss away the card in your hand before you can draw another card from the sack. In order to win you must say “stop!” at exactly the moment you are holding the highest card. You can never go back to an earlier card.

What is your optimum strategy?
What chance does that strategy give you to win this game?
What would your chance be if the stack had 1 million unique cards?

Finally (as though that weren’t enough) — suppose there were 1 million cards, but the winning condition is now to find either the highest card -or- the 2nd-highest card. How does that change your tactics? What now is your chance to win?

Clue: the answer to the last question is you have a 58% chance to end up with one of the two highest cards in a deck of 1 million cards!! (if you use optimal technique). Wow!!

Now, if that doesn’t inspire you, you’re not really alive to what’s going on here.

This second question/puzzle is interesting because it models a real-world problem that we face all the time — coming-to-terms with an unknown situation and making effective choices.

  • How do we finally settle on a husband or wife?
  • How do we choose which house to buy?
  • How to pick a career? Or a philosophy?

Remember: 58% is possible on a million cards!! — Now think!! —

AFTER 650 DAYS: this question has been studied (approx) 24,000 times inspiring only 10 answer attempts. We have TWO ANSWERS which are 95% CORRECT!!—

First Prize (Almost) Goes To —
* * * Zijin Cui * * * — a college student —
* * * Bernard Cook * * * — an anesthesiologist —
Woo! Hoo! — Congratulations!!

Zijin solved the problem using good intuition and an unusual statistical approach. Yes, this is a stats problem disguising itself as a math puzzle.

Bernard solved my harder 58%-version by fearlessly applying combinatorics and Stirling’s approximation to zero-in on the correct answer. He took the bull by the horns and deftly flipped it belly-up. Kudos!!

Nonetheless, I am still hoping for somebody to solve both problems in closed-form (for an arbitrary number of cards).

Since nobody seems able, I will give a huge hint:

You have to use all the obvious variables PLUS you must invent a non-obvious variable to create an expression for the probability of winning. The calculation requires solving a double integral. One of these integrations is across the non-obvious variable, which then disappears entirely from the calculation & the solution.

Haselbauer-Dickheiser Test

This test is known as the Haselbauer-Dickheiser test for exceptional intelligence.

The question source is: The Most Difficult IQ Test in the World

 
 
 
 
 
 
 
 
 
 
 
 
A D G H F B E C
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Source of 25 above images: The Most Difficult IQ Test in the World

Some possible answers:

  1. October 2018 – Dimitrios Kalemis
  2. November 2018 – Dimitrios Kalemis
  3. December 2018 – Dimitrios Kalemis
  4. January 2019 – Dimitrios Kalemis
  5. Sources: http://matrix67.com/iqtest/
 

BONUS QUESTION

Really stretch the ol’ brain a bit, loosen the cobwebs:

  • What is existence made of, at the smallest scale?

Mathematic/Arithmetic Problems:

17
 

What is ‘epicness’ in artistic mediums?

“A feeling of ‘epicness’ occurs when someone who has been habituated to perceive a piece of art at one scale suddenly must perceive that piece of art at a different scale, and realizes that they had the option to perceive it in that way the entire time. ‘Scale’ refers to effective size of interactions; for example: ‘nano’, ‘human’, or ‘planetary’ scales.” Given this is true, explain how the concept of “sometimes what you were looking for was right under your nose the whole time” can result in a feeling of ‘epicness’. Describe a situation where that concept would not result in a feeling of epicness. Describe an addition to that situation that makes it feel epic. By Elliott Kelley (IQ: 190)https://www.quora.com/profile/Elliott-Kelley

 

How do geniuses and people with high IQ (above 180) solve problems in real life and very hard questions in an IQ test?

A few traits of the profoundly gifted include divergent thinking (different ways of considering the problem and its possible solutions–think back to spontaneous challenges in Odyssey of the Mind from grade school), thinking in analogies such that information is interconnected (so, math and music and sociology concepts may be linked in memory), and projection into the problem (such that someone literally is walking through a mental representation of the problem as if he/she were the problem). Complex material is quite simple because of these traits, but simple problems become a bit of an overload, as the question-makers aren’t anticipating interconnection of material or divergent solutions. Combining multiple steps into a single step is also common (holistic learning).

This allows profoundly gifted individuals to intuit solutions to material they may not explicitly know or have seen before (such as math included on the SAT taken prior to junior high). For references on this, see here: https://www.slideshare.net/ColleenFarrelly/understanding-the-profoundly-gifted

As an example, take a writer who is imaging a scene with several characters. She might close her eyes and imagine the scene involving those characters and then imagine herself as that particular character. Doing this for each step of the scene allows her to intuit how each character would respond to the situation and to each other, along with allowing her to mentally visualize the scene unfolding. In this manner, she simply records what she sees in her mind’s eye.

 

What is a person with IQ between 150 & 160 like?

I’m going to go anonymous on this because I don’t usually talk about my IQ to anyone.

  • Finding meaningful conversation is seriously hard since I feel that people don’t always understand what I’m saying unless they happen to be an expert on said subject.
  • Thus, I find it hard to symphatize with other people since their worldview is vastly different.
  • I have been clinically depressed when I was younger since I couldn’t adapt to norms.
  • I have never cared and never will care about societal norms.
  • I’m social and have huge social circles but only few friends.
  • School was never hard for me but I never got great grades since I got bored and lazy about school. It never gave me anything new or exiting to research.
  • I often got in trouble at school for talking against teachers because I knew they were wrong and got offended when corrected.
  • I have always absolutely loved all science and I’m fascinated about almost any subject you can humanly think of.
  • I hate people who feel superior solely based on their IQ. Critical thinking, expertise and hard work will earn my respect, not your IQ. This is why I’m not part of Mensa.
  • I would really like to meet someone with substantially higher IQ than mine.
  • When people challenge in constructive way and argument their points very well I feel like I’m in heaven. It’s truly great though rare.
  • Short fuse has always been my problem and I’m learning to control it.
  • I despise irrational thinking.
  • But love facts.
  • Find it funny when people try to “teach” me things that aren’t true or at least largely untrue as facts.
  • I’m blunt and don’t usually sugarcoat things.
  • I find dating extremely hard since I get easily bored (my current partner is an exception to this rule).

Bottom line is that I try to get by and help people as much as I can and be understanding. Slowing down for others is often frustrating but I feel like I’m getting so much out of this that I wouldn’t trade my life for anyone else. By the Author

Who has the highest recorded IQ of all time?

Top 10 highest recorded IQs of all time

10. Stephen Hawking IQ-154

9. Albert Einstein IQ 160–190

8. Judit Polgar IQ-170

7. Leonardo Da Vinci IQ 180–190

6. Richard Rosner IQ-192

5. Gary Kasparov IQ-194

4. Kim Ung Yong IQ-210

3. Christopher Hirata IQ-225

2. Terence Tao IQ 225–230

1.William James Sidis IQ 250–300

In 1899, at age one, Sidis could already confidently read The New York Times by himself. At age eight, he was fluent in eight different languages (Armenian, French, German, Greek, Hebrew, Latin, Russian and Turkish) and had invented one for himself called ‘Vendergood’.

Sidis set the world record in 1909 for the youngest enrolment in Harvard University—he was 11 years old—studying advanced mathematics.

Yet Sidis’ memories of this time were far from happy. His biographer, Amy Wallace, claimed that,

“He had been made a laughing stock [. . .] he admitted he had never kissed a girl. He was teased and chased [. . .] and all he wanted was to be away from academia [and] be a regular working man.” [1]

 

If that wasn’t already enough, news reporters frequently followed Sidis around campus, seeking to sensationalise his story.

