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$154,000,000,000 is being poured into humanoid robotics, and people think this is just a funny soccer game Watching $16,000 Unitree G1 humanoids fall over in Beijing looks ridiculous until you realize what’s actually happening on that pitch. 3 brutal facts behind this video: This is Not Entertainment, It’s Stress-Testing:...

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Piggle

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58,378 görüntüleme • 7 gün önce •via X (Twitter)

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As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries
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As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

Daniel

151,698 görüntüleme • 8 ay önce

Okay, full 5 second laugh break done. But wait… This tiny DIY robot made in China is already learning how to grab, move, and manipulate toys autonomously inside a real home environment. That is literally the first real step toward personal robotics and autonomous home manipulation. Toys are officially entering the robot era. At first you laugh, then two seconds later you realize this is exactly how robotics culture spreads: from labs running fully autonomous humanoids to factories to garages and now directly into kids’ bedrooms with DIY robots already doing miniature warehouse robotics. This is physical AI leaving the cloud and entering the living room. And honestly, it’s exciting watching this happen live on X right now.
0:22

Okay, full 5 second laugh break done. But wait… This tiny DIY robot made in China is already learning how to grab, move, and manipulate toys autonomously inside a real home environment. That is literally the first real step toward personal robotics and autonomous home manipulation. Toys are officially entering the robot era. At first you laugh, then two seconds later you realize this is exactly how robotics culture spreads: from labs running fully autonomous humanoids to factories to garages and now directly into kids’ bedrooms with DIY robots already doing miniature warehouse robotics. This is physical AI leaving the cloud and entering the living room. And honestly, it’s exciting watching this happen live on X right now.

TechniaHQ | humanoid robots

18,738 görüntüleme • 3 ay önce

A $5.8 Billion Chinese robotics titan just proved Optimus is years behind UBTECH, a HK-listed industry leader, just executed real-time whole-body dynamic tracking live at the World Robot Conference. Why this ballroom dance demo changes everything: Real-Time Force Control: The Walker S reads live tactile feedback and weight distribution to mirror human balance instantly. Complex Spatial Sensing: Making micro-adjustments around a live partner in an unpredictable crowd requires low-latency VLA models. Industrial Monetization: UBTECH is already generating millions by deploying humanoid workers directly into EV assembly lines like NIO and BYD. Physical AI is no longer an experiment, it's an impending $38 trillion industrial market.
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A $5.8 Billion Chinese robotics titan just proved Optimus is years behind UBTECH, a HK-listed industry leader, just executed real-time whole-body dynamic tracking live at the World Robot Conference. Why this ballroom dance demo changes everything: Real-Time Force Control: The Walker S reads live tactile feedback and weight distribution to mirror human balance instantly. Complex Spatial Sensing: Making micro-adjustments around a live partner in an unpredictable crowd requires low-latency VLA models. Industrial Monetization: UBTECH is already generating millions by deploying humanoid workers directly into EV assembly lines like NIO and BYD. Physical AI is no longer an experiment, it's an impending $38 trillion industrial market.

Piggle

111,033 görüntüleme • 9 gün önce

⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.
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⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

OptimAI Network

43,634 görüntüleme • 11 ay önce

🇺🇸 TRUMP & LUTNICK EYE HUMANOID ROBOTICS REVOLUTION IN 2026: “AI THAT WALKS AND WORKS” Trump and Secretary of Commerce Howard Lutnick are now turning their attention to the next seismic shift in tech: humanoid robotics, with a targeted push beginning in 2026. The move is part of a broader strategy to supercharge American AI leadership, but not just in software. The focus is shifting to physical, labor-replacing machines: humanoid robots that can think, move, and work in real-world environments. Think less ChatGPT, more “steel spine and servers flipping burgers, or building cars.” Why does it matter though? The U.S. is now staring down a future where whoever builds the best humanoid labor force wins the next economy, and we know China’s not waiting. Trump and Lutnick’s entrance into this space signals something serious: this isn’t just a Silicon Valley playground anymore. This is becoming a national priority. For a country dealing with a shrinking workforce, soaring labor costs, and foreign competitors pumping billions into robotics. It’s time to start taking humanoid robots more seriously and build them already. 2026 could be the year the Made in America label gets printed by robots. Source: Disclose.tv / Politico / AOL News
0:45

