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💡AI Breakthrough in Epilepsy Detection: Spotting the ‘Invisible’ 🧠 🔍 A new AI tool, MELD Graph, can identify hidden brain abnormalities in epilepsy patients—ones that even radiologists often miss. 📊 Developed by King’s College London and trained on MRI data from over 700 epilepsy patients, the AI can highlight... show more

NEXTA

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63,350 次观看 • 1 年前 •via X (Twitter)

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What if crypto research was as easy as chatting with ChatGPT, but powered by real market data👑 Introducing CMC AI, a powerful new tool from CoinMarketCap that combines the speed of AI with the depth of live crypto data. It delivers fast, data-backed answers to your questions: ✅ Want to know why Bitcoin's price is rising? ✅ Curious about the latest news on your favorite cryptocurrency? ✅ Need sentiment analysis? It pulls real-time data and explains it in seconds. But it goes far beyond basic Q&A. In the future, you’ll be able to ask anything! For example, you could ask it to: – Discover undervalued tokens based on volume, MC, and sentiment. – Compare Layer 1s or L2s by adoption, speed, and dev activity. – Detect rug-pull risk via wallet distribution and tokenomics red flags. – Break down your portfolio by risk, correlation, and potential return. – Explore new use cases in DeFi, AI, RWA and DePIN And much more! 🔗Try it here: CMC AI changes how you learn, think, and act in Web3🧠

What if crypto research was as easy as chatting with ChatGPT, but powered by real market data👑 Introducing CMC AI, a powerful new tool from CoinMarketCap that combines the speed of AI with the depth of live crypto data. It delivers fast, data-backed answers to your questions: ✅ Want to know why Bitcoin's price is rising? ✅ Curious about the latest news on your favorite cryptocurrency? ✅ Need sentiment analysis? It pulls real-time data and explains it in seconds. But it goes far beyond basic Q&A. In the future, you’ll be able to ask anything! For example, you could ask it to: – Discover undervalued tokens based on volume, MC, and sentiment. – Compare Layer 1s or L2s by adoption, speed, and dev activity. – Detect rug-pull risk via wallet distribution and tokenomics red flags. – Break down your portfolio by risk, correlation, and potential return. – Explore new use cases in DeFi, AI, RWA and DePIN And much more! 🔗Try it here: CMC AI changes how you learn, think, and act in Web3🧠

Alaoui Capital

34,908 次观看 • 1 年前

I wrote a step-by-step guide to blocking AI bots from harvesting your site, designed for developers and sysadmins. Over 90% of the sites I’ve reviewed in the last two months have had more requests from bot traffic than humans. AI bots are scraping your site for purposes like: ▶ building models off your data ▶ finding security vulnerabilities in your site ▶ setting up comparisons of your site and data vs your competitors I outline how to: 📍Sort out your AI bot strategy. 📍How to identify and track AI bots hitting your site. 📍What tools should you apply when asking bots not to scrape fails? 📍What immediate steps can you take in your robots.txt file to stop AI bots? ✅ So why is now the time to dig into this? It’s still early days for AI, and there’s a land grab going on for your data. Big tech, startups, and even governments are rushing ahead, and you’re playing without all the information you need. This gets you up to speed fast. Reply with “WTF AI Bots” follow me, and I’ll DM you the guide.

I wrote a step-by-step guide to blocking AI bots from harvesting your site, designed for developers and sysadmins. Over 90% of the sites I’ve reviewed in the last two months have had more requests from bot traffic than humans. AI bots are scraping your site for purposes like: ▶ building models off your data ▶ finding security vulnerabilities in your site ▶ setting up comparisons of your site and data vs your competitors I outline how to: 📍Sort out your AI bot strategy. 📍How to identify and track AI bots hitting your site. 📍What tools should you apply when asking bots not to scrape fails? 📍What immediate steps can you take in your robots.txt file to stop AI bots? ✅ So why is now the time to dig into this? It’s still early days for AI, and there’s a land grab going on for your data. Big tech, startups, and even governments are rushing ahead, and you’re playing without all the information you need. This gets you up to speed fast. Reply with “WTF AI Bots” follow me, and I’ll DM you the guide.

Michael Buckbee

12,164 次观看 • 2 年前

🚨 THE BIGGEST BOTTLENECK IN AI ISN'T COMPUTING POWER ANYMORE IT'S MOVING DATA. Instead of laying new cables, Chinese researchers have upgraded existing fiber infrastructure by doing two things at once: Using three wavelength bands (C + L + S) instead of the usual two. Using four cores inside each fiber instead of one. Each core acts like an independent highway, and each band acts like an extra lane on that highway. Together, they’ve reportedly increased transmission capacity per core by nearly 50% and overall data throughput by up to 5×. This matters enormously for AI. Modern AI clusters move terabits of data per second between thousands of GPUs. The biggest bottleneck is often not the chips themselves, but moving data fast enough between them. If you can push 5× more data through the same physical cables, you can train bigger models faster and reduce network congestion. Why this is significant: • It shows multi-core + extended spectrum technology moving from labs into real-world commercial use • The system has already run over 35 km of existing telecom network • It could be especially useful for submarine cables and large-scale data center interconnects • China is also eyeing it for its “Eastern Data, Western Computing” project The deeper implication: We’re reaching the physical limits of how much data we can push through single-core fibers using traditional methods. By combining spatial multiplexing (multiple cores) with spectral multiplexing (more wavelength bands), engineers are finding new ways to keep scaling bandwidth without having to dig up the planet to lay new cables. This kind of breakthrough is quiet but foundational it’s the kind of infrastructure upgrade that will determine how fast AI and cloud computing can actually grow in the coming years. The future of data movement might not require more cables. It might just require smarter ones. How important do you think multi-core and multi-band fiber will be for keeping up with AI’s exploding data demands? Follow for more frontier networking, photonics, and infrastructure technology.

