Tag: Mitochondrial infusion

I want to learn AI, but I don't know the best way to do it because I am currently a beginner in Python and SQL, which I studied in college. I also studied math and statistics in college. Can anyone suggest how I can develop my skills and advance in this field? submitted by /u/Own_Hawk2887 [link] [comments]

View Poll submitted by /u/Georgeo57 [link] [comments]

Hi, can active recommend a video tool that specifically can handle the following. I have two cartoon characters. I have 1,000 scripts already created with sone instructions for charachter facial expressions, arm gestures, walking etc Want to create 1,000 videos (can do one at a time but batches preferred) Video of 1 minute each ai generated from the upload of the two character images and a text file that includes instructions for expressions, actions such as walking.. and script of dialogue. Text to speak has to be multiple languages - japanese.. korean.. malay etc Auto captions of the speech and other captions we might want to add I have developed that can integrate with an API if needed and can format script and instructions into whatever file format needed etc. Basically animation from i struction and script created automatically Any advice welcome. It’s for social enterprise and free service. submitted by /u/Far_Incident_8999 [link] [comments]

In a world awash with AI-generated deepfakes, we’re stepping into what can only be described as the “Deep Doubt” era. Remember when you could look at a photo or video and believe it captured reality? Well, those days are fading fast, as AI tools are making it easier to create convincing fakes. But the real twist? Now, anyone can dismiss genuine evidence as just another AI trick. Whether it’s a viral image, a political rally, or even a historical record, it’s becoming harder to know what’s real anymore. What Is “Deep Doubt” Anyway? Deep doubt is the new wave of skepticism bred by the rise of AI-generated media, especially deepfakes. With AI able to create photos, videos, and even voices that mimic reality, people are starting to question everything—even legitimate, fact-based media. This dangerous trend lets people more easily claim that things didn’t happen, pointing to AI as a scapegoat. For instance, in recent months, former President Donald Trump claimed an image with E. Jean Carroll (the writer who sued him for sexual assault) was an AI fabrication. Spoiler: it wasn’t. The “Liar’s Dividend”: How Doubt Became a Tool Back in 2019, legal scholars Danielle Citron and Robert Chesney coined the term "liar's dividend." It’s a neat way of saying: "If everyone thinks something could be fake, liars can claim everything is fake." Simple, right? In practice, though, it's much more alarming. Think about a politician caught on camera saying something incriminating—well, now they can just shrug and say, "It’s probably AI." And a surprising number of people will believe it. We’re seeing this play out everywhere. For example, conspiracy theorists have used AI to push wild claims that public figures—like President Joe Biden—are holograms or digitally created. If you thought your aunt’s Facebook feed was bad before, it’s about to get worse. How We Got Here: A History of Manipulated Media Manipulating media isn’t new. Even before Photoshop, photographers would crop, frame, and manipulate images. It’s just that AI has made it so much easier. Thanks to AI deepfakes, a high schooler in their basement can now create a video of your favorite actor doing or saying just about anything. All they need is a few hours and the right tools. And with each new breakthrough in AI tech, these fakes get more lifelike—and the lies more believable. The Rise of Deep Doubt in Politics and Law It’s not just social media users causing chaos. The real implications of deep doubt hit when it infects more serious areas, like politics and the legal system. Federal judges are already nervous about deepfakes being used to introduce fake evidence into trials or to undermine real evidence. Imagine trying to convict someone based on video footage, only to have the defense argue, "That’s not real; it’s AI." This uncertainty stretches beyond the courtroom. It’s seeping into how we talk about history. Could AI-manipulated media rewrite our understanding of past events? With deepfakes, historical photos and footage—once seen as ironclad proof—could be called into question. If we can’t trust our records, where does that leave us? The Social Fallout: Trust is on Life Support Our trust in online content is eroding fast, and deep doubt is driving us further down the rabbit hole. Enter the “Dead Internet Theory,” a growing conspiracy that claims most online interactions are generated by AI and bots. The fact that it’s so easy to imagine this as true shows just how deep doubt has spread. What’s next? If we stop trusting what we see online, social trust could unravel. It’s already happening as conspiracy theories fester in spaces where AI deepfakes and misinformation thrive. Even tech giants like Microsoft have raised alarms about a potential “post-epistemic world”—a world where fact and fiction blur so much that no one can tell them apart. How to Fight Deep Doubt: Context, Credibility, and Common Sense So, how do we combat deep doubt in this AI-warped world? The key lies in context. Just as a historian would verify a centuries-old parchment by cross-referencing sources, we must do the same with digital media today. Verifying a suspicious video or image means looking for multiple corroborating sources—different angles of the event, original reporting, and reputable eyewitness accounts. It's not enough to trust a single screenshot or viral post. Relying on trustworthy, verified accounts is our best shot at discerning truth from AI-generated fiction. Even though AI detection tools exist, they aren’t foolproof and can often give false results. In the end, good old-fashioned critical thinking, combined with credible sourcing, remains our best defense against deep doubt. Conclusion: Welcome to the New Normal (Unfortunately) As the line between real and fake continues to blur, we’re all going to need to be a little more skeptical—and a lot more vigilant. AI has opened Pandora’s box, and now anyone can weaponize deep doubt to sow confusion, undermine the truth, and erode social trust. The only question left is: How long until we stop believing anything we see online? submitted by /u/These-Salary-9215 [link] [comments]