🇺🇸 TRUMP & LUTNICK EYE HUMANOID ROBOTICS REVOLUTION IN 2026: “AI THAT WALKS AND WORKS” Trump and Secretary of Commerce Howard Lutnick are now turning their attention to the next seismic shift in tech: humanoid robotics, with a targeted push beginning in 2026. The move is part of a broader strategy to supercharge American AI leadership, but not just in software. The focus is shifting to physical, labor-replacing machines: humanoid robots that can think, move, and work in real-world environments. Think less ChatGPT, more “steel spine and servers flipping burgers, or building cars.” Why does it matter though? The U.S. is now staring down a future where whoever builds the best humanoid labor force wins the next economy, and we know China’s not waiting. Trump and Lutnick’s entrance into this space signals something serious: this isn’t just a Silicon Valley playground anymore. This is becoming a national priority. For a country dealing with a shrinking workforce, soaring labor costs, and foreign competitors pumping billions into robotics. It’s time to start taking humanoid robots more seriously and build them already. 2026 could be the year the Made in America label gets printed by robots. Source: Disclose.tv / Politico / AOL News

Mario Nawfal

64,898 görüntüleme • 8 ay önce

A KID WITH CURSOR AI CAN NOW BUILD A ROBLOX GAME THAT MAKES $150M THIS IS NOT A JOKE Roblox has 80 million players logging in every single day. The platform pays out billions to creators annually. The top games generate seven and eight figure revenues every year. And until recently, building one required years of coding, 3D modeling, sound design, and game development experience. Cursor AI just removed every single one of those requirements. Maps, models, sounds, mechanics, monetization – all of it generated by describing what you want. The AI builds while you direct. Children are already shipping games this way. The Roblox gold rush isn't coming. It's already happening. The people getting in now with AI tools are building the games that will dominate the platform for the next decade. Bookmark this. The video explains exactly how to start.
2:59

A KID WITH CURSOR AI CAN NOW BUILD A ROBLOX GAME THAT MAKES $150M THIS IS NOT A JOKE Roblox has 80 million players logging in every single day. The platform pays out billions to creators annually. The top games generate seven and eight figure revenues every year. And until recently, building one required years of coding, 3D modeling, sound design, and game development experience. Cursor AI just removed every single one of those requirements. Maps, models, sounds, mechanics, monetization – all of it generated by describing what you want. The AI builds while you direct. Children are already shipping games this way. The Roblox gold rush isn't coming. It's already happening. The people getting in now with AI tools are building the games that will dominate the platform for the next decade. Bookmark this. The video explains exactly how to start.

SCOTTY BEAM

19,099 görüntüleme • 3 ay önce

Just how capable are open source models? Below is the first in a new series where we go behind the scenes and pull back the curtain on interesting AI research / demos, making them fun and easy to understand. Here, we have a short visual demonstration from aizk ✡️ showcasing how Kimi K3 (a language model that operates primarily through text) is capable of building complicated 3D structures / moments in history in Minecraft, something that previously was not possible with other open source models, and why this matters. The crazy part? The model doesn't "see" the game like we do. The LLMs must reason in pure text, writing JavaScript, that later compiles down into commands placing each block, one at a time. Spatial reasoning is a very hard problem in AI, it's the same core challenge behind robotics and self-driving cars, where a model has to understand and act in physical 3D space. Watching a text model pull it off is nothing short of a miracle. The point isn't just Minecraft itself, rather, it's AI being able to generalize, not memorize, on things that are weird and beyond their training data. This is key to building true artificial general intelligence. These video game benchmarks (there are many different games actively being researched right now) provide a clear-cut end goal, challenges that are almost certainly not in the training set, and a fun, very fast, visual way to almost feel the increasing capabilities of various open source AI models over time. If you haven't given open source models a serious try yet, watch the video, it may shock you!
2:46