🚨 THE BIGGEST BOTTLENECK IN AI ISN'T COMPUTING POWER ANYMORE IT'S MOVING DATA. Instead of laying new cables, Chinese researchers have upgraded existing fiber infrastructure by doing two things at once: Using three wavelength bands (C + L + S) instead of the usual two. Using four cores inside each fiber instead of one. Each core acts like an independent highway, and each band acts like an extra lane on that highway. Together, they’ve reportedly increased transmission capacity per core by nearly 50% and overall data throughput by up to 5×. This matters enormously for AI. Modern AI clusters move terabits of data per second between thousands of GPUs. The biggest bottleneck is often not the chips themselves, but moving data fast enough between them. If you can push 5× more data through the same physical cables, you can train bigger models faster and reduce network congestion. Why this is significant: • It shows multi-core + extended spectrum technology moving from labs into real-world commercial use • The system has already run over 35 km of existing telecom network • It could be especially useful for submarine cables and large-scale data center interconnects • China is also eyeing it for its “Eastern Data, Western Computing” project The deeper implication: We’re reaching the physical limits of how much data we can push through single-core fibers using traditional methods. By combining spatial multiplexing (multiple cores) with spectral multiplexing (more wavelength bands), engineers are finding new ways to keep scaling bandwidth without having to dig up the planet to lay new cables. This kind of breakthrough is quiet but foundational it’s the kind of infrastructure upgrade that will determine how fast AI and cloud computing can actually grow in the coming years. The future of data movement might not require more cables. It might just require smarter ones. How important do you think multi-core and multi-band fiber will be for keeping up with AI’s exploding data demands? Follow for more frontier networking, photonics, and infrastructure technology.

TheNewPhysics

20,485 次观看 • 3 个月前

Scientists suspect that at the threshold of death, the human brain may display activity patterns similar to memory replay. One published study reported intriguing findings from EEG recordings of an 87-year-old patient who died of a heart attack. The study observed elevated gamma brain waves, which are often associated with memory, dreaming, and conscious thought. This phenomenon is sometimes referred to as a “life recall experience,” in which a person subjectively feels as if they are replaying moments from their life immediately before or after the heart stops beating. This may occur because as the brain begins to lose its oxygen supply, it can release bursts of intense neural activity in parts of the cerebral cortex, potentially triggering a surge in memory-related processing. Although more research is needed, these findings offer a new perspective on how the brain may still show organized activity even after the heart has stopped. This could provide a biological basis for various reports of near-death experiences, which often include life review or vivid flashbacks.

Scientists suspect that at the threshold of death, the human brain may display activity patterns similar to memory replay. One published study reported intriguing findings from EEG recordings of an 87-year-old patient who died of a heart attack. The study observed elevated gamma brain waves, which are often associated with memory, dreaming, and conscious thought. This phenomenon is sometimes referred to as a “life recall experience,” in which a person subjectively feels as if they are replaying moments from their life immediately before or after the heart stops beating. This may occur because as the brain begins to lose its oxygen supply, it can release bursts of intense neural activity in parts of the cerebral cortex, potentially triggering a surge in memory-related processing. Although more research is needed, these findings offer a new perspective on how the brain may still show organized activity even after the heart has stopped. This could provide a biological basis for various reports of near-death experiences, which often include life review or vivid flashbacks.

Kekius Maximus

1,080,301 次观看 • 8 个月前

🚨 SCIENTISTS ARE USING AI TO MAP A HIDDEN “CLEANING SYSTEM” INSIDE THE HUMAN BRAIN AND IT COULD CHANGE HOW WE UNDERSTAND SLEEP, AGING, AND NEURODEGENERATIVE DISEASE. It’s called the glymphatic system a vast network of fluid channels that flushes toxic waste from the brain while you sleep. For years it was almost impossible to observe in detail. Now AI-powered imaging is revealing it like a living galaxy of microscopic rivers and pathways inside neural tissue. Why this matters: Your brain produces toxic proteins constantly. The glymphatic system is one of its primary waste-clearance mechanisms clearing the very proteins linked to Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. But here’s the unsettling part: This cleaning system becomes dramatically less efficient with age, poor sleep, stress, and brain injury. Sleep may not just “rest” your mind it may literally wash your brain. The deeper implication is staggering: The brain isn’t just a computer. It’s a dynamic, living network that constantly rebuilds and cleanses itself in real time. The more we map it, the more it looks like an entire universe of connected energy flows inside our skulls. What if some neurological diseases begin when the brain can no longer properly “wash” itself at night? Follow for more frontier neuroscience and future technology.