It is considered that Sidis’ IQ fell somewhere between 250 and 300 (Einstein’s IQ was estimated at 160). [2]

After graduating Harvard at 16, Sidis worked a brief stint as a mathematics professor at Rice University (Houston, TX). He resigned shortly after, however, because he was harassed by journalists everywhere he went. He claimed,

“I want to live a perfect life. The only way to live a perfect life is to live in isolation.” [3]

 

And that he did. Following his resignation, Sidis went into hiding, moving from city to city, working minimum wage jobs to earn his keep. During this time, he wrote a vast number of books in subjects ranging from modern history to mathematics.

In 1919, he was arrested for his coordination of a number of communist rallies and sentenced to 18 months in prison. After his release from prison, he isolated himself in his apartment in Boston. He was determined to finally live an independent and private life, becoming estranged from his own parents in the process.

It was there that he lived out the rest of his days. Isolated and, for the most part, completely alone until his death in 1944.

It seems all Sidis ever wanted was to lead a ‘normal life’. And he was, most certainly, cursed with one incredibly remarkable mind.

Edit: I think it’s absolutely hilarious you guys have all this information worth contesting about this guy, and all you care about is the brief mention of “communist rallies”.

Footnotes

[1] Meet William James Sidis: The Smartest Guy Ever?
[2] Full text of “Psychology For The Millions”
[3] The sad story of the smartest man who ever lived – William James Sidis

Reference: Mensa Norway

IQ Q&A:

How will the world look like when AI GPT models reach 1600 IQ?

Mo Gawdat, former Chief Business Officer of Google [X] predicts that AI will evolve from this year’s 155 IQ to 1600 IQ within the next decade.

Gawdat describes that this will be equal to the relative difference between Einstein’s IQ to of a fly.

What kind of problems do you think AI will be able to solve then? How will humans decode or translate the results?

Some notable comments:

Things will be similar to industrial revolution, first the society will disrupt(average human economic value will fall) and revolution or war will come. Than, we will have a new historic era. New economic approaches new type of working, education and social structure.

Industrial revolution happened 1760 – 1840 => https://www.britannica.com/summary/Industrial-Revolution-Timeline

and first war started 1914 (fast economic transformation triggered total war).

And lets look when computer revolution started: 1971

https://en.wikipedia.org/wiki/History_of_personal_computers

when it enters the workspace and start doing your job, we can call it economically revolutional. So, we are expecting till 2040’s nearly all of jobs right now will be useless, and it already started:

https://www.forbes.com/sites/brianbushard/2023/07/11/will-ai-take-your-job-27-of-jobs-in-wealthy-countries-at-high-risk-report-says/?sh=7b9f15641113

By looking the history, when society economically disrupted we see big crisis than war. Now, our economy is not doing great, for young person its impossible to buy a home by just working at job. This will definitely cause economic crisis and war in the end. So, things already started, 2024 will be awful year economically i believe. And after next year or inside 2024? Good luck everybody

What are some extremely difficult genius level (160+) IQ questions?

Genius-level IQ is typically considered to be 160 or above. Questions for individuals at this level would likely involve complex problem-solving, advanced mathematical concepts, pattern recognition, and critical thinking. Here are some types of questions that might be challenging:

1. Advanced Pattern Recognition:

Identify the next figure in a complex sequence, or determine the underlying rule of a series of shapes, numbers, or symbols.

2. Cryptic Crossword Puzzles:

These require a deep understanding of the language, wordplay, cultural references, and the ability to think outside the box.

3. Abstract Logical Puzzles:

Solve puzzles that require advanced logic and the ability to see multiple steps ahead, similar to high-level chess problems.

4. Mathematical Problem Solving:

Solve complex mathematical problems that require a deep understanding of various mathematical concepts and theories.

5. Memory Challenges:

Remember long strings of numbers, letters, or symbols, and then manipulate or recall them in specific ways.

6. Spatial Visualization:

Visualize complex three-dimensional shapes in your mind and solve problems related to them.

7. Philosophical and Theoretical Questions:

Engage with deep philosophical questions that require critical thinking, extensive knowledge, and the ability to articulate and defend a position.

8. Creative Problem-Solving:

Generate innovative solutions to complex problems that may not have a single correct answer.

What are some extremely difficult genius level (160+) IQ questions?
What are some extremely difficult genius level (160+) IQ questions?

How do intelligent people recognize each other?

You can see it in a person’s eyes where they stand mentally. If you don’t believe me, go to a pre-school (ages 4-5) with average kids and speak to one. Look them in the eye. Then go to a pre-school for gifted kids and look them in the eye. You can see it within, that there is something… “more”. You can see their effortless focus and attention on you, and you feel that they are “there” listening and processing what you’re doing, saying, etc. It’s as if you can see their little gears effortlessly turning away, figuring you out. It never goes away and stays with them throughout their life. They may be able to hide it, but it’s there if you look.

Young ones haven’t learned to hide it yet, and most don’t even realize they have it, but you can see it, plain as day and night.

If you’re interested in learning more about the secret signs of intellectual brilliance and how intelligent individuals identify each other, check out this fascinating article: The Secret Signs of Intellectual Brilliance: How Intelligent Individuals Identify Each Other. It delves deeper into the unique qualities and behaviors that set intellectually gifted individuals apart from the average population.

Is the difference between IQ 190 and 130 as big as between 130 and 70?

Are IQ tests just a matter of thinking fast? Could a person with an IQ of 110-125 perform like somebody in the 130-160 with extra time?

Is the Sigma test the hardest IQ test? The last problem is finally solved. People with an IQ between 180-200 could never solve it.

Can a 130 IQ correctly answer a question from a 160+ IQ test?

Is it okay if I assert myself as “smarter than everyone else in the room” if my IQ is 126?

What are some things only a person with 160 IQ+ could solve within a reasonable amount of time?

What can a person with an IQ of 160 do that a person with an IQ of 100 cannot? Are certain things fundamentally unlearnable/undoable like IQ claims? How can this be overcome?

How does a person with an IQ of 170+ think?

What would be an example of an IQ question that only someone with an IQ of 135+ could answer?

What are the most difficult IQ questions?

What is a person with IQ between 150 & 160 like?

Do you think 140-160 IQs are mostly where “average geniuses” and polymaths are?

How much different between a person with IQ 180 vs IQ 90 in their way of thinking? Please provide some example

Can you solve this IQ-test question? -168 IQ requires

aptilink iq test

What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market

AI Revolution in October 2023: The Latest Innovations Reshaping the Tech Landscape

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 How to find common elements in two unsorted arrays with sizes n and m avoiding double for loop?

How to find common elements in two unsorted arrays with sizes n and m avoiding double for loop? Blog Introduction: In this blog post, we will be discussing how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We will be discussing various methods that can be used to solve this problem and comparing the time complexity of each method. Blog Body: Method 1: Linear Search The first method we will discuss is linear search. This method involves iterating through both arrays and comparing each element. If the element is found in both arrays, it is added to the result array. The time complexity of this method is O(nm), where n is the size of the first array and m is the size of the second array. Method 2: HashMap Method The second method we will discuss is the HashMap method. This method involves creating a HashMap of all the elements in the first array. Then, we iterate through the second array and check if the elements are present in the HashMap. If they are, we add them to the result array. The time complexity of this method is O(n+m), where n is the size of the first array and m is the size of the second array. Method 3: Sort andCompare Method The third method we will discuss is the Sort and Compare Method. This method involves sorting both arrays using any sorting algorithm like merge sort or quick sort. Once both arrays are sorted, we compare each element of both arrays one by one until we find a match. If a match is found, we add it to our result array. The time complexity of this method is O(nlogn+mlogm), where n is the size of the first array and m is the size of the second array. Conclusion: In this blog post, we discussed how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We discussed three different methods that can be used to solve this problem and compared their time complexities. We hope that this blog post was helpful in understanding how to solve this problem.