Just how capable are open source models? Below is the first in a new series where we go behind the scenes and pull back the curtain on interesting AI research / demos, making them fun and easy to understand. Here, we have a short visual demonstration from aizk ✡️ showcasing how Kimi K3 (a language model that operates primarily through text) is capable of building complicated 3D structures / moments in history in Minecraft, something that previously was not possible with other open source models, and why this matters. The crazy part? The model doesn't "see" the game like we do. The LLMs must reason in pure text, writing JavaScript, that later compiles down into commands placing each block, one at a time. Spatial reasoning is a very hard problem in AI, it's the same core challenge behind robotics and self-driving cars, where a model has to understand and act in physical 3D space. Watching a text model pull it off is nothing short of a miracle. The point isn't just Minecraft itself, rather, it's AI being able to generalize, not memorize, on things that are weird and beyond their training data. This is key to building true artificial general intelligence. These video game benchmarks (there are many different games actively being researched right now) provide a clear-cut end goal, challenges that are almost certainly not in the training set, and a fun, very fast, visual way to almost feel the increasing capabilities of various open source AI models over time. If you haven't given open source models a serious try yet, watch the video, it may shock you!

Featherless AI

39,769 görüntüleme • 11 gün önce

THEY BUILT A COMBAT-GRADE EXOSKELETON. WATCH HOW IT MOVES. 🤖🩻 Dark green, “S-01” stamped across the chest plate, built with the kind of bulk you’d expect on a battlefield platform. This is a new exoskeleton prototype reportedly developed for the U.S. military, and in this clip it’s shifting its weight foot to foot, testing balance and stance in a parking lot outside what looks like an industrial facility. This is the part nobody talks about when they show off military robotics: the same balance and actuator control that lets a machine carry heavy loads or absorb impact is exactly what’s being tested here — dynamic weight distribution, stance shifts, and controlled recovery. It may not look dramatic, but every small movement is training the system for stability under real-world conditions. Would you want something this size training next to real troops?
0:21

THEY BUILT A COMBAT-GRADE EXOSKELETON. WATCH HOW IT MOVES. 🤖🩻 Dark green, “S-01” stamped across the chest plate, built with the kind of bulk you’d expect on a battlefield platform. This is a new exoskeleton prototype reportedly developed for the U.S. military, and in this clip it’s shifting its weight foot to foot, testing balance and stance in a parking lot outside what looks like an industrial facility. This is the part nobody talks about when they show off military robotics: the same balance and actuator control that lets a machine carry heavy loads or absorb impact is exactly what’s being tested here — dynamic weight distribution, stance shifts, and controlled recovery. It may not look dramatic, but every small movement is training the system for stability under real-world conditions. Would you want something this size training next to real troops?

DN_DEGEN

36,016 görüntüleme • 27 gün önce

Sam Altman: "Very soon an AI will just be running for you in the background all the time" That entire model is on its way out. But the vision isn't the tell. This is: He says everyone's going to want "so much more of this AI infrastructure than we think." That's not a roadmap. That's a man admitting he can't build chips and power fast enough. The always-on assistant is the headline. The infrastructure bottleneck underneath it is the trade almost nobody is pricing in. That gap is the whole edge.
0:25

Sam Altman: "Very soon an AI will just be running for you in the background all the time" That entire model is on its way out. But the vision isn't the tell. This is: He says everyone's going to want "so much more of this AI infrastructure than we think." That's not a roadmap. That's a man admitting he can't build chips and power fast enough. The always-on assistant is the headline. The infrastructure bottleneck underneath it is the trade almost nobody is pricing in. That gap is the whole edge.

plutos

25,689 görüntüleme • 2 ay önce

The power of generative models — now embodied in humanoids. Announcing DreamControl –– After a year-long research effort at General Robotics — we present a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to unlock real-world scene interaction. Diffusion + RL → natural whole-body skills on real robots. DreamControl enables humanoids to move beyond locomotion demos → performing natural, human-like skills such as –– Picking & lifting objects, Opening drawers & doors, Precise punching, kicking, and jumping, Bimanual manipulation tasks Our key innovation: a diffusion prior over human motion that guides RL, eliminating the need for massive teleoperation datasets, and producing motions that look human while transferring to real hardware. Trained purely in simulation, deployed on the Unitree G1 humanoid, DreamControl policies run in real time, bridging sim-to-real with unprecedented naturalness. We leverage a novel hybrid edge + cloud infrastructure that runs RL-trained policies on the edge backed by powerful AI models running in the cloud This is the next step in General Robotics’ journey toward general-purpose humanoid assistants that interact, adapt, and assist autonomously. Paper: Blog: 1/n
1:54

