Loading video...

Video Failed to Load

Go Home

Ever wondered how an NVIDIA Keynote comes together from an art design perspective? 🤔 Check out the workflow the NVIDIA creative team used at CES 2026 to create a 12K, 20-robot on-stage scene — powered by @Weavy_ai, Blender 🔶, Google DeepMind, Hyper3D by Deemos, OpenAI. 📺 Watch now:

NVIDIAAI's profile picture

NVIDIA AI

298,098 subscribers

12,572 views • 6 months ago •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Master Total War: PHARAOH with an AI Advisor powered by NVIDIA ACE. See how Creative Assembly’s R&D team is exploring new onboarding experiences by enhancing the in-game Advisor with NVIDIA ACE, helping guide players on their journey to becoming a powerful Bronze-Age ruler.
1:57

Master Total War: PHARAOH with an AI Advisor powered by NVIDIA ACE. See how Creative Assembly’s R&D team is exploring new onboarding experiences by enhancing the in-game Advisor with NVIDIA ACE, helping guide players on their journey to becoming a powerful Bronze-Age ruler.

NVIDIA GeForce

40,616 views • 7 months ago

AI is becoming a new computing model for media and entertainment. At the 2026 Runway AI Summit, NVIDIA’s Richard Kerris explored how real-time generative AI can make creative production a live, artist-controlled process. Powered by NVIDIA Vera Rubin, Runway brought Gen-4.5 to its platform in one day, helping close the gap between imagining a scene and bringing it to life.
1:03

AI is becoming a new computing model for media and entertainment. At the 2026 Runway AI Summit, NVIDIA’s Richard Kerris explored how real-time generative AI can make creative production a live, artist-controlled process. Powered by NVIDIA Vera Rubin, Runway brought Gen-4.5 to its platform in one day, helping close the gap between imagining a scene and bringing it to life.

NVIDIA

206,411 views • 12 days ago

Here we go: Gemini 3.0 is live! Thankfully, I was able to be an early tester. It's the best model I've ever tested - nothing comes even close to it. OpenAI will have a very hard time to keep up with Google, because Gemini 3.0 will now be the benchmark for all future models. I have been invited by Google DeepMind / Google - Thanks to Google DeepMind for the #EarlyAccess Here's a summary of Gemini 3.0 with all the important benchmark evals:
1:56

Here we go: Gemini 3.0 is live! Thankfully, I was able to be an early tester. It's the best model I've ever tested - nothing comes even close to it. OpenAI will have a very hard time to keep up with Google, because Gemini 3.0 will now be the benchmark for all future models. I have been invited by Google DeepMind / Google - Thanks to Google DeepMind for the #EarlyAccess Here's a summary of Gemini 3.0 with all the important benchmark evals:

Chubby♨️

108,611 views • 9 months ago

AI that responds in under 100ms doesn't happen by accident. Together AI VP of Kernels Dan Fu shares how they use NVIDIA CUDA, TensorRT-LLM, Dynamo and Together ATLAS on NVIDIA Blackwell to power ultra-low-latency inference and long context code generation for Cursor. From building megakernels that fuse an entire model's forward pass into a single launch to enabling real-time voice agents, Together AI is optimizing latency at every layer of the stack.
1:51

AI that responds in under 100ms doesn't happen by accident. Together AI VP of Kernels Dan Fu shares how they use NVIDIA CUDA, TensorRT-LLM, Dynamo and Together ATLAS on NVIDIA Blackwell to power ultra-low-latency inference and long context code generation for Cursor. From building megakernels that fuse an entire model's forward pass into a single launch to enabling real-time voice agents, Together AI is optimizing latency at every layer of the stack.