How to find common elements in two unsorted arrays with sizes n and m avoiding double for loop?

Programmers, software engineers, coders, IT professionals, and software architects all face the common challenge of needing to find common elements in two unsorted arrays with sizes n and m. This can be a difficult task, especially if you don’t want to use a double for loop.

In this blog post, we will be discussing how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We will be discussing various methods that can be used to solve this problem and comparing the time complexity of each method.

There are several ways that you can find common elements in two unsorted arrays with sizes n and m avoiding double for loop. One way is by using the hashing technique. With this technique, you can create a hash table for one of the arrays. Then, you can traverse through the second array and check if the element is present in the hash table or not. If the element is present in the hash table, then it is a common element. Another way that you can find common elements in two unsorted arrays with sizes n and m avoiding double for loop is by using the sorting technique. With this technique, you can sort both of the arrays first. Then, you can traverse through both of the arrays simultaneously and compare the elements. If the elements are equal, then it is a common element.

Method 1: Linear Search

The first method we will discuss is linear search. This method involves iterating through both arrays and comparing each element. If the element is found in both arrays, it is added to the result array. The time complexity of this method is O(nm), where n is the size of the first array and m is the size of the second array.

Method 2: HashMap Method

The second method we will discuss is the HashMap method. This method involves creating a HashMap of all the elements in the first array. Then, we iterate through the second array and check if the elements are present in the HashMap. If they are, we add them to the result array. The time complexity of this method is O(n+m), where n is the size of the first array and m is the size of the second array.

Method 3: Sort and Compare Method

The third method we will discuss is the Sort and Compare Method. This method involves sorting both arrays using any sorting algorithm like merge sort or quick sort. Once both arrays are sorted, we compare each element of both arrays one by one until we find a match. If a match is found, we add it to our result array. The time complexity of this method is O(nlogn+mlogm), where n is the size of the first array and m is the size of the second array.

The naïve algorithm for finding common elements in two unsorted arrays with sizes nn and mm is O(nm)O(nm), i.e. quadratic.

The algorithm for sorting an array is O(nlogn)O(nlog⁡n), and you can find common elements in two sorted arrays in O(n+m)O(n+m). In other words, for large enough arrays, it is significantly faster to first sort them, then look for the common elements, because the sorting algorithm will dominate the complexity, so your final algorithm ends up at O(nlogn)O(nlog⁡n) as well.

How to find common elements in two unsorted arrays with sizes n and m avoiding double for loop?
One of the most straight forward ways to find common elements in two arrays is by using a double for loop. This approach is simple to understand and implement but it is not very efficient. The time complexity of this algorithm is O(n*m) where n and m are the size of the two arrays respectively. The reason for this is because we are looping through both arrays completely which takes a lot of time. Furthermore, this approach also uses a lot of extra space because we are storing the common elements in a new list.

Conclusion:

In this blog post, we discussed how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We discussed three different methods that can be used to solve this problem and compared their time complexities. We hope that this blog post was helpful in understanding how to solve this problem.

There are many different ways to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. The most straight forward way is by using a double for loop but this approach is not very efficient. A more efficient way is by using a hash table which has a time complexity of O(n+m). This algorithm is faster because we only need to loop through one of the arrays. We can then use the values from that array to check if there are any duplicates in the second array. This approach also uses less memory because we are not creating a new list to store the common elements.

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What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions

AWS Certified Cloud Practitioner Exam Preparation

What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions

AWS certifications are becoming increasingly popular as the demand for AWS-skilled workers continues to grow. AWS certifications show that an individual has the necessary skills to work with AWS technologies, which can be beneficial for both job seekers and employers. AWS-certified individuals can often command higher salaries and are more likely to be hired for AWS-related positions. So, what are the top 10 AWS jobs that you can get with an AWS certification?

1. AWS Solutions Architect / Cloud Architect:

AWS solutions architects are responsible for designing, implementing, and managing AWS solutions. They work closely with other teams to ensure that AWS solutions are designed and implemented correctly.

AWS Architects, AWS Cloud Architects, and AWS solutions architects spend their time architecting, building, and maintaining highly available, cost-efficient, and scalable AWS cloud environments. They also make recommendations regarding AWS toolsets and keep up with the latest in cloud computing.

Professional AWS cloud architects deliver technical architectures and lead implementation efforts, ensuring new technologies are successfully integrated into customer environments. This role works directly with customers and engineers, providing both technical leadership and an interface with client-side stakeholders.

What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions
AWS SAA-C02 SAA-C03 Exam Prep

Average yearly salary: $148,000-$158,000 USD

2. AWS SysOps Administrator / Cloud System Administrators:

AWS sysops administrators are responsible for managing and operating AWS systems. They work closely with AWS developers to ensure that systems are running smoothly and efficiently.

A Cloud Systems Administrator, or AWS SysOps administrator, is responsible for the effective provisioning, installation/configuration, operation, and maintenance of virtual systems, software, and related infrastructures. They also maintain analytics software and build dashboards for reporting.

Average yearly salary: $97,000-$107,000 USD

3. AWS DevOps Engineer:

AWS devops engineers are responsible for designing and implementing automated processes for Amazon Web Services. They work closely with other teams to ensure that processes are efficient and effective.

AWS DevOps engineers design AWS cloud solutions that impact and improve the business. They also perform server maintenance and implement any debugging or patching that may be necessary. Among other DevOps things!

Average yearly salary: $118,000-$138,000 USD

What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions
AWS Developer Associate DVA-C01 Exam Prep

4. AWS Cloud Engineer:

AWS cloud engineers are responsible for designing, implementing, and managing cloud-based solutions using AWS technologies. They work closely with other teams to ensure that solutions are designed and implemented correctly.

5. AWS Network Engineer:

AWS network engineers are responsible for designing, implementing, and managing networking solutions using AWS technologies. They work closely with other teams to ensure that networking solutions are designed and implemented correctly.

Cloud network specialists, engineers, and architects help organizations successfully design, build, and maintain cloud-native and hybrid networking infrastructures, including integrating existing networks with AWS cloud resources.

Ace the 2024 AWS Certified Machine Learning Specialty Exam with Flying Colors

AI- Powered Jobs Interview Warmup For Job Seekers

Average yearly salary: $107,000-$127,000 USD

6. AWS Security Engineer:

AWS security engineers are responsible for ensuring the security of Amazon Web Services environments. They work closely with other teams to identify security risks and implement controls to mitigate those risks.

Cloud security engineers provide security for AWS systems, protect sensitive and confidential data, and ensure regulatory compliance by designing and implementing security controls according to the latest security best practices.

Average yearly salary: $132,000-$152,000 USD

What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions
AWS Certified Security Specialty

7. AWS Database administrator:

As a database administrator on Amazon Web Services (AWS), you’ll be responsible for setting up, maintaining, and securing databases hosted on the Amazon cloud platform. You’ll work closely with other teams to ensure that databases are properly configured and secured.

8. Cloud Support Engineer:

Support engineers are responsible for providing technical support to AWS customers. They work closely with customers to troubleshoot problems and provide resolution within agreed upon SLAs.