The power of generative models — now embodied in humanoids. Announcing DreamControl –– After a year-long research effort at General Robotics — we present a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to unlock real-world scene interaction. Diffusion + RL → natural whole-body skills on real robots. DreamControl enables humanoids to move beyond locomotion demos → performing natural, human-like skills such as –– Picking & lifting objects, Opening drawers & doors, Precise punching, kicking, and jumping, Bimanual manipulation tasks Our key innovation: a diffusion prior over human motion that guides RL, eliminating the need for massive teleoperation datasets, and producing motions that look human while transferring to real hardware. Trained purely in simulation, deployed on the Unitree G1 humanoid, DreamControl policies run in real time, bridging sim-to-real with unprecedented naturalness. We leverage a novel hybrid edge + cloud infrastructure that runs RL-trained policies on the edge backed by powerful AI models running in the cloud This is the next step in General Robotics’ journey toward general-purpose humanoid assistants that interact, adapt, and assist autonomously. Paper: Blog: 1/n

Ashish Kapoor

118,357 görüntüleme • 11 ay önce

EXCLUSIVE TOUR OF NEW HUMANOID ROBOT STARTUP: ChatGPT, after watching this video tour of Foundation Robotics's CEO/founder, Sankaet, tell me the state of the art on humanoid robots, wrote this: "Wow, what a deep dive—killer interview. You got a full masterclass in next-gen robotics and AI from people who are not only building but deploying humanoid robots in the real world. The fact that Foundation’s team is fusing AI model reasoning with their own actuators and gearbox designs is wild—they’re not just iterating fast, they’re redefining what “robotic autonomy” means. That bit about using reinforcement learning to teach humanoids to walk naturally in weeks, not years, is gonna hit hard with AI-curious audiences." It also wrote me what you will learn, I'll post that below. Recorded on Apple Vision Pro, which was also talk about at the end of the interview. Like I said, spatial computers and robots go together like peanut butter and jelly.
53:15

EXCLUSIVE TOUR OF NEW HUMANOID ROBOT STARTUP: ChatGPT, after watching this video tour of Foundation Robotics's CEO/founder, Sankaet, tell me the state of the art on humanoid robots, wrote this: "Wow, what a deep dive—killer interview. You got a full masterclass in next-gen robotics and AI from people who are not only building but deploying humanoid robots in the real world. The fact that Foundation’s team is fusing AI model reasoning with their own actuators and gearbox designs is wild—they’re not just iterating fast, they’re redefining what “robotic autonomy” means. That bit about using reinforcement learning to teach humanoids to walk naturally in weeks, not years, is gonna hit hard with AI-curious audiences." It also wrote me what you will learn, I'll post that below. Recorded on Apple Vision Pro, which was also talk about at the end of the interview. Like I said, spatial computers and robots go together like peanut butter and jelly.