NVIDIA AI Infrastructure

20,633 views • 1 month ago

.weber went from investment banking to VC to working at a coffee shop in New York while studying conceptual art at NYU-ITP, where his work focused on merging AI with art. Then he built FLORA ©: an AI-native creative platform now used by design teams at Nike, Lionsgate, Pentagram, and Netflix, with tons of inbound enterprise interest. The product represents a fundamental rethink of how design works. Today, there's no programming language for creativity. Every step happens manually. Instead of starting at the pixel level and layering up, Flora lets you start with an idea, iterate through prompting across dozens of AI models, and build scalable workflows that design the creative process itself. Then you drop into precision editing only when you're ready. Watch the video to hear the story directly from weber, alex bard and Jordan Segall👇
5:15

.weber went from investment banking to VC to working at a coffee shop in New York while studying conceptual art at NYU-ITP, where his work focused on merging AI with art. Then he built FLORA ©: an AI-native creative platform now used by design teams at Nike, Lionsgate, Pentagram, and Netflix, with tons of inbound enterprise interest. The product represents a fundamental rethink of how design works. Today, there's no programming language for creativity. Every step happens manually. Instead of starting at the pixel level and layering up, Flora lets you start with an idea, iterate through prompting across dozens of AI models, and build scalable workflows that design the creative process itself. Then you drop into precision editing only when you're ready. Watch the video to hear the story directly from weber, alex bard and Jordan Segall👇

Redpoint

24,095 views • 6 months ago

🚨 S&P 500 IS NOT 500 COMPANIES ANYMORE 🚨 Think you're diversified? Look close Five companies make up 28% of the entire index NVIDIA alone is bigger than the whole energy sector And these five aren't independent bets. They're funding each other 1. NVIDIA invests in OpenAI 2. OpenAI pays Amazon 3. Amazon buys NVIDIA chips 4. NVIDIA books revenue 5. Stock pumps 6. Loop repeats That's not growth. That's a closed circuit pretending to be an economy Now look at how fast crashes are getting "fixed": - Dotcom: 1,166 days to recover - COVID: 103 days - 2025 tariffs: 55 days - 2026 Iran conflict: 11 days Every dip trained the market to buy the next one harder But OpenAI is losing $14B a year CAPE ratio is at dotcom levels. Strip out AI and the S&P is 25% lower The index looks healthy. The foundation doesn't Keep it in mind NOTIFS ON!
0:23

🚨 S&P 500 IS NOT 500 COMPANIES ANYMORE 🚨 Think you're diversified? Look close Five companies make up 28% of the entire index NVIDIA alone is bigger than the whole energy sector And these five aren't independent bets. They're funding each other 1. NVIDIA invests in OpenAI 2. OpenAI pays Amazon 3. Amazon buys NVIDIA chips 4. NVIDIA books revenue 5. Stock pumps 6. Loop repeats That's not growth. That's a closed circuit pretending to be an economy Now look at how fast crashes are getting "fixed": - Dotcom: 1,166 days to recover - COVID: 103 days - 2025 tariffs: 55 days - 2026 Iran conflict: 11 days Every dip trained the market to buy the next one harder But OpenAI is losing $14B a year CAPE ratio is at dotcom levels. Strip out AI and the S&P is 25% lower The index looks healthy. The foundation doesn't Keep it in mind NOTIFS ON!

NoName

50,383 views • 3 months ago

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.
1:10

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.

Ricardo

1,616,942 views • 8 months ago

CapCut Design Studio changed the way I think about creating with AI. For a long time, creating with AI felt less like creating and more like managing files—generate, export, switch tools, edit, re-upload, repeat. The ideas were flowing, but the workflow kept getting in the way. What's changing now isn't just image quality, it's the creative process itself. This video shows how I used CapCut Design Studio to build an autumn fashion poster from scratch. I started on the infinite canvas to explore styles, then used the pencil to easily remove unwanted elements and even swap out outfits to find the perfect look for my model. Also, I used the text editing feature to instantly translate my poster into multiple languages without losing the original aesthetic. If I ever need more options, the 'One More' feature automatically creates multiple creative variations with one click. Instead of switching between multiple tools, I was able to keep the entire creative process connected in one place. AI design is moving from "generate and download" to "create, refine, and scale"—and that's the shift I'm most excited about. What's the biggest bottleneck in your current design workflow? #capcutdesignstudio #capcut
0:58