9. Sales Engineer:

Sales engineers are responsible for working with sales teams to generate new business opportunities through the use of AWS products and services .They must have a deep understanding of AWS products and how they can be used by potential customers to solve their business problems .

10. Cloud Developer

An AWS Developer builds software services and enterprise-level applications. Generally, previous experience working as a software developer and a working knowledge of the most common cloud orchestration tools is required to get and succeed at an AWS cloud developer job

Average yearly salary: $132,000 USD


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11. Cloud Consultant

Cloud consultants provide organizations with technical expertise and strategy in designing and deploying AWS cloud solutions or in consulting on specific issues such as performance, security, or data migration.

Average yearly salary: $104,000-$124,000

12. Cloud Data Architect

Cloud data architects and data engineers may be cloud database administrators or data analytics professionals who know how to leverage AWS database resources, technologies, and services to unlock the value of enterprise data.

Average yearly salary: $130,000-$140,000 USD

What are the Top 10 AWS jobs you can get with an AWS certification in 2022 plus AWS Interview Questions
AWS Data analytics DAS-C01 Exam Prep

Getting a job after getting an AWS certification

The field of cloud computing will continue to grow and even more different types of jobs will surface in the future.

AWS certified professionals are in high demand across a variety of industries. AWS certs can open the door to a number of AWS jobs, including cloud engineer, solutions architect, and DevOps engineer.

Through studying and practice, any of the listed jobs could becoming available to you if you pass your AWS certification exams. Educating yourself on AWS concepts plays a key role in furthering your career and receiving not only a higher salary, but a more engaging position.

Source: 8 AWS jobs you can get with an AWS certification

AWS Tech Jobs  Interview Questions in 2022

Graphs

1) Process Ordering – LeetCode link…

2) Number of Islands – LeetCode link…

3) k Jumps on Grid – Loading…)

Sort

1) Finding Prefix in Dictionary – LeetCode Link…

Tree

1) Binary Tree Top Down View – LeetCode link…

2) Traversing binary tree in an outward manner.

3) Diameter of a binary tree [Path is needed] – Diameter of a Binary Tree – GeeksforGeeks

Sliding window

1) Contains Duplicates III – LeetCode link…

2) Minimum Window Substring [Variation of this question] – LeetCode link..

Linked List

1) Reverse a Linked List II – LeetCode link…

2) Remove Loop From Linked List – Remove Loop in Linked List

3) Reverse a Linked List in k-groups – LeetCode link…

Binary Search

1) Search In rotate sorted Array – LeetCode link…

Solution:

def pivotedBinarySearch(arr, n, key):
 
    pivot = findPivot(arr, 0, n-1)
 
    # If we didn't find a pivot,
    # then array is not rotated at all
    if pivot == -1:
        return binarySearch(arr, 0, n-1, key)
 
    # If we found a pivot, then first
    # compare with pivot and then
    # search in two subarrays around pivot
    if arr[pivot] == key:
        return pivot
    if arr[0] <= key:
        return binarySearch(arr, 0, pivot-1, key)
    return binarySearch(arr, pivot + 1, n-1, key)
 
 
# Function to get pivot. For array
# 3, 4, 5, 6, 1, 2 it returns 3
# (index of 6)
def findPivot(arr, low, high):
 
    # base cases
    if high < low:
        return -1
    if high == low:
        return low
 
    # low + (high - low)/2;
    mid = int((low + high)/2)
 
    if mid < high and arr[mid] > arr[mid + 1]:
        return mid
    if mid > low and arr[mid] < arr[mid - 1]:
        return (mid-1)
    if arr[low] >= arr[mid]:
        return findPivot(arr, low, mid-1)
    return findPivot(arr, mid + 1, high)
 
# Standard Binary Search function
def binarySearch(arr, low, high, key):
 
    if high < low:
        return -1
 
    # low + (high - low)/2;
    mid = int((low + high)/2)
 
    if key == arr[mid]:
        return mid
    if key > arr[mid]:
        return binarySearch(arr, (mid + 1), high,
                            key)
    return binarySearch(arr, low, (mid - 1), key)
 
# Driver program to check above functions
# Let us search 3 in below array
if __name__ == '__main__':
    arr1 = [5, 6, 7, 8, 9, 10, 1, 2, 3]
    n = len(arr1)
    key = 3
    print("Index of the element is : ", \
          pivotedBinarySearch(arr1, n, key))
 
# This is contributed by Smitha Dinesh Semwal

Arrays

1) Max bandWidth [Priority Queue, Sorting] – Loading…

2) Next permutation – Loading…

3) Largest Rectangle in Histogram – Loading…

Content by – Sandeep Kumar

#AWS #interviews #leetcode #questions #array #sorting #queue #loop #tree #graphs #amazon #sde —-#interviewpreparation #coding #computerscience #softwareengineer

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What is the single most influential book every Programmers should read

There are a lot of books that can be influential to programmers. But, what is the one book that every programmer should read? This is a question that has been asked by many, and it is still up for debate. However, there are some great contenders for this title. In this blog post, we will discuss three possible books that could be called the most influential book for programmers. So, what are you waiting for? Keep reading to find out more!

What is the single most influential book every Programmers should read
What is the single most influential book every Programmers should read

Source: Wikipedia

What is the single most influential book every Programmers should read
Popular Programming Languages

What are the concepts every Java C# C++ Python Rust programmer must know?

 

Ok…I think this is one of the most important questions to answer. According to the my personal experience as a Programmer, I would say you must learn following 5 universal core concepts of programming to become a successful Java programmer.

(1) Mastering the fundamentals of Java programming Language – This is the most important skill that you must learn to become successful java programmer. You must master the fundamentals of the language, specially the areas like OOP, Collections, Generics, Concurrency, I/O, Stings, Exception handling, Inner Classes and JVM architecture.

Recommended readings are OCA Java SE 8 Programmer by by Kathy Sierra and Bert Bates (First read Head First Java if you are a new comer ) and Effective Java by Joshua Bloch.

(2) Data Structures and Algorithms – Programming languages are basically just a tool to solve problems. Problems generally has data to process on to make some decisions and we have to build a procedure to solve that specific problem domain. In any real life complexity of the problem domain and the data we have to handle would be very large. That’s why it is essential to knowing basic data structures like Arrays, Linked Lists, Stacks, Queues, Trees, Heap, Dictionaries ,Hash Tables and Graphs and also basic algorithms like Searching, Sorting, Hashing, Graph algorithms, Greedy algorithms and Dynamic Programming.

Recommended readings are Data Structures & Algorithms in Java by Robert Lafore (Beginner) , Algorithms Robert Sedgewick (intermediate) and Introduction to Algorithms-MIT press by CLRS (Advanced).

(3) Design Patterns – Design patterns are general reusable solution to a commonly occurring problem within a given context in software design and they are absolutely crucial as hard core Java Programmer. If you don’t use design patterns you will write much more code, it will be buggy and hard to understand and refactor, not to mention untestable and they are really great way for communicating your intent very quickly with other programmers.

Recommended readings are Head First Design Patterns Elisabeth Freeman and Kathy Sierra and Design Patterns: Elements of Reusable by Gang of four.

(4) Programming Best Practices – Programming is not only about learning and writing code. Code readability is a universal subject in the world of computer programming. It helps standardize products and help reduce future maintenance cost. Best practices helps you, as a programmer to think differently and improves problem solving attitude within you. A simple program can be written in many ways if given to multiple developers. Thus the need to best practices come into picture and every programmer must aware about these things.