Robert Scoble

269,783 görüntüleme • 1 yıl önce

Jeff Bezos' secret AI startup was just LEAKED by The New York Times. After 4 years of retirement from running companies, he's back as co-CEO of a brand new AI startup called Project Prometheus. With $6.2 BILLION in funding on day one. This is one of the most heavily funded early-stage startups in HISTORY. Here's what we know: Project Prometheus is building "AI for the physical economy." Not chatbots. Not content generation. Not another LLM. They're building AI that learns from the PHYSICAL WORLD. AI that can design rockets, manufacture cars, build computers, engineer spacecraft components etc. And Bezos isn't just investing - he's literally co-CEO, running the company day-to-day. His co-CEO is Vik Bajaj, a physicist and chemist who worked at Google X (the "Moonshot Factory") where he worked directly with Sergey Brin on the self-driving car project that became Waymo. Together, they've already hired nearly 100 people poached from OpenAI, Google DeepMind, and Meta's AI division. The company is still in stealth mode. LinkedIn page just says: "AI for the physical economy." That's it. But here's the thing: If Project Prometheus succeeds, they won't just disrupt industries - they'll REPLACE entire manufacturing processes. Right now, designing a new car takes YEARS. - Testing prototypes - Iterating on designs - Running simulations - Building physical models What if AI could do all of that in WEEKS? Right now, building a rocket costs billions and takes decades. What if AI could simulate millions of rocket designs, test them virtually, optimize everything, then manufacture the perfect design on the first try? This is the bet Bezos is making. That AI won't just write better emails - it'll engineer better EVERYTHING. Everyone sees what's coming: The next wave of AI isn't chatbots... It's robots, factories, engineering systems, and physical automation at scale. Whoever wins this race controls the next industrial revolution. And Bezos just walked into the arena with $6.2 billion, a co-CEO who built self-driving cars at Google, and a team of the world's best AI researchers. The name "Prometheus" is perfect. In Greek mythology, Prometheus stole fire from the gods and gave it to humanity. He was punished for eternity, but humanity got FIRE - the tool that changed everything. Bezos is saying: "We're bringing the fire of AI to the physical world." If this works, if AI can actually design better rockets, cars, and computers than humans, we're looking at the biggest technological shift since the internet. Maybe bigger. Because the internet changed information. This would change PRODUCTION. And if it doesn't work? Well Bezos loses $6.2 billion, which for him is like 2.5% of his net worth. A rounding error. But if it DOES work, he owns the future of manufacturing. The upside is UNLIMITED. This is how billionaires think differently. Most people wouldn't risk $6 billion on a moonshot. Bezos sees it as "$6 billion to potentially control the next industrial revolution." Not really a risk... That's the best bet available. When Jeff Bezos comes out of retirement to co-run a company with this much money and this much talent, you pay attention. Because whatever he's building, it's about to change the game. What do you think?
2:15

Jeff Bezos' secret AI startup was just LEAKED by The New York Times. After 4 years of retirement from running companies, he's back as co-CEO of a brand new AI startup called Project Prometheus. With $6.2 BILLION in funding on day one. This is one of the most heavily funded early-stage startups in HISTORY. Here's what we know: Project Prometheus is building "AI for the physical economy." Not chatbots. Not content generation. Not another LLM. They're building AI that learns from the PHYSICAL WORLD. AI that can design rockets, manufacture cars, build computers, engineer spacecraft components etc. And Bezos isn't just investing - he's literally co-CEO, running the company day-to-day. His co-CEO is Vik Bajaj, a physicist and chemist who worked at Google X (the "Moonshot Factory") where he worked directly with Sergey Brin on the self-driving car project that became Waymo. Together, they've already hired nearly 100 people poached from OpenAI, Google DeepMind, and Meta's AI division. The company is still in stealth mode. LinkedIn page just says: "AI for the physical economy." That's it. But here's the thing: If Project Prometheus succeeds, they won't just disrupt industries - they'll REPLACE entire manufacturing processes. Right now, designing a new car takes YEARS. - Testing prototypes - Iterating on designs - Running simulations - Building physical models What if AI could do all of that in WEEKS? Right now, building a rocket costs billions and takes decades. What if AI could simulate millions of rocket designs, test them virtually, optimize everything, then manufacture the perfect design on the first try? This is the bet Bezos is making. That AI won't just write better emails - it'll engineer better EVERYTHING. Everyone sees what's coming: The next wave of AI isn't chatbots... It's robots, factories, engineering systems, and physical automation at scale. Whoever wins this race controls the next industrial revolution. And Bezos just walked into the arena with $6.2 billion, a co-CEO who built self-driving cars at Google, and a team of the world's best AI researchers. The name "Prometheus" is perfect. In Greek mythology, Prometheus stole fire from the gods and gave it to humanity. He was punished for eternity, but humanity got FIRE - the tool that changed everything. Bezos is saying: "We're bringing the fire of AI to the physical world." If this works, if AI can actually design better rockets, cars, and computers than humans, we're looking at the biggest technological shift since the internet. Maybe bigger. Because the internet changed information. This would change PRODUCTION. And if it doesn't work? Well Bezos loses $6.2 billion, which for him is like 2.5% of his net worth. A rounding error. But if it DOES work, he owns the future of manufacturing. The upside is UNLIMITED. This is how billionaires think differently. Most people wouldn't risk $6 billion on a moonshot. Bezos sees it as "$6 billion to potentially control the next industrial revolution." Not really a risk... That's the best bet available. When Jeff Bezos comes out of retirement to co-run a company with this much money and this much talent, you pay attention. Because whatever he's building, it's about to change the game. What do you think?