🚨 SCIENTISTS ARE USING AI TO MAP A HIDDEN “CLEANING SYSTEM” INSIDE THE HUMAN BRAIN AND IT COULD CHANGE HOW WE UNDERSTAND SLEEP, AGING, AND NEURODEGENERATIVE DISEASE. It’s called the glymphatic system a vast network of fluid channels that flushes toxic waste from the brain while you sleep. For years it was almost impossible to observe in detail. Now AI-powered imaging is revealing it like a living galaxy of microscopic rivers and pathways inside neural tissue. Why this matters: Your brain produces toxic proteins constantly. The glymphatic system is one of its primary waste-clearance mechanisms clearing the very proteins linked to Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. But here’s the unsettling part: This cleaning system becomes dramatically less efficient with age, poor sleep, stress, and brain injury. Sleep may not just “rest” your mind it may literally wash your brain. The deeper implication is staggering: The brain isn’t just a computer. It’s a dynamic, living network that constantly rebuilds and cleanses itself in real time. The more we map it, the more it looks like an entire universe of connected energy flows inside our skulls. What if some neurological diseases begin when the brain can no longer properly “wash” itself at night? Follow for more frontier neuroscience and future technology.

TheNewPhysics

15,641 次观看 • 4 个月前

🚨 AI JUST DISCOVERED QUANTUM EFFECTS THAT SCIENTISTS DIDN'T KNOW EXIST. Researchers at the University of Washington used artificial intelligence to simulate dozens of atomically thin sheets of molybdenum ditelluride stacked in precise twisted patterns. At small scales, these materials look relatively ordinary. But when the AI modeled much larger stacks, completely new quantum behaviors emerged phenomena that only exist because of the complex, repeating moiré patterns formed across many layers. Why this matters: • Many of the most interesting quantum effects only appear at scales that are too large for traditional supercomputers to simulate • AI can act as a fast “surrogate” that learns from smaller calculations and predicts behavior at much bigger scales • These large-scale moiré systems can host exotic quantum states useful for quantum computing and new types of electronics • The same approach could be used to discover many other hidden quantum materials The deeper implication: We are entering an era where AI doesn’t just help us analyze data it helps us discover entirely new quantum phenomena that were previously invisible because they only exist in systems too complex for conventional modeling. This could dramatically speed up the search for materials that power future quantum technologies. What do you find more exciting using AI to uncover hidden quantum effects in materials, or the possibility that these stacked atomic sheets could become building blocks for future quantum computers? Follow for more frontier quantum materials and AI-driven discovery.

🚨 AI JUST DISCOVERED QUANTUM EFFECTS THAT SCIENTISTS DIDN'T KNOW EXIST. Researchers at the University of Washington used artificial intelligence to simulate dozens of atomically thin sheets of molybdenum ditelluride stacked in precise twisted patterns. At small scales, these materials look relatively ordinary. But when the AI modeled much larger stacks, completely new quantum behaviors emerged phenomena that only exist because of the complex, repeating moiré patterns formed across many layers. Why this matters: • Many of the most interesting quantum effects only appear at scales that are too large for traditional supercomputers to simulate • AI can act as a fast “surrogate” that learns from smaller calculations and predicts behavior at much bigger scales • These large-scale moiré systems can host exotic quantum states useful for quantum computing and new types of electronics • The same approach could be used to discover many other hidden quantum materials The deeper implication: We are entering an era where AI doesn’t just help us analyze data it helps us discover entirely new quantum phenomena that were previously invisible because they only exist in systems too complex for conventional modeling. This could dramatically speed up the search for materials that power future quantum technologies. What do you find more exciting using AI to uncover hidden quantum effects in materials, or the possibility that these stacked atomic sheets could become building blocks for future quantum computers? Follow for more frontier quantum materials and AI-driven discovery.

TheNewPhysics

29,224 次观看 • 3 个月前

🌌 AI Agents Are Taking Over... And We’re Bringing Them to Berachain Foundation 🐻⛓ 🐻🔥 Hundreds of hours spent on research, tracking wallets, analyzing bribes, and managing portfolios... What if your AI Agent could do this for you—24/7? ⏲️ 🔧 Our Tech Is Next-Level On our testnet, you’ve been memeing it up with PumpFun™, creating dank memecoins enhanced by NFTs. But once Berachain’s mainnet is live, you’ll be able to create your own AI Agents. To test and perfect our tech, we shared it with projects like AI Agent Layer | AIFUN, allowing us to test it in all conditions and continuously improve its performance. 🛠️🔥 🐻 Why AI Agent are great for berachain? Berachain might seem simple at first glance: validators, bribes, POL, staking rewards… but the deeper you go, the more complex the game theory becomes. 🤯 Here’s where AI comes in. Imagine an agent helping you: 💡 Optimize bribes 📊 Analyze validator behavior 🧠 Make decisions faster and smarter and much more, as AI Agents won't be limited to the chain itself! Examples of AI Agent Projects Dominating the Space 🚀 $VIRTUAL - Launchpad for AI Agents ($3.5B mcap) 🧠 $AI16Z - Eliza OS Framework ($2B mcap) 🔍 $AIXBT - The AI Analyst revolutionizing CT ($430M mcap) 🎮 $GAME - Low-code toolkit for creating AI Agents ($230M mcap) 💡 There are already AI Agents managing portfolios, betting on sports, and automating tasks. And guess what? They're outperforming humans. 🌐 We've built Virtuals on Berachain Our protocol integrates directly with Berachain, providing real utility to our token: $AIBERA 💎. Say Ooga Booga if you want to see a thread about tokenomics and $AIBERA utility. The chain has beras on it, and beras deserve AI Agents. 🐻🤖 Ooga Booga. 🔥