Recommended readings are Clean Code by Robert Cecil Martin and Code Complete by Steve McConnell.

(5) Testing and Debugging (T&D) – As you know about the writing the code for specific problem domain, you have to learn how to test that code snippet and debug it when it is needed. Some programmers skip their unit testing or other testing methodology part and leave it to QA guys. That will lead to delivering 80% bugs hiding in your code to the QA team and reduce the productivity and risking and pushing your project boundaries to failure. When a miss behavior or bug occurred within your code when the testing phase. It is essential to know about the debugging techniques to identify that bug and its root cause.

Recommended readings are Debugging by David Agans and A Friendly Introduction to Software Testing by Bill Laboon.

I hope these instructions will help you to become a successful Java Programmer. Here i am explain only the universal core concepts that you must learn as successful programmer. I am not mentioning any technologies that Java programmer must know such as Spring, Hibernate, Micro-Servicers and Build tools, because that can be change according to the problem domain or environment that you are currently working on…..Happy Coding!

Ace the 2024 AWS Certified Machine Learning Specialty Exam with Flying Colors

AI- Powered Jobs Interview Warmup For Job Seekers

By Aravinda Meewalaarachchi

Summary: There’s no doubt that books have had a profound influence on society and the advancement of human knowledge. But which book is the most influential for programmers? Some might say it’s The Art of Computer Programming, or The Pragmatic Programmer. But I would argue that the most influential book for programmers is CODE: The Hidden Language of Computer Hardware and Software. In CODE, author Charles Petzold takes you on a journey from the basics of computer hardware to the intricate workings of software. Along the way, you learn how to write code in Assembly language, and gain an understanding of how computers work at a fundamental level. If you’re serious about becoming a programmer, then CODE should be at the top of your reading list!

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Google interview questions for various roles and How to Ace the Google Software Engineering Interview?

Google Interview Questions and Answers

Google interview questions for various roles and How to Ace the Google Software Engineering Interview?

Google is one of the most sought-after employers in the world, known for their cutting-edge technology and innovative products.

If you’re lucky enough to land an interview with Google, you can expect to be asked some challenging questions. Google is known for their brainteasers and algorithmic questions, so it’s important to brush up on your coding skills before the interview. However, Google also values creativity and out-of-the-box thinking, so don’t be afraid to think outside the box when answering questions. product managers need to be able to think strategically about Google’s products, while software engineers will need to demonstrate their technical expertise. No matter what role you’re interviewing for, remember to stay calm and confident, and you’ll be sure to ace the Google interview.

The interview process is notoriously difficult, with contenders being put through their paces with brain-teasers, algorithm questions, and intense coding challenges. However, Google interviews aren’t just designed to trip you up – they’re also an opportunity to show off your skills and demonstrate why you’re the perfect fit for the role. If you’re hoping to secure a Google career, preparation is key. Here are some top tips for acing the Google interview, whatever position you’re applying for.

Firstly, take some time to familiarize yourself with Google’s products and services. Google is such a huge company that it can be easy to get overwhelmed, but it’s important to remember that they started out as a search engine. Having a solid understanding of how Google works will give you a good foundation to build upon during the interview process. Secondly, practice your coding skills. Google interviews are notoriously difficult, and many contenders fail at the first hurdle because they’re not prepared for the level of difficulty.

The company is known for its rigorous interview process, which often includes a mix of coding, algorithm, and behavioral questions. While Google interview questions can vary depending on the role, there are some common themes that arise. For software engineering positions, candidates can expect to be asked questions about their coding skills and experience. For product manager roles, Google interviewers often focus on behavioral questions, such as how the candidate has handled difficult decisions in the past. Quantitative compensation analyst candidates may be asked math-based questions, while AdWords Associates may be asked about Google’s advertising products and policies. Google is known for being an intense place to work, so it’s important for interviewees to go into the process prepared and ready to impress. Ultimately, nailing the Google interview isn’t just about having the right answers – it’s also about having the right attitude.

Below are some of the questions asked during Google Interview for various roles:

Google interview questions for various roles and How to Ace the Google Software Engineering Interview?
Google interview questions for various roles and How to Ace the Google Software Engineering Interview?

 

Google Interview Questions: Product Marketing Manager

  • Why do you want to join Google?
  • What do you know about Google’s product and technology?
  • If you are Product Manager for Google’s Adwords, how do you plan to market this?
  • What would you say during an AdWords or AdSense product seminar?
  • Who are Google’s competitors, and how does Google compete with them?
  • Have you ever used Google’s products? Gmail?
  • What’s a creative way of marketing Google’s brand name and product?
  • If you are the product marketing manager for Google’s Gmail product, how do you plan to market it so as to achieve 100 million customers in 6 months?
  • How much money you think Google makes daily from Gmail ads?
  • Name a piece of technology you’ve read about recently. Now tell me your own creative execution for an ad for that product.
  • Say an advertiser makes $0.10 every time someone clicks on their ad. Only 20% of people who visit the site click on their ad. How many people need to visit the site for the advertiser to make $20?
  • Estimate the number of students who are college seniors, attend four-year schools, and graduate with a job in the United States every year.

Google Interview Questions: Product Manager

  • How would you boost the GMail subscription base?
  • What is the most efficient way to sort a million integers?
  • How would you re-position Google’s offerings to counteract competitive threats from Microsoft?
  • How many golf balls can fit in a school bus?
  • You are shrunk to the height of a nickel and your mass is proportionally reduced so as to maintain your original density. You are then thrown into an empty glass blender. The blades will start moving in 60 seconds. What do you do?
  • How much should you charge to wash all the windows in Seattle?
  • How would you find out if a machine’s stack grows up or down in memory?
  • Explain a database in three sentences to your eight-year-old nephew.
  • How many times a day does a clock’s hands overlap?
  • You have to get from point A to point B. You don’t know if you can get there. What would you do?
  • Imagine you have a closet full of shirts. It’s very hard to find a shirt. So what can you do to organize your shirts for easy retrieval?
  • Every man in a village of 100 married couples has cheated on his wife. Every wife in the village instantly knows when a man other than her husband has cheated, but does not know when her own husband has. The village has a law that does not allow for adultery. Any wife who can prove that her husband is unfaithful must kill him that very day. The women of the village would never disobey this law. One day, the queen of the village visits and announces that at least one husband has been unfaithful. What happens?
  • In a country in which people only want boys, every family continues to have children until they have a boy. If they have a girl, they have another child. If they have a boy, they stop. What is the proportion of boys to girls in the country?
  • If the probability of observing a car in 30 minutes on a highway is 0.95, what is the probability of observing a car in 10 minutes (assuming constant default probability)?
  • If you look at a clock and the time is 3:15, what is the angle between the hour and the minute hands? (The answer to this is not zero!)
  • Four people need to cross a rickety rope bridge to get back to their camp at night. Unfortunately, they only have one flashlight and it only has enough light left for seventeen minutes. The bridge is too dangerous to cross without a flashlight, and it’s only strong enough to support two people at any given time. Each of the campers walks at a different speed. One can cross the bridge in 1 minute, another in 2 minutes, the third in 5 minutes, and the slow poke takes 10 minutes to cross. How do the campers make it across in 17 minutes?
  • You are at a party with a friend and 10 people are present including you and the friend. your friend makes you a wager that for every person you find that has the same birthday as you, you get $1; for every person he finds that does not have the same birthday as you, he gets $2. would you accept the wager?
  • How many piano tuners are there in the entire world?
  • You have eight balls all of the same size. 7 of them weigh the same, and one of them weighs slightly more. How can you find the ball that is heavier by using a balance and only two weighings?
  • You have five pirates, ranked from 5 to 1 in descending order. The top pirate has the right to propose how 100 gold coins should be divided among them. But the others get to vote on his plan, and if fewer than half agree with him, he gets killed. How should he allocate the gold in order to maximize his share but live to enjoy it? (Hint: One pirate ends up with 98 percent of the gold.)
  • You are given 2 eggs. You have access to a 100-story building. Eggs can be very hard or very fragile means it may break if dropped from the first floor or may not even break if dropped from 100th floor. Both eggs are identical. You need to figure out the highest floor of a 100-story building an egg can be dropped without breaking. The question is how many drops you need to make. You are allowed to break 2 eggs in the process.
  • Describe a technical problem you had and how you solved it.
  • How would you design a simple search engine?
  • Design an evacuation plan for San Francisco.
  • There’s a latency problem in South Africa. Diagnose it.
  • What are three long term challenges facing Google?
  • Name three non-Google websites that you visit often and like. What do you like about the user interface and design? Choose one of the three sites and comment on what new feature or project you would work on. How would you design it?
  • If there is only one elevator in the building, how would you change the design? How about if there are only two elevators in the building?
  • How many vacuum’s are made per year in USA?