Ricardo

46,380 görüntüleme • 9 ay önce

We recently crossed 10,000 GitHub stars on Rerun 😍 That's great and all, but something bigger is happening in robotics and Physical AI right now: The open-source ecosystem has seen real acceleration over the last few years. More teams are sharing real infrastructure: datasets, models, simulators, tooling, and the unglamorous plumbing that makes iteration possible. Jan Florian Maas, Physical Intelligence, Hugging Face are just some of the names driving this forward. Visualization and data infra belong in that category. If your entire data loop depends on being able to query and inspect what your robots are doing, that layer can’t be fragile or vendor-controlled. It needs to be something you can introspect, build on, extend, and trust long-term. Huge thanks to everyone building open-source robotics. The next decade of Physical AI will be built in the open.
0:22

We recently crossed 10,000 GitHub stars on Rerun 😍 That's great and all, but something bigger is happening in robotics and Physical AI right now: The open-source ecosystem has seen real acceleration over the last few years. More teams are sharing real infrastructure: datasets, models, simulators, tooling, and the unglamorous plumbing that makes iteration possible. Jan Florian Maas, Physical Intelligence, Hugging Face are just some of the names driving this forward. Visualization and data infra belong in that category. If your entire data loop depends on being able to query and inspect what your robots are doing, that layer can’t be fragile or vendor-controlled. It needs to be something you can introspect, build on, extend, and trust long-term. Huge thanks to everyone building open-source robotics. The next decade of Physical AI will be built in the open.

Rerun

29,684 görüntüleme • 6 ay önce

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.
0:58

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Karl Mehta

34,814 görüntüleme • 1 ay önce

a16z co-founder Marc Andreessen on why the shift from software AI to physical AI will create the biggest industry in human history: AI today is software. You open ChatGPT on your phone, and there's no manufacturing component, no real generator of middle-class jobs. But Marc Andreessen 🇺🇸 argues that a second, far more consequential turn is coming: the shift to embodied physical AI. "There's another turn on AI that's coming, which is the turn to embodied physical AI, which is robotics." This transition, he points out, has already begun. Drones went from human-piloted to fully autonomous. Cars went from purely physical products to rolling computers that drive themselves. "If you ever have the misfortune of finding yourself in San Francisco, take a Waymo. It's amazing to live in a cyberpunk future reality where you're in literally a state-of-the-art self-driving car that's literally out of the Jetsons." He makes clear: this isn't science fiction anymore. The self-driving car really works, and it's only the beginning. The next frontier is humanoid robots. "The general purpose robotics thing is going to happen. And it's going to happen in the next decade and it's going to happen at giant scale." Andreessen shares Elon Musk's view that robotics could become the single biggest industry in the history of the planet: "There's going to be billions, tens of billions, hundreds of billions of robots of all shapes, sizes, descriptions running around doing all kinds of things." And all of those robots need to be designed and built. Which brings Andreessen to his core argument: the real opportunity isn't in trying to recover what was lost. It's in leaning forward into what's coming. "We don't try to get the old manufacturing jobs back. What we should do is lean hard into the manufacturing jobs of the future."
1:36