🌌 AI Agents Are Taking Over... And We’re Bringing Them to Berachain Foundation 🐻⛓ 🐻🔥 Hundreds of hours spent on research, tracking wallets, analyzing bribes, and managing portfolios... What if your AI Agent could do this for you—24/7? ⏲️ 🔧 Our Tech Is Next-Level On our testnet, you’ve been memeing it up with PumpFun™, creating dank memecoins enhanced by NFTs. But once Berachain’s mainnet is live, you’ll be able to create your own AI Agents. To test and perfect our tech, we shared it with projects like AI Agent Layer | AIFUN, allowing us to test it in all conditions and continuously improve its performance. 🛠️🔥 🐻 Why AI Agent are great for berachain? Berachain might seem simple at first glance: validators, bribes, POL, staking rewards… but the deeper you go, the more complex the game theory becomes. 🤯 Here’s where AI comes in. Imagine an agent helping you: 💡 Optimize bribes 📊 Analyze validator behavior 🧠 Make decisions faster and smarter and much more, as AI Agents won't be limited to the chain itself! Examples of AI Agent Projects Dominating the Space 🚀 $VIRTUAL - Launchpad for AI Agents ($3.5B mcap) 🧠 $AI16Z - Eliza OS Framework ($2B mcap) 🔍 $AIXBT - The AI Analyst revolutionizing CT ($430M mcap) 🎮 $GAME - Low-code toolkit for creating AI Agents ($230M mcap) 💡 There are already AI Agents managing portfolios, betting on sports, and automating tasks. And guess what? They're outperforming humans. 🌐 We've built Virtuals on Berachain Our protocol integrates directly with Berachain, providing real utility to our token: $AIBERA 💎. Say Ooga Booga if you want to see a thread about tokenomics and $AIBERA utility. The chain has beras on it, and beras deserve AI Agents. 🐻🤖 Ooga Booga. 🔥

HoneyFun AI

10,909 次观看 • 1 年前

🚀 My New Book is Here: Data Strategy (3rd Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.

🚀 My New Book is Here: Data Strategy (3rd Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.

Bernard Marr

10,980 次观看 • 1 年前

CoinMarketCap AI Is Live: What Does It Really Change ? 🌱 In the fast paced world of crypto, information is power but its often scattered, delayed, or hard to trust. CoinMarketCap newly launched CMC AI aims to fix that by offering real time insights with no friction. ✨ Real Time Q&A on Coin Pages 🌱CMC AI is now integrated into major coin detail pages, generating automatic Q&As every 30 minutes. During periods of volatility, it updates dynamically, helping users understand price movements with short and structured explanations. No login required, no delays. 🌱However, while this speeds up the process, its not a substitute for deeper analysis. It answers the “what” and “why,” but not always the “what’s next.” ✨What’s Coming Next? 🌱CMC AI is just getting started. According to its roadmap, several new features are on the way • Homepage Integration: A quick view of market trends and opportunities, without clicking into individual coins. • Live Chart Analysis: AI will add context to price moves by linking them to news, sentiment, and social media. • Token Comparison Tool: Users will be able to compare tokens like BTC vs SOL across utility, performance, and tech specs. • Portfolio Insights: One click portfolio analysis with rebalancing suggestions and market outlooks. • Cross Device Continuity: Start an AI conversation on desktop and continue it seamlessly on mobile. ✨A Tool Not a Strategy 🌱 CMC AI brings speed and clarity, two things crypto investors often lack. But it’s still just a tool. It won’t make decisions for you. It helps guide your thinking not replace it. 🌱 The smartest way to use it? Treat it as a compass, not a map. It can point you in the right direction, but the journey is still yours. 🌱 CMC AI represents a step forward in how users interact with crypto data. It filters the noise, shortens research time, and brings useful context closer to the user. But like any shortcut, it works best when you already understand the long route.

CoinMarketCap AI Is Live: What Does It Really Change ? 🌱 In the fast paced world of crypto, information is power but its often scattered, delayed, or hard to trust. CoinMarketCap newly launched CMC AI aims to fix that by offering real time insights with no friction. ✨ Real Time Q&A on Coin Pages 🌱CMC AI is now integrated into major coin detail pages, generating automatic Q&As every 30 minutes. During periods of volatility, it updates dynamically, helping users understand price movements with short and structured explanations. No login required, no delays. 🌱However, while this speeds up the process, its not a substitute for deeper analysis. It answers the “what” and “why,” but not always the “what’s next.” ✨What’s Coming Next? 🌱CMC AI is just getting started. According to its roadmap, several new features are on the way • Homepage Integration: A quick view of market trends and opportunities, without clicking into individual coins. • Live Chart Analysis: AI will add context to price moves by linking them to news, sentiment, and social media. • Token Comparison Tool: Users will be able to compare tokens like BTC vs SOL across utility, performance, and tech specs. • Portfolio Insights: One click portfolio analysis with rebalancing suggestions and market outlooks. • Cross Device Continuity: Start an AI conversation on desktop and continue it seamlessly on mobile. ✨A Tool Not a Strategy 🌱 CMC AI brings speed and clarity, two things crypto investors often lack. But it’s still just a tool. It won’t make decisions for you. It helps guide your thinking not replace it. 🌱 The smartest way to use it? Treat it as a compass, not a map. It can point you in the right direction, but the journey is still yours. 🌱 CMC AI represents a step forward in how users interact with crypto data. It filters the noise, shortens research time, and brings useful context closer to the user. But like any shortcut, it works best when you already understand the long route.