Google Interview Questions: Software Engineer

  • Why are manhole covers round?
  • What is the difference between a mutex and a semaphore? Which one would you use to protect access to an increment operation?
  • A man pushed his car to a hotel and lost his fortune. What happened?
  • Explain the significance of “dead beef”.
  • Write a C program which measures the the speed of a context switch on a UNIX/Linux system.
  • Given a function which produces a random integer in the range 1 to 5, write a function which produces a random integer in the range 1 to 7.
  • Describe the algorithm for a depth-first graph traversal.
  • Design a class library for writing card games.
  • You need to check that your friend, Bob, has your correct phone number, but you cannot ask him directly. You must write a the question on a card which and give it to Eve who will take the card to Bob and return the answer to you. What must you write on the card, besides the question, to ensure Bob can encode the message so that Eve cannot read your phone number?
  • How are cookies passed in the HTTP protocol?
  • Design the SQL database tables for a car rental database.
  • Write a regular expression which matches a email address.
  • Write a function f(a, b) which takes two character string arguments and returns a string containing only the characters found in both strings in the order of a. Write a version which is order N-squared and one which is order N.
  • You are given a the source to a application which is crashing when run. After running it 10 times in a debugger, you find it never crashes in the same place. The application is single threaded, and uses only the C standard library. What programming errors could be causing this crash? How would you test each one?
  • Explain how congestion control works in the TCP protocol.
  • In Java, what is the difference between final, finally, and finalize?
  • What is multithreaded programming? What is a deadlock?
  • Write a function (with helper functions if needed) called to Excel that takes an excel column value (A,B,C,D…AA,AB,AC,… AAA..) and returns a corresponding integer value (A=1,B=2,… AA=26..).
  • You have a stream of infinite queries (ie: real time Google search queries that people are entering). Describe how you would go about finding a good estimate of 1000 samples from this never ending set of data and then write code for it.
  • Tree search algorithms. Write BFS and DFS code, explain run time and space requirements. Modify the code to handle trees with weighted edges and loops with BFS and DFS, make the code print out path to goal state.
  • You are given a list of numbers. When you reach the end of the list you will come back to the beginning of the list (a circular list). Write the most efficient algorithm to find the minimum # in this list. Find any given # in the list. The numbers in the list are always increasing but you don’t know where the circular list begins, ie: 38, 40, 55, 89, 6, 13, 20, 23, 36.
  • Describe the data structure that is used to manage memory. (stack)
  • What’s the difference between local and global variables?
  • If you have 1 million integers, how would you sort them efficiently? (modify a specific sorting algorithm to solve this)
  • In Java, what is the difference between static, final, and const. (if you don’t know Java they will ask something similar for C or C++).
  • Talk about your class projects or work projects (pick something easy)… then describe how you could make them more efficient (in terms of algorithms).
  • Suppose you have an NxN matrix of positive and negative integers. Write some code that finds the sub-matrix with the maximum sum of its elements.
  • Write some code to reverse a string.
  • Implement division (without using the divide operator, obviously).
  • Write some code to find all permutations of the letters in a particular string.
  • What method would you use to look up a word in a dictionary?
  • Imagine you have a closet full of shirts. It’s very hard to find a shirt. So what can you do to organize your shirts for easy retrieval?
  • You have eight balls all of the same size. 7 of them weigh the same, and one of them weighs slightly more. How can you fine the ball that is heavier by using a balance and only two weighings?
  • What is the C-language command for opening a connection with a foreign host over the internet?
  • Design and describe a system/application that will most efficiently produce a report of the top 1 million Google search requests. These are the particulars: 1) You are given 12 servers to work with. They are all dual-processor machines with 4Gb of RAM, 4x400GB hard drives and networked together.(Basically, nothing more than high-end PC’s) 2) The log data has already been cleaned for you. It consists of 100 Billion log lines, broken down into 12 320 GB files of 40-byte search terms per line. 3) You can use only custom written applications or available free open-source software.
  • There is an array A[N] of N numbers. You have to compose an array Output[N] such that Output[i] will be equal to multiplication of all the elements of A[N] except A[i]. For example Output[0] will be multiplication of A[1] to A[N-1] and Output[1] will be multiplication of A[0] and from A[2] to A[N-1]. Solve it without division operator and in O(n).
  • There is a linked list of numbers of length N. N is very large and you don’t know N. You have to write a function that will return k random numbers from the list. Numbers should be completely random. Hint: 1. Use random function rand() (returns a number between 0 and 1) and irand() (return either 0 or 1) 2. It should be done in O(n).
  • Find or determine non existence of a number in a sorted list of N numbers where the numbers range over M, M>> N and N large enough to span multiple disks. Algorithm to beat O(log n) bonus points for constant time algorithm.
  • You are given a game of Tic Tac Toe. You have to write a function in which you pass the whole game and name of a player. The function will return whether the player has won the game or not. First you to decide which data structure you will use for the game. You need to tell the algorithm first and then need to write the code. Note: Some position may be blank in the game। So your data structure should consider this condition also.
  • You are given an array [a1 To an] and we have to construct another array [b1 To bn] where bi = a1*a2*…*an/ai. you are allowed to use only constant space and the time complexity is O(n). No divisions are allowed.
  • How do you put a Binary Search Tree in an array in a efficient manner. Hint :: If the node is stored at the ith position and its children are at 2i and 2i+1(I mean level order wise)Its not the most efficient way.
  • How do you find out the fifth maximum element in an Binary Search Tree in efficient manner. Note: You should not use use any extra space. i.e sorting Binary Search Tree and storing the results in an array and listing out the fifth element.
  • Given a Data Structure having first n integers and next n chars. A = i1 i2 i3 … iN c1 c2 c3 … cN.Write an in-place algorithm to rearrange the elements of the array ass A = i1 c1 i2 c2 … in cn
  • Given two sequences of items, find the items whose absolute number increases or decreases the most when comparing one sequence with the other by reading the sequence only once.
  • Given That One of the strings is very very long , and the other one could be of various sizes. Windowing will result in O(N+M) solution but could it be better? May be NlogM or even better?
  • How many lines can be drawn in a 2D plane such that they are equidistant from 3 non-collinear points?
  • Let’s say you have to construct Google maps from scratch and guide a person standing on Gateway of India (Mumbai) to India Gate(Delhi). How do you do the same?
  • Given that you have one string of length N and M small strings of length L. How do you efficiently find the occurrence of each small string in the larger one?
  • Given a binary tree, programmatically you need to prove it is a binary search tree.
  • You are given a small sorted list of numbers, and a very very long sorted list of numbers – so long that it had to be put on a disk in different blocks. How would you find those short list numbers in the bigger one?
  • Suppose you have given N companies, and we want to eventually merge them into one big company. How many ways are theres to merge?
  • Given a file of 4 billion 32-bit integers, how to find one that appears at least twice?
  • Write a program for displaying the ten most frequent words in a file such that your program should be efficient in all complexity measures.
  • Design a stack. We want to push, pop, and also, retrieve the minimum element in constant time.
  • Given a set of coin denominators, find the minimum number of coins to give a certain amount of change.
  • Given an array, i) find the longest continuous increasing subsequence. ii) find the longest increasing subsequence.
  • Suppose we have N companies, and we want to eventually merge them into one big company. How many ways are there to merge?
  • Write a function to find the middle node of a single link list.
  • Given two binary trees, write a compare function to check if they are equal or not. Being equal means that they have the same value and same structure.
  • Implement put/get methods of a fixed size cache with LRU replacement algorithm.
  • You are given with three sorted arrays ( in ascending order), you are required to find a triplet ( one element from each array) such that distance is minimum.
  • Distance is defined like this : If a[i], b[j] and c[k] are three elements then distance=max(abs(a[i]-b[j]),abs(a[i]-c[k]),abs(b[j]-c[k]))” Please give a solution in O(n) time complexity
  • How does C++ deal with constructors and deconstructors of a class and its child class?
  • Write a function that flips the bits inside a byte (either in C++ or Java). Write an algorithm that take a list of n words, and an integer m, and retrieves the mth most frequent word in that list.
  • What’s 2 to the power of 64?
  • Given that you have one string of length N and M small strings of length L. How do you efficiently find the occurrence of each small string in the larger one?
  • How do you find out the fifth maximum element in an Binary Search Tree in efficient manner.
  • Suppose we have N companies, and we want to eventually merge them into one big company. How many ways are there to merge?
  • There is linked list of millions of node and you do not know the length of it. Write a function which will return a random number from the list.
  • You need to check that your friend, Bob, has your correct phone number, but you cannot ask him directly. You must write a the question on a card which and give it to Eve who will take the card to Bob and return the answer to you. What must you write on the card, besides the question, to ensure Bob can encode the message so that Eve cannot read your phone number?
  • How long it would take to sort 1 trillion numbers? Come up with a good estimate.
  • Order the functions in order of their asymptotic performance: 1) 2^n 2) n^100 3) n! 4) n^n
  • There are some data represented by(x,y,z). Now we want to find the Kth least data. We say (x1, y1, z1) > (x2, y2, z2) when value(x1, y1, z1) > value(x2, y2, z2) where value(x,y,z) = (2^x)*(3^y)*(5^z). Now we can not get it by calculating value(x,y,z) or through other indirect calculations as lg(value(x,y,z)). How to solve it?
  • How many degrees are there in the angle between the hour and minute hands of a clock when the time is a quarter past three?
  • Given an array whose elements are sorted, return the index of a the first occurrence of a specific integer. Do this in sub-linear time. I.e. do not just go through each element searching for that element.
  • Given two linked lists, return the intersection of the two lists: i.e. return a list containing only the elements that occur in both of the input lists.
  • What’s the difference between a hashtable and a hashmap?
  • If a person dials a sequence of numbers on the telephone, what possible words/strings can be formed from the letters associated with those numbers?
  • How would you reverse the image on an n by n matrix where each pixel is represented by a bit?
  • Create a fast cached storage mechanism that, given a limitation on the amount of cache memory, will ensure that only the least recently used items are discarded when the cache memory is reached when inserting a new item. It supports 2 functions: String get(T t) and void put(String k, T t).
  • Create a cost model that allows Google to make purchasing decisions on to compare the cost of purchasing more RAM memory for their servers vs. buying more disk space.
  • Design an algorithm to play a game of Frogger and then code the solution. The object of the game is to direct a frog to avoid cars while crossing a busy road. You may represent a road lane via an array. Generalize the solution for an N-lane road.
  • What sort would you use if you had a large data set on disk and a small amount of ram to work with?
  • What sort would you use if you required tight max time bounds and wanted highly regular performance.
  • How would you store 1 million phone numbers?
  • Design a 2D dungeon crawling game. It must allow for various items in the maze – walls, objects, and computer-controlled characters. (The focus was on the class structures, and how to optimize the experience for the user as s/he travels through the dungeon.)
  • What is the size of the C structure below on a 32-bit system? On a 64-bit?