CapCut Design Studio changed the way I think about creating with AI. For a long time, creating with AI felt less like creating and more like managing files—generate, export, switch tools, edit, re-upload, repeat. The ideas were flowing, but the workflow kept getting in the way. What's changing now isn't just image quality, it's the creative process itself. This video shows how I used CapCut Design Studio to build an autumn fashion poster from scratch. I started on the infinite canvas to explore styles, then used the pencil to easily remove unwanted elements and even swap out outfits to find the perfect look for my model. Also, I used the text editing feature to instantly translate my poster into multiple languages without losing the original aesthetic. If I ever need more options, the 'One More' feature automatically creates multiple creative variations with one click. Instead of switching between multiple tools, I was able to keep the entire creative process connected in one place. AI design is moving from "generate and download" to "create, refine, and scale"—and that's the shift I'm most excited about. What's the biggest bottleneck in your current design workflow? #capcutdesignstudio #capcut

Farlane

41,971 views • 2 months ago

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.
1:01

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Ricardo

159,345 views • 3 months ago

Take a practical look at Unreal Engine 5.8's Mesh Terrain by revisiting last week's Inside Unreal livestream, featuring an exploration of the feature with Etienne Carrier! Check it out the VOD and get an insight on how to create terrain that your projects can really mesh with:
0:59

Take a practical look at Unreal Engine 5.8's Mesh Terrain by revisiting last week's Inside Unreal livestream, featuring an exploration of the feature with Etienne Carrier! Check it out the VOD and get an insight on how to create terrain that your projects can really mesh with:

Unreal Engine

21,512 views • 12 days ago

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.
4:31

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

17,092 views • 2 months ago

Etched came out of stealth at $800M and by lunch X had NVIDIA in the ground We do this every few months. A chip launches, the deck says killer, the timeline holds a funeral, and NVIDIA closes green anyway Etched hardwires the transformer into silicon. That is where the speed comes from, nearly the whole die on one job instead of the ~30% a GPU uses. It is also the trap. The day that chip tapes out is the best it will ever be. You cannot patch it. You burned progress into a wafer and now pray the field stops moving NVIDIA made the opposite bet. Same board, faster every quarter in software. Dynamo is pulling more tokens per watt out of the same rack, on version 1.0 The depreciation risk the bears aimed at NVIDIA for two years does not live at NVIDIA. It lives here, on the chip built to bury it Etched is not a fraud. It is a niche tool priced like a general one, and $800M is not enough to run a frontier supply chain. The rest get bought on the next down cycle Bury the lead, not the leader. Full case with Jack Farley and Max Wiethe on MTS And special thanks for Baseten for the cool T Shirt! Chapters 00:00 Switching from bonds to semis 00:33 What Etched actually is 01:31 Faster and cheaper, but how much HBM 02:56 Maturing market, not an NVIDIA killer 05:01 $1B in contracts and a Taiwan factory 05:20 Why these startups all get absorbed 06:48 Tiered inference and the obsolescence trap 09:39 Etched vs TPUs and Trainium 12:17 Is the CUDA moat weakening 13:21 Co-design, squeezing every token per watt 14:37 NVIDIA is a software company that sells a chip 14:58 Who is NVIDIA's most dangerous competitor 16:23 The NVIDIA killers, ranked 18:19 A rich man's game 18:43 AMD's MI500 vs Rubin Ultra 20:19 The neocloud business decision 22:46 Lightning round, Rambus the toll on HBM 25:11 The CXL run-up on Astera, Marvell, Credo 26:22 Use AI less, go to the booth 28:10 EDA is not dead
30:42