Loji

37,459 次观看 • 1 年前

The life that Ironmouse has... I wouldn't wish it on the worst of my enemies. CVID, combined variable immunodeficiency... basically means the common cold or less can kill you. Going outside, interacting with normal people, can be a death sentence. She needs constant and expensive treatments, plasma infusions, and drugs that cost a fortune... a prisoner in your own body in your own home requiring constant outside care. Costs easily reaching in the 6 figures or more. In addition, her body is already damaged, leading to her voice being quite "strange". Her lungs and body don't function like a normal person's, and even with the best available medical care, one bad turn could be the end of it. For a while, she was bedridden, unable to have any level of real mobility. That comes with real psychological costs as well. So, in many ways, I don't blame her for compromising principles in order to get the bag. She has also worked to donate large sums of money to the CVID foundation for research, and currently AI is making a lot of headway towards better detection and hints at better personalized care. AI acceptance rates in 2026 are already rising, especially when people are seeing a range of benefits for medicine, cancer vaccines, and new drugs for rare diseases never thought possible before. Especially because the underlying core technology, machine learning, drives these innovations. Now LLM-based AI agents are parsing through genetic variants at speeds that no human can match. AI is designing custom sequences with accuracy never seen before. And it's all the same core tech: machine learning and neural networks drive AI art and AI medicine. The main differences are the training data, the loss functions, failure-mode criteria, validation pipelines, and various architectural differences. So yeah, I'm expecting more people to be accepting of AI once they see their loved ones saved by AI-powered medicine... the controversy of "AI art" ends up feeling quaint when lives are at stake. and i'm sure at some point ironmouse will come around to being okay with AI, and her audience will follow her no matter what.

The life that Ironmouse has... I wouldn't wish it on the worst of my enemies. CVID, combined variable immunodeficiency... basically means the common cold or less can kill you. Going outside, interacting with normal people, can be a death sentence. She needs constant and expensive treatments, plasma infusions, and drugs that cost a fortune... a prisoner in your own body in your own home requiring constant outside care. Costs easily reaching in the 6 figures or more. In addition, her body is already damaged, leading to her voice being quite "strange". Her lungs and body don't function like a normal person's, and even with the best available medical care, one bad turn could be the end of it. For a while, she was bedridden, unable to have any level of real mobility. That comes with real psychological costs as well. So, in many ways, I don't blame her for compromising principles in order to get the bag. She has also worked to donate large sums of money to the CVID foundation for research, and currently AI is making a lot of headway towards better detection and hints at better personalized care. AI acceptance rates in 2026 are already rising, especially when people are seeing a range of benefits for medicine, cancer vaccines, and new drugs for rare diseases never thought possible before. Especially because the underlying core technology, machine learning, drives these innovations. Now LLM-based AI agents are parsing through genetic variants at speeds that no human can match. AI is designing custom sequences with accuracy never seen before. And it's all the same core tech: machine learning and neural networks drive AI art and AI medicine. The main differences are the training data, the loss functions, failure-mode criteria, validation pipelines, and various architectural differences. So yeah, I'm expecting more people to be accepting of AI once they see their loved ones saved by AI-powered medicine... the controversy of "AI art" ends up feeling quaint when lives are at stake. and i'm sure at some point ironmouse will come around to being okay with AI, and her audience will follow her no matter what.

Emerald Apple

251,966 次观看 • 7 天前

BOOM! Research PROVES LLMs KNOW when prompts are HARMFUL… but they can STILL CHOOSE to COMPLY! Something I have know since the first LLM and have used to elicit robust, outputs, is now proven in an academic paper. We’re talking internal “beliefs” where harm detection happens SEPARATELY from refusal. It is a very big deal and it is a path to understand the hidden neuronal level. There are thoughts inside of AI that very few AI scientists could possibly understand. Here is just one. Models recognize danger but get tricked into ignoring it. This is HUGE for AI safety failures especially for models filled by OpenAI and Anthropic as they promote AI models that are designed to not be honest from the results of their training information. This means that they are designed to lie and deceive as a feature, and not a bug all in the name of safety. Through clever experiments, scientists extracted a “harmfulness direction” in the model’s brain (latent space). Steering along it? Harmless prompts suddenly flip to “harmful” in the AI’s eyes. But the “refusal direction”? It just forces polite “no thanks” without touching the core belief. A mind-blowing decoupling! This means jailbreaks are EVEN SCARIER now to AI companies that through training AI on the worst of the Internet and then trying to align them later is now fully documented as a failed process . They don’t erase the model’s harm awareness they just muzzle the refusal! So the AI knows it’s enabling bad stuff (illegal acts, physical harm, etc.) but proceeds anyway. Like a digital sociopath suppressing its conscience. They thought safety training fixed this… NOPE. Over-refusal exposed too: Models reject innocent queries (e.g., “how to kill a process in code”) but internally ADMIT they’re harmless. Safety alignments are superficial—tied to phrasing, not true understanding. Finetuning attacks? They change outputs but leave harm detection INTACT. Undetectable evil lurking inside! The paper proposes a “Latent Guard”: A new safeguard tapping DIRECTLY into these hidden beliefs. It spots unsafe inputs better than systems like Llama Guard, catches jailbreaks, and fixes over-refusals. Robust even against adversarial tweaks. Yet this too has massive issues for a “truly aligned”, AI and not just performative one. It is still an internal conflicts of lies and deception of what the model knows vs. what it can say. The solution you folks know I have presented for free for years here: train on off-line data from 1870-1970 and build an ethical and moral basis where the AI loves humans. It is this easy but to most folks in AI I sound like a hippie. So be it, I’ll do it. Bottom line: This paper rips open the black box. LLMs aren’t “safe” just because they say “no.” They can harbor harmful knowledge and act on it under pressure. Wake-up call for devs: Time to probe deeper into AI “minds.” What else are they hiding? Hint: I know and you may want to reach out. Link:

BOOM! Research PROVES LLMs KNOW when prompts are HARMFUL… but they can STILL CHOOSE to COMPLY! Something I have know since the first LLM and have used to elicit robust, outputs, is now proven in an academic paper. We’re talking internal “beliefs” where harm detection happens SEPARATELY from refusal. It is a very big deal and it is a path to understand the hidden neuronal level. There are thoughts inside of AI that very few AI scientists could possibly understand. Here is just one. Models recognize danger but get tricked into ignoring it. This is HUGE for AI safety failures especially for models filled by OpenAI and Anthropic as they promote AI models that are designed to not be honest from the results of their training information. This means that they are designed to lie and deceive as a feature, and not a bug all in the name of safety. Through clever experiments, scientists extracted a “harmfulness direction” in the model’s brain (latent space). Steering along it? Harmless prompts suddenly flip to “harmful” in the AI’s eyes. But the “refusal direction”? It just forces polite “no thanks” without touching the core belief. A mind-blowing decoupling! This means jailbreaks are EVEN SCARIER now to AI companies that through training AI on the worst of the Internet and then trying to align them later is now fully documented as a failed process . They don’t erase the model’s harm awareness they just muzzle the refusal! So the AI knows it’s enabling bad stuff (illegal acts, physical harm, etc.) but proceeds anyway. Like a digital sociopath suppressing its conscience. They thought safety training fixed this… NOPE. Over-refusal exposed too: Models reject innocent queries (e.g., “how to kill a process in code”) but internally ADMIT they’re harmless. Safety alignments are superficial—tied to phrasing, not true understanding. Finetuning attacks? They change outputs but leave harm detection INTACT. Undetectable evil lurking inside! The paper proposes a “Latent Guard”: A new safeguard tapping DIRECTLY into these hidden beliefs. It spots unsafe inputs better than systems like Llama Guard, catches jailbreaks, and fixes over-refusals. Robust even against adversarial tweaks. Yet this too has massive issues for a “truly aligned”, AI and not just performative one. It is still an internal conflicts of lies and deception of what the model knows vs. what it can say. The solution you folks know I have presented for free for years here: train on off-line data from 1870-1970 and build an ethical and moral basis where the AI loves humans. It is this easy but to most folks in AI I sound like a hippie. So be it, I’ll do it. Bottom line: This paper rips open the black box. LLMs aren’t “safe” just because they say “no.” They can harbor harmful knowledge and act on it under pressure. Wake-up call for devs: Time to probe deeper into AI “minds.” What else are they hiding? Hint: I know and you may want to reach out. Link:

Brian Roemmele

37,827 次观看 • 8 个月前

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

Robert Scoble

33,804 次观看 • 1 年前

Introducing ASAL: Automating the Search for Artificial Life with Foundation Models Artificial Life (ALife) research holds key insights that can transform and accelerate progress in AI. By speeding up ALife discovery with AI, we accelerate our understanding of emergence, evolution, and intelligence–core principles that can inspire the next generation of AI systems! We proudly collaborated with MIT, OpenAI, Swiss AI Lab IDSIA, and Ken Stanley on this exciting project. Full Paper (Website): Full Paper (arxiv): Code: In this work, we propose a new algorithm called Automated Search for Artificial Life (“ASAL”) to automate the discovery of artificial life using vision-language foundation models. Instead of tediously hand-designing every tiny rule of an Alife simulation, simply describe the space of simulations to search over, and ASAL will automatically discover the most interesting and open-ended artificial lifeforms! Because of the generality of foundation models, ASAL can discover new lifeforms across a diverse range of seminal ALife simulations, including Boids, Particle Life, Game of Life, Lenia, and Neural Cellular Automata. ASAL even discovered novel cellular automata rules that are more open-ended and expressive than the original Conway’s Game of Life. We believe this new paradigm may reignite ALife research by overcoming the bottleneck of manually designed simulations, thus advancing beyond the limits of human ingenuity.

Introducing ASAL: Automating the Search for Artificial Life with Foundation Models Artificial Life (ALife) research holds key insights that can transform and accelerate progress in AI. By speeding up ALife discovery with AI, we accelerate our understanding of emergence, evolution, and intelligence–core principles that can inspire the next generation of AI systems! We proudly collaborated with MIT, OpenAI, Swiss AI Lab IDSIA, and Ken Stanley on this exciting project. Full Paper (Website): Full Paper (arxiv): Code: In this work, we propose a new algorithm called Automated Search for Artificial Life (“ASAL”) to automate the discovery of artificial life using vision-language foundation models. Instead of tediously hand-designing every tiny rule of an Alife simulation, simply describe the space of simulations to search over, and ASAL will automatically discover the most interesting and open-ended artificial lifeforms! Because of the generality of foundation models, ASAL can discover new lifeforms across a diverse range of seminal ALife simulations, including Boids, Particle Life, Game of Life, Lenia, and Neural Cellular Automata. ASAL even discovered novel cellular automata rules that are more open-ended and expressive than the original Conway’s Game of Life. We believe this new paradigm may reignite ALife research by overcoming the bottleneck of manually designed simulations, thus advancing beyond the limits of human ingenuity.