struct foo {

char a;
char* b;
};

  • A triomino is formed by joining three unit-sized squares in an L-shape. A mutilated chessboard is made up of 64 unit-sized squares arranged in an 8-by-8 square, minus the top left square.

    Design an algorithm which computes a placement of 21 triominos that covers the mutilated chessboard.2.

  • The mathematician G. H. Hardy was on his way to visit his collaborator S. Ramanujan who was in the hospital. Hardy remarked to Ramanujan that he traveled in a taxi cab with license plate 1729, which seemed a dull number. To this, Ramanujan replied that 1729 was a very interesting number – it was the smallest number expressible as the sum of cubes of two numbers in two different ways. Indeed, 10x10x10 + 9x9x9 = 12x12x12 + 1x1x1 = 1729.

    Given an arbitrary positive integer, how would you determine if it can be expressed as a sum of two cubes?

  • There are fifty coins in a line—these could be pennies, nickels, dimes, or quarters. Two players, $F$ and $S$, take turns at choosing one coin each—they can only choose from the two coins at the ends of the line. The game ends when all the coins have been picked up. The player whose coins have the higher total value wins. Each player must select a coin when it is his turn, so the game ends in fifty turns.

    If you want to ensure you do not lose, would you rather go first or second? Design an efficient algorithm for computing the maximum amount of money the first player can win.

  • You are given two sorted arrays. Design an efficient algorithm for computing the k-th smallest element in the union of the two arrays. (Keep in mind that the elements may be repeated.)

  • How do you merge two sorted linked lists”?

    It’s literally about 10 lines of code, give or take. It’s at the heart of merge sort.

    Merge 2 sorted lists in C language
    Merge 2 sorted linked lists in C language

    Reference: Here

     

 

Google Interview: Software Engineer in Test

  • Efficiently implement 3 stacks in a single array.
  • Given an array of integers which is circularly sorted, how do you find a given integer.
  • Write a program to find depth of binary search tree without using recursion.
  • Find the maximum rectangle (in terms of area) under a histogram in linear time.
  • Most phones now have full keyboards. Before there there three letters mapped to a number button. Describe how you would go about implementing spelling and word suggestions as people type.
  • Describe recursive mergesort and its runtime. Write an iterative version in C++/Java/Python.
  • How would you determine if someone has won a game of tic-tac-toe on a board of any size?
  • Given an array of numbers, replace each number with the product of all the numbers in the array except the number itself *without* using division.
  • Create a cache with fast look up that only stores the N most recently accessed items.
  • How to design a search engine? If each document contains a set of keywords, and is associated with a numeric attribute, how to build indices?
  • Given two files that has list of words (one per line), write a program to show the intersection.
  • What kind of data structure would you use to index annagrams of words? e.g. if there exists the word “top” in the database, the query for “pot” should list that.