a16z co-founder Marc Andreessen on why the shift from software AI to physical AI will create the biggest industry in human history: AI today is software. You open ChatGPT on your phone, and there's no manufacturing component, no real generator of middle-class jobs. But Marc Andreessen 🇺🇸 argues that a second, far more consequential turn is coming: the shift to embodied physical AI. "There's another turn on AI that's coming, which is the turn to embodied physical AI, which is robotics." This transition, he points out, has already begun. Drones went from human-piloted to fully autonomous. Cars went from purely physical products to rolling computers that drive themselves. "If you ever have the misfortune of finding yourself in San Francisco, take a Waymo. It's amazing to live in a cyberpunk future reality where you're in literally a state-of-the-art self-driving car that's literally out of the Jetsons." He makes clear: this isn't science fiction anymore. The self-driving car really works, and it's only the beginning. The next frontier is humanoid robots. "The general purpose robotics thing is going to happen. And it's going to happen in the next decade and it's going to happen at giant scale." Andreessen shares Elon Musk's view that robotics could become the single biggest industry in the history of the planet: "There's going to be billions, tens of billions, hundreds of billions of robots of all shapes, sizes, descriptions running around doing all kinds of things." And all of those robots need to be designed and built. Which brings Andreessen to his core argument: the real opportunity isn't in trying to recover what was lost. It's in leaning forward into what's coming. "We don't try to get the old manufacturing jobs back. What we should do is lean hard into the manufacturing jobs of the future."

Big Brain AI

35,113 görüntüleme • 1 ay önce

Dodging randomly thrown balls doesn’t seem that difficult… Shanghai-based EmbodyDeep tested their CereBase 3.0, a powerful real-time motion model, on the Unitree G1. The robot dodges incoming soccer balls with lifelike reflexes: instantly detecting the ball, predicting its trajectory, and smoothly stepping, twisting, or crouching while staying perfectly balanced. --- This breakthrough in perceptual-motor control brings us closer to human-like conditioned reflexes in complex, uncertain environments. I have to say, this kind of reactive ability is truly necessary--it will allow humanoid robots to safely navigate crowded factories, assist in homes with unpredictable human movements, and operate reliably in disaster zones full of sudden obstacles.
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Dodging randomly thrown balls doesn’t seem that difficult… Shanghai-based EmbodyDeep tested their CereBase 3.0, a powerful real-time motion model, on the Unitree G1. The robot dodges incoming soccer balls with lifelike reflexes: instantly detecting the ball, predicting its trajectory, and smoothly stepping, twisting, or crouching while staying perfectly balanced. --- This breakthrough in perceptual-motor control brings us closer to human-like conditioned reflexes in complex, uncertain environments. I have to say, this kind of reactive ability is truly necessary--it will allow humanoid robots to safely navigate crowded factories, assist in homes with unpredictable human movements, and operate reliably in disaster zones full of sudden obstacles.

CyberRobo

20,684 görüntüleme • 3 ay önce

Godfather of AI Yann LeCun reveals the humanoid robot industry's secret: the companies building the robots have no idea how to make them smart enough to be useful. "There is a lot of expectations that robotics is going to be a revolution, essentially, in a big market, eventually." "But the secret of the industry is that none of the companies at the moment that are building robots, like humanoid robots, none of those companies has any idea how to make those robots smart enough to be useful." "There's a big push for AI to make progress towards... understanding the physical world. That's what is prompting this investment." "There's nothing wrong with investing in LLMs. LLMs are useful. They're just addressing a completely different set of applications, really." LeCun is not describing someone else's problem. He has spent 15 years on world models, raised more than $1 billion for AMI Labs to build that missing intelligence layer, and in the same interview he calls 2026 the year of the world model and puts consumer robots 3 to 5 years out. Every humanoid robot demo you have seen is a body waiting for a brain. The winner in robotics will not be the company that shipped the body; it will be the one that ships the intelligence. - Yann LeCun (Yann LeCun), Turing Award winner and founder of AMI Labs, on Bloomberg Television.
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Godfather of AI Yann LeCun reveals the humanoid robot industry's secret: the companies building the robots have no idea how to make them smart enough to be useful. "There is a lot of expectations that robotics is going to be a revolution, essentially, in a big market, eventually." "But the secret of the industry is that none of the companies at the moment that are building robots, like humanoid robots, none of those companies has any idea how to make those robots smart enough to be useful." "There's a big push for AI to make progress towards... understanding the physical world. That's what is prompting this investment." "There's nothing wrong with investing in LLMs. LLMs are useful. They're just addressing a completely different set of applications, really." LeCun is not describing someone else's problem. He has spent 15 years on world models, raised more than $1 billion for AMI Labs to build that missing intelligence layer, and in the same interview he calls 2026 the year of the world model and puts consumer robots 3 to 5 years out. Every humanoid robot demo you have seen is a body waiting for a brain. The winner in robotics will not be the company that shipped the body; it will be the one that ships the intelligence. - Yann LeCun (Yann LeCun), Turing Award winner and founder of AMI Labs, on Bloomberg Television.