Generative AI (Gen AI) is a cutting-edge form of artificial intelligence (AI) that can generate new data like images, text, or even code. Unlike traditional AI used for analysis, Gen AI delves deeper to generate new insights and possibilities. Learn in detail about Generative AI and its techniques, application, and impact on businesses. Ever wondered how Baymax scans the body effortlessly, providing the vital stats and diagnosis of the person with preventive measures for any medical issue? Well, it will be considered an AI-generated response. We have not yet reached that stage in AI and healthcare, however, Gen AI is making a lot of movements in the healthcare sector by enabling more accurate diagnoses, personalized treatments, and accelerated drug discovery with healthcare AI companies taking the lead. Read: https://www.seaflux.tech/blogs/genai-impact-in-healthcare-industry submitted by /u/Sandyrocks77 [link] [comments]

How are the latest advancements in AI changing the way digital assistants provide personalized experiences? What specific features do you find most impactful? submitted by /u/CLEVERTONE1 [link] [comments]

Have you heard the buzz about NPUs? If not, you’re about to—because neural processing units (NPUs) are set to become a game-changer for personal computers. You’ve heard of CPUs and GPUs, but NPUs are the next big thing in hardware, and soon, most PCs will have them. But what exactly are they, and why are they so important? NPU 101: What is it? NPU stands for Neural Processing Unit. It’s a specialized processor designed to handle AI and machine learning tasks much more efficiently than traditional CPUs or GPUs. Think of NPUs as AI accelerators—they boost the performance of AI features without draining your battery or heating up your device. How Do NPUs Work? AI tasks, like image recognition or language processing, rely on something called neural networks. NPUs are optimized to process these networks faster and with less power consumption. While GPUs are great at AI tasks, they require lots of energy. NPUs, on the other hand, hit the sweet spot by offering a balance between performance and efficiency. NPU vs. CPU vs. GPU: The Breakdown CPU (Central Processing Unit): Your PC’s brain, handling general tasks. GPU (Graphics Processing Unit): Focused on handling complex graphics and gaming, but also useful for AI work. NPU (Neural Processing Unit): The AI specialist, running tasks like voice assistants, image processing, and more—without hogging system resources or battery life. Why Do NPUs Matter? If you’ve ever run AI tools like ChatGPT or Stable Diffusion on your PC, you might have noticed they’re power-hungry and slow down your machine. NPUs can run these tasks faster and more efficiently. Plus, they free up your CPU and GPU for other tasks, meaning your entire system runs smoother. NPUs in Action: What Can They Do? Windows PCs with NPUs can run AI-powered features, like Microsoft’s Windows Studio Effects (think background blurring on video calls or automatic eye contact correction). In the future, more apps will take advantage of NPUs, offering smoother AI-enhanced experiences—from audio and video editing to gaming. What’s the Catch? Right now, not every PC has an NPU. But brands like Intel, AMD, and Qualcomm are starting to pack them into their newest chips. So, if you're shopping for a new laptop, it’s something to keep an eye on. Should You Get a PC with an NPU Now? It’s tempting to future-proof your device, but NPUs are still in their early stages. For most people, they’re a nice-to-have, not a need-to-have—yet. Many AI tools still run on the cloud, meaning your current hardware will work fine. But if you're looking to stay ahead of the curve, picking up a PC with an NPU could be a smart move for AI-heavy tasks. The AI revolution is just getting started, and NPUs will be at the heart of it. Whether you’re a gamer, creator, or just want a smoother PC experience, NPUs are set to make everything faster, smarter, and more efficient. Note: i used chatgpt to rewrite and make it better due to lack of my English skills submitted by /u/These-Salary-9215 [link] [comments]

By bringing together researchers, practitioners, and nonprofit organizations, G42 and Microsoft are creating a collaborative environment for developing best practices in responsible AI. This partnership is a step toward global AI governance. With endorsement from the UAE’s AIATC and support from both the US and UAE governments, this partnership has significant geopolitical implications. It shows how AI can be regulated and advanced responsibly at an international level. Could this partnership influence global AI policy and regulation? source link: https://www.mediaoffice.abudhabi/en/technology/g42-and-microsoft-to-establish-two-research-centres-in-abu-dhabi-to-advance-development-of-responsible-artificial-intelligence/ submitted by /u/jealousrooster88 [link] [comments]

I want to create floor plans in bulk. If possible with 1 click 🙂 Also a 3d render would be great. Is there an AI app that can do that? I don't need anything professional. It's more important for me to do them really quickly and in bulk. submitted by /u/vovr [link] [comments]

Apologies if I'm not using the correct terms, I just started to get into AI and I'm not super-knowledgable at the moment. This came to mind the other day - I have this video that's otherwise good but it was saved at a lower resolution than it should have been, so it lacks detail in some areas. (You know how if you send someone a video via email on the iPhone it prompts you to send it in a lower resolution? It's that kind of situation.) It occurred to me that maybe an AI could analyze the video and fill in the gaps with generative AI. Here's my logic. Let's say you have a low-quality photo of a wooden fence. You can tell it's a wooden fence (and if you asked an AI they would say it's a wooden fence) but it lacks those finer details like wood grain. So you feed it into the AI, it says "ah, that's a wooden fence and wooden fences have wood grain" and then fills in the grain because that's what it would expect. It uses the photo or image as a baseline and only makes minor changes rather than altering the whole thing, like it might if you said "redo this image in cartoon style" or something like that. I played around with this concept in DiffusionBee but the AI wasn't picking up what I was putting down. Depending on settings like prompt strength, it would either not do anything or give me what was almost a whole new image inspired by the base image. I'm no AI expert so maybe I wasn't using the right search terms, but I did some Googling and it doesn't seem like there's an easy way to do this. Other image tools like Topaz kind of helped but clearly it's not doing that "generative" aspect like I was referring to. It's also a bit hard to tell how tools like Topaz actually work, because it's kind of a black box and obviously they aren't going to spill the beans on their proprietary method. Is there a reason why this is so hard? It seems like it might be an obvious solution to improving video or images that are somewhat lower quality. submitted by /u/UnfoldedHeart [link] [comments]