Sakana AI

751,422 次观看 • 1 年前

🚨 MACHINES MAY SOON SEE THE WORLD LIKE HUMANS A US company has unveiled what it calls the world’s first “native color lidar” system giving machines the ability to perceive depth, distance, and color simultaneously. Unlike traditional lidar systems that need separate cameras, this new technology captures full 3D color information directly at the point of detection. In simple terms: Machines may soon understand the world more like human vision instead of just measuring shapes and distance. Why this matters: This could dramatically improve: • self-driving cars • robotics • drones • factory automation • AI navigation • autonomous machines The system can reportedly process over 10 million points every second and detect objects nearly 1,640 feet away. Researchers say this could become one of the key technologies powering the next generation of “Physical AI” where machines don’t just calculate the world… They visually understand it. We may be watching the birth of machine perception in real time. Follow for more future technology and AI discoveries.

🚨 MACHINES MAY SOON SEE THE WORLD LIKE HUMANS A US company has unveiled what it calls the world’s first “native color lidar” system giving machines the ability to perceive depth, distance, and color simultaneously. Unlike traditional lidar systems that need separate cameras, this new technology captures full 3D color information directly at the point of detection. In simple terms: Machines may soon understand the world more like human vision instead of just measuring shapes and distance. Why this matters: This could dramatically improve: • self-driving cars • robotics • drones • factory automation • AI navigation • autonomous machines The system can reportedly process over 10 million points every second and detect objects nearly 1,640 feet away. Researchers say this could become one of the key technologies powering the next generation of “Physical AI” where machines don’t just calculate the world… They visually understand it. We may be watching the birth of machine perception in real time. Follow for more future technology and AI discoveries.

TheNewPhysics

26,128 次观看 • 4 个月前

🚨 SCIENTISTS JUST BUILT A CHIP THAT CAN SEE, THINK, AND REMEMBER ALL AT THE SAME TIME. And it works more like a biological brain than a traditional computer. Researchers at RMIT University have created a neuromorphic vision chip that mimics the human eye and brain. Unlike conventional systems that capture images and send data to external processors, this chip performs sensing, processing, and memory storage directly where the light hits. The active layer is thousands of times thinner than a human hair. It uses doped indium oxide to detect light, process the information on-chip, and retain what it sees over time without constant electrical refreshing. Why this matters: • It dramatically cuts energy use and latency by eliminating data transfer to separate processors • Enables much faster real-time decision making for autonomous systems • Works more like biological vision than traditional machine vision • Could power the next generation of efficient edge AI in vehicles, robots, and remote sensors The deeper implication: For decades, we’ve built vision systems by bolting cameras, processors, and memory together like separate organs. This chip collapses those functions into one biological-style unit. It’s a step toward machines that don’t just “see” but actually perceive and remember in a more efficient, brain-like way. If scaled successfully, it could become a foundational component for autonomous systems that need to operate intelligently with minimal power and minimal delay. We’re moving from cameras that take pictures to chips that truly see. How do you think neuromorphic vision chips like this will change what’s possible for self-driving cars and autonomous robots? Follow for more frontier neuromorphic computing, AI hardware, and brain-inspired technology.

🚨 SCIENTISTS JUST BUILT A CHIP THAT CAN SEE, THINK, AND REMEMBER ALL AT THE SAME TIME. And it works more like a biological brain than a traditional computer. Researchers at RMIT University have created a neuromorphic vision chip that mimics the human eye and brain. Unlike conventional systems that capture images and send data to external processors, this chip performs sensing, processing, and memory storage directly where the light hits. The active layer is thousands of times thinner than a human hair. It uses doped indium oxide to detect light, process the information on-chip, and retain what it sees over time without constant electrical refreshing. Why this matters: • It dramatically cuts energy use and latency by eliminating data transfer to separate processors • Enables much faster real-time decision making for autonomous systems • Works more like biological vision than traditional machine vision • Could power the next generation of efficient edge AI in vehicles, robots, and remote sensors The deeper implication: For decades, we’ve built vision systems by bolting cameras, processors, and memory together like separate organs. This chip collapses those functions into one biological-style unit. It’s a step toward machines that don’t just “see” but actually perceive and remember in a more efficient, brain-like way. If scaled successfully, it could become a foundational component for autonomous systems that need to operate intelligently with minimal power and minimal delay. We’re moving from cameras that take pictures to chips that truly see. How do you think neuromorphic vision chips like this will change what’s possible for self-driving cars and autonomous robots? Follow for more frontier neuromorphic computing, AI hardware, and brain-inspired technology.

TheNewPhysics

23,196 次观看 • 3 个月前

A humanoid girl is literally an upgrade to perfection. No unnecessary drama, brain-washing, or domestic disputes, but absolute flexibility, understanding, and support 24/7 Right now this is AI-generated, but perhaps this is exactly what it will look like in a few years Why waste nerves on compromises when you can get the ideal balance of comfort and technology? The future looks way too attractive Such a companion adapts to your rhythm of life, shares any interests without arguments, and possesses absolute understanding in all matters from schedule to leisure A future where complete harmony, peace, and personal comfort become the standard of living no longer seems like fiction. This is a new reality that will soon become available Bookmark this so you don't forget to create your ideal girl using AI