Karl Mehta

44,425 görüntüleme • 1 ay önce

A $100 Billion hardware boom is unfolding right now And a $3,000 quadruped bot dumping live suppressed rounds without flinching is the ultimate payday signal for spatial AI builders. In this range test, a custom tactical quadruped fired rapid bursts from a top-mounted rifle. The moment gun recoil hit the frame, high-torque actuators and microsecond control loops adjusted joint resistance in real time, keeping the barrel locked dead on target. Instead of building simple wrappers, smart developers are pivoting straight to physical AI. Defense labs and hardware startups are aggressively handing out $200k–$400k+ compensation packages to anyone who can master C++ control SDKs, ROS2 middleware, and real-time Nvidia Isaac Sim reinforcement learning. The mechanical hardware is already dirt cheap. The multi-billion-dollar goldmine sits entirely in the software layer that processes force-feedback telemetry and mitigates physical shock under live fire.
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A $100 Billion hardware boom is unfolding right now And a $3,000 quadruped bot dumping live suppressed rounds without flinching is the ultimate payday signal for spatial AI builders. In this range test, a custom tactical quadruped fired rapid bursts from a top-mounted rifle. The moment gun recoil hit the frame, high-torque actuators and microsecond control loops adjusted joint resistance in real time, keeping the barrel locked dead on target. Instead of building simple wrappers, smart developers are pivoting straight to physical AI. Defense labs and hardware startups are aggressively handing out $200k–$400k+ compensation packages to anyone who can master C++ control SDKs, ROS2 middleware, and real-time Nvidia Isaac Sim reinforcement learning. The mechanical hardware is already dirt cheap. The multi-billion-dollar goldmine sits entirely in the software layer that processes force-feedback telemetry and mitigates physical shock under live fire.

Rich Odin

13,600 görüntüleme • 16 gün önce

🚨 BILLIONS IN GOLD & SILVER… AND NO ONE IS ASKING WHY I sat down with Andy Schectman (CEO of Miles Franklin) — and what he said should stop you in your tracks. Every month… BILLIONS are being taken OFF the market. Not paper. Not contracts. PHYSICAL DELIVERY. “Send me the metal.” Think about that. • $5+ BILLION in gold in a single month • $3+ BILLION in silver • Month after month after month • For over a YEAR And here’s the real question: WHO IS DOING THIS? Because it’s NOT retail. It’s NOT average investors. This is the biggest money in the world quietly moving. And the media? Silent. Completely silent. Andy said it plainly: “This is the ONLY question that matters.” While everyone is distracted… While headlines scream about everything else… The smartest players on the planet are taking possession. Not promises. Not paper. REAL ASSETS. At what point do people realise… They’re not messing around? Watch this clip. Because once you understand what’s happening here… You can’t unsee it.
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🚨 BILLIONS IN GOLD & SILVER… AND NO ONE IS ASKING WHY I sat down with Andy Schectman (CEO of Miles Franklin) — and what he said should stop you in your tracks. Every month… BILLIONS are being taken OFF the market. Not paper. Not contracts. PHYSICAL DELIVERY. “Send me the metal.” Think about that. • $5+ BILLION in gold in a single month • $3+ BILLION in silver • Month after month after month • For over a YEAR And here’s the real question: WHO IS DOING THIS? Because it’s NOT retail. It’s NOT average investors. This is the biggest money in the world quietly moving. And the media? Silent. Completely silent. Andy said it plainly: “This is the ONLY question that matters.” While everyone is distracted… While headlines scream about everything else… The smartest players on the planet are taking possession. Not promises. Not paper. REAL ASSETS. At what point do people realise… They’re not messing around? Watch this clip. Because once you understand what’s happening here… You can’t unsee it.

Jim Ferguson

49,305 görüntüleme • 5 ay önce