Google Interview: Quantitative Compensation Analyst

  • What is the yearly standard deviation of a stock given the monthly standard deviation?
  • How many resumes does Google receive each year for software engineering?
  • Anywhere in the world, where would you open up a new Google office and how would you figure out compensation for all the employees at this new office?
  • What is the probability of breaking a stick into 3 pieces and forming a triangle?

Google Interview: Engineering Manager

  • You’re the captain of a pirate ship, and your crew gets to vote on how the gold is divided up. If fewer than half of the pirates agree with you, you die. How do you recommend apportioning the gold in such a way that you get a good share of the booty, but still survive?

Google Interview: AdWords Associate

  • How would you work with an advertiser who was not seeing the benefits of the AdWords relationship due to poor conversions?
  • How would you deal with an angry or frustrated advertisers on the phone?

Sources

To conclude:

Google is one of the most sought-after employers in the tech industry. The company is known for its rigorous interview process, which often includes a mix of coding, algorithm, and behavioural questions. While Google interview questions can vary depending on the role, there are some common themes that arise. For software engineering positions, candidates can expect to be asked questions about their coding skills and experience. For product manager roles, Google interviewers often focus on behavioral questions, such as how the candidate has handled difficult decisions in the past. Quantitative compensation analyst candidates may be asked math-based questions, while AdWords Associates may be asked about Google’s advertising products and policies. Google is known for being an intense place to work, so it’s important for interviewees to go into the process prepared and ready to impress. Ultimately, nailing the Google interview isn’t just about having the right answers – it’s also about having the right attitude.

Is “cracking the coding interview” enough to prepare you for Google onsite interview?

Simply put, no.

There’s no doubt that Cracking The Coding Interview (CTCI) is a great tool for honing your coding skills.

But in today’s competitive job landscape, you need a lot more than sharp coding skills to get hired by Google.

Think about it.

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Google receives about 3 million job applications every year.

But it hires less than 1% of those people.

Most of those who get the job (if they’re software engineers, at least) spent weeks or months practicing problems in CTCI and LeetCode before their interview.

But so did the people who don’t get hired.

So if a mastery of coding problems isn’t whats set the winners apart from the losers, what is?

The soft skills.

Believe it or not, soft skills matter a lot, even as a software engineer.

Here are three soft skills Google looks for that CTCI won’t help you with.

#1 LEADERSHIP


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You’d be amazed how many candidates overlook the importance of leadership as they try to get hired by Google.

They forget that recruiters are not looking for their ability to be a strong junior engineer, but their ability to develop into a strong senior engineer.

Recruiters need to know that you have the empathy to lead a team, and that you’re willing to pull up your socks when things go awry.

If you can’t show that you’re a leader in your interview, it won’t matter how good your code is—you won’t be getting hired.

#2 COMMUNICATION & TEAMWORK

Teamwork and communication are two other skill sets you won’t gain from CTCI.

And just like leadership, you need to demonstrate these skills if you expect to get an offer from Google.

Why?

Because building the world’s best technology is a team sport, and if you want to thrive on Team Google, you need to prove yourself as a team player.

Don’t overlook this.

Google and the other FAANG companies regularly pass up skilled engineers because they don’t believe they’ll be strong members of the larger team.

#3 MASTERY OVER AMBIGUITY

Google recruiters often throw highly ambiguous problems at candidates just to see how they handle them.

So if you can’t walk the recruiter through your process for solving it, they’re going to move on to someone else.

The ambiguous problems I’m talking about are not like the ones you face in CTCI. They’re much more open-ended, and there truly are no right answers.

These are the sort of questions you need a guide to help you navigate through. That’s why you need more guidance than what CTCI provides if you want to give yourself the best chance at getting an offer.

If you just want to hone your coding skills, CTCI is a good place to start.

But if you’re serious about getting a job at Google, I recommend a more comprehensive course like Tech Interview Pro, which was designed by ex-Google and ex-Facebook software engineers to help you succeed in all areas of the job hunt, from building your resume all the way to salary negotiations.

Whatever you do, don’t overlook the importance of soft skills on your journey to getting hired. They’ll be what clinches your spot.

Good luck!

Source:

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Is it good useful meaningful worthwhile to use register variables in C++?

What are the Greenest or Least Environmentally Programming Languages?

Is it good useful meaningful worthwhile to use register variables in C++?

The register keyword has been largely ignored by compilers for decades. In C, it prevents you from taking the address of a variable. But otherwise, most compilers ignore the hint it offers.

STANDARD C++ does not support register variables in 2022. In C register variables serve as a hint to the compiler to use a register rather than a memory address. Prior to C++17, it could also be used as a hint to the compiler in C++ as well, but only some conforming compilers did anything as a result. Starting in C++17, register has become an unused but reserved keyword.

Some compilers still permit it and some may even honor the request. Your programs, however, will not be cross-platform or written in true, standards-compliant C++ if you use the register keyword.

Is it good useful meaningful worthwhile to use register variables in C++?
Is it good useful meaningful worthwhile to use register variables in C++?

NOTE:

The situation in C (as opposed to C++) is quite different.

 

“Is it good?”

Usually the answer to that question is that it’s the wrong question, and that you should instead ask “Is it useful/meaningful/worthwhile…?” For example, if you had asked about using the register keyword in C, I would say “There’s nothing wrong about it. It won’t harm your program. It’s just a waste of time.”

It turns out C++ deprecated the register keyword in C++11, and removed it in C++17. As of C++17, the keyword register is now a reserved word with no meaning.

So, the answer to “is it good?” is “No.” Your program will fail to compile as a C++17 program.

By the end of 90s, register was the “R-type” decal of the C programming world. It did about as much for the speed of your program as the decal did for your car. (Possible exception for weak compilers on some embedded platforms.)

In any case, it doesn’t make sense to have a register qualifier on a parameter in a function prototype. It is ignored on any function declaration that is not a definition, similar to top level const.

That is, all four of these are equivalent:

  • void foo(int x);
  • void foo(const int x);
  • void foo(register int x);
  • void foo(register const int x);

Now, both of those are meaningful in a definition. The register keyword stops you from taking an address (in C, but not C++), and const stops you from mutating the variable.

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  • void foo(register const int x) {
  • const int *px = &x; // ERROR
  • x = 42; // ERROR
  • }

So, in principle you should be able to delete the unnecessary and useless register keywords from.the prototypes in the header without affecting any aspect of the program’s speed or correctness.

As of C++17 the use of the register qualifier has been removed. It’s now an unused reserved word.

Old? It is outright obsolete and even if you’re coding on an older version you’re advised to not use it for forward compatibility.

It was a hint to the compiler that a variable would be frequently accessed and the the compiler should prefer to use a CPU register to hold it. The downside being you can’t take the address of a register.

In days of yore (pre-millennium) on now arcane and primitive architectures significant improvements could be had from making (typically) the control variable of a for-loop as a register.

I’m sure that’s still true of some embedded platforms. But modern CPUs have multiple tiers of memory cache and the overhead of loading from and storing variables to main memory is less significant.

We no longer really live with the simplistic Von Neumann of CPU and Main Memory with nothing in between.

Also, optimizers have vastly improved and will tend to make good choices for storage on their own.

It was removed from the standard not because its use was doing harm but that it was regarded as having little practical value and the keyword may be useful in the future.


AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence (OpenAI, ChatGPT, Google Gemini, Generative AI, Discriminative AI, xAI, LLMs, GPUs, Machine Learning, NLP, Promp Engineering)

Reference: here

What are the Greenest or Least Environmentally Friendly Programming Languages?

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