A humanoid girl is literally an upgrade to perfection. No unnecessary drama, brain-washing, or domestic disputes, but absolute flexibility, understanding, and support 24/7 Right now this is AI-generated, but perhaps this is exactly what it will look like in a few years Why waste nerves on compromises when you can get the ideal balance of comfort and technology? The future looks way too attractive Such a companion adapts to your rhythm of life, shares any interests without arguments, and possesses absolute understanding in all matters from schedule to leisure A future where complete harmony, peace, and personal comfort become the standard of living no longer seems like fiction. This is a new reality that will soon become available Bookmark this so you don't forget to create your ideal girl using AI

Bober_smart

103,139 次观看 • 1 个月前

🚨 BREAKING: President Trump announces he will be appointing a HIGH IQ "AI CZAR" and launches the "AI FORCE" Trump says we will UNLEASH AI and that the propaganda will fail All of this will be geared towards not only BUSTING anti-AI hoaxes but keeping America number one. LET'S GO! 🔥 "I am forming the AI Force, much like I did Space Force, which has been a tremendous SUCCESS, in my First Term. To that end, I will be announcing, in the near future, the AI “Czar” — Only High I.Q. individuals need apply! AI is the next Industrial Revolution, or Internet, but will be even larger and more impactful, possibly as much as 25% of our Country’s GDP. We are leading China, and the rest of the World, and I intend to keep it that way!" "Over the years, there have been many Hoaxes, all generated by the Radical Left Dumocrats, for purposes of destroying our Country. RUSSIA, RUSSIA, RUSSIA, UKRAINE, UKRAINE, UKRAINE, Global Warming, Impeachment Hoax 1, Impeachment Hoax 2..." "Now, the decimation, or destruction, of AI, commonly known as Artificial Intelligence — And I, as President of the United States, will not stand by and let this happen." "It all began with an attack on our Data Centers, until people realized how wealthy and prestigious they were for the Communities in which they were built." "Higher Salaries, Lower Taxes, and Safer Streets, was the result, and the crazed Data Center attack has largely failed, so now, in much the same way as they changed the term “Global Warming” to “Climate Change,” in that it covers a much larger “territory” of doubt, they are going straight at AI. We will not in any way hinder or stifle the Growth of this incredible Industry." "Rather, we will cherish it, help it, and watch over it, as it grows! However, we will also be looking for BAD, and we can do that, very easily, with our already existing Criminal and Civil Justice System."

🚨 BREAKING: President Trump announces he will be appointing a HIGH IQ "AI CZAR" and launches the "AI FORCE" Trump says we will UNLEASH AI and that the propaganda will fail All of this will be geared towards not only BUSTING anti-AI hoaxes but keeping America number one. LET'S GO! 🔥 "I am forming the AI Force, much like I did Space Force, which has been a tremendous SUCCESS, in my First Term. To that end, I will be announcing, in the near future, the AI “Czar” — Only High I.Q. individuals need apply! AI is the next Industrial Revolution, or Internet, but will be even larger and more impactful, possibly as much as 25% of our Country’s GDP. We are leading China, and the rest of the World, and I intend to keep it that way!" "Over the years, there have been many Hoaxes, all generated by the Radical Left Dumocrats, for purposes of destroying our Country. RUSSIA, RUSSIA, RUSSIA, UKRAINE, UKRAINE, UKRAINE, Global Warming, Impeachment Hoax 1, Impeachment Hoax 2..." "Now, the decimation, or destruction, of AI, commonly known as Artificial Intelligence — And I, as President of the United States, will not stand by and let this happen." "It all began with an attack on our Data Centers, until people realized how wealthy and prestigious they were for the Communities in which they were built." "Higher Salaries, Lower Taxes, and Safer Streets, was the result, and the crazed Data Center attack has largely failed, so now, in much the same way as they changed the term “Global Warming” to “Climate Change,” in that it covers a much larger “territory” of doubt, they are going straight at AI. We will not in any way hinder or stifle the Growth of this incredible Industry." "Rather, we will cherish it, help it, and watch over it, as it grows! However, we will also be looking for BAD, and we can do that, very easily, with our already existing Criminal and Civil Justice System."

Eric Daugherty

191,567 次观看 • 6 天前

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it

iamigorekk

22,205 次观看 • 1 个月前

🦔I wanted to share a compilation that I saw of residents recording what data centers sound like from their neighborhoods. The hum runs 24 hours a day, 7 days a week. I've covered the community side of the buildout before with the Gilroy and Pecos County projects, but hearing it is different than reading about it. My Take The people in these videos didn't sign up for a 24-hour industrial hum so that AI companies can train their next model. They weren't asked, and in a lot of cases they weren't even told until construction started. The buildout gets measured in gigawatts and billions of dollars on earnings calls. On the ground it gets measured in sleep you don't get and a home you can't sell. I've posted a lot of numbers this year about the AI boom. This is what those numbers sound like. Hedgie🤗

🦔I wanted to share a compilation that I saw of residents recording what data centers sound like from their neighborhoods. The hum runs 24 hours a day, 7 days a week. I've covered the community side of the buildout before with the Gilroy and Pecos County projects, but hearing it is different than reading about it. My Take The people in these videos didn't sign up for a 24-hour industrial hum so that AI companies can train their next model. They weren't asked, and in a lot of cases they weren't even told until construction started. The buildout gets measured in gigawatts and billions of dollars on earnings calls. On the ground it gets measured in sleep you don't get and a home you can't sell. I've posted a lot of numbers this year about the AI boom. This is what those numbers sound like. Hedgie🤗

Hedgie

22,945 次观看 • 1 个月前