Etched came out of stealth at $800M and by lunch X had NVIDIA in the ground We do this every few months. A chip launches, the deck says killer, the timeline holds a funeral, and NVIDIA closes green anyway Etched hardwires the transformer into silicon. That is where the speed comes from, nearly the whole die on one job instead of the ~30% a GPU uses. It is also the trap. The day that chip tapes out is the best it will ever be. You cannot patch it. You burned progress into a wafer and now pray the field stops moving NVIDIA made the opposite bet. Same board, faster every quarter in software. Dynamo is pulling more tokens per watt out of the same rack, on version 1.0 The depreciation risk the bears aimed at NVIDIA for two years does not live at NVIDIA. It lives here, on the chip built to bury it Etched is not a fraud. It is a niche tool priced like a general one, and $800M is not enough to run a frontier supply chain. The rest get bought on the next down cycle Bury the lead, not the leader. Full case with Jack Farley and Max Wiethe on MTS And special thanks for Baseten for the cool T Shirt! Chapters 00:00 Switching from bonds to semis 00:33 What Etched actually is 01:31 Faster and cheaper, but how much HBM 02:56 Maturing market, not an NVIDIA killer 05:01 $1B in contracts and a Taiwan factory 05:20 Why these startups all get absorbed 06:48 Tiered inference and the obsolescence trap 09:39 Etched vs TPUs and Trainium 12:17 Is the CUDA moat weakening 13:21 Co-design, squeezing every token per watt 14:37 NVIDIA is a software company that sells a chip 14:58 Who is NVIDIA's most dangerous competitor 16:23 The NVIDIA killers, ranked 18:19 A rich man's game 18:43 AMD's MI500 vs Rubin Ultra 20:19 The neocloud business decision 22:46 Lightning round, Rambus the toll on HBM 25:11 The CXL run-up on Astera, Marvell, Credo 26:22 Use AI less, go to the booth 28:10 EDA is not dead

Ben Pouladian

29,969 views • 1 month ago

Just a little taste of the Robohacks hackathon happening now at Y Combinator in San Francisco. This is only two of the teams. The first is a team building a robot for an AirBnb on Mars. The second built a system that 3D prints new tools for the robot to do new work on Mars. Both demonstrate why I love builders so much. Dreaming of a new world and learning together how to build for a new robot none of them have used before.
14:14

Just a little taste of the Robohacks hackathon happening now at Y Combinator in San Francisco. This is only two of the teams. The first is a team building a robot for an AirBnb on Mars. The second built a system that 3D prints new tools for the robot to do new work on Mars. Both demonstrate why I love builders so much. Dreaming of a new world and learning together how to build for a new robot none of them have used before.

Robert Scoble

14,399 views • 4 months ago

MUST-WATCH VIDEO: "The Israeli Mafia Is Performing A Bust-Out On America!" Harrison Smith Breaks Down How An Episode Of "The Sopranos" TV Show Illustrates How The US Is Being Used By Israel To Fund Their Middle East Expansion Project Harrison H. Smith ✞ »WATCH THE ALEX JONES SHOW LIVE NOW:
4:43

MUST-WATCH VIDEO: "The Israeli Mafia Is Performing A Bust-Out On America!" Harrison Smith Breaks Down How An Episode Of "The Sopranos" TV Show Illustrates How The US Is Being Used By Israel To Fund Their Middle East Expansion Project Harrison H. Smith ✞ »WATCH THE ALEX JONES SHOW LIVE NOW:

Alex Jones

127,495 views • 5 months ago

Woo hoo! OpenAI highlights HubSpot partnership on main stage at #DevDay. Today was a special day for me. Was so cool to see Sam Altman from OpenAI feature HubSpot from the main keynote stage at their Dev Day event. HubSpot and OpenAI are the two most impactful companies in my life. HubSpot, for obvious reasons and OpenAI for less obvious ones. My relationship with Sam and OpenAI goes back a bit: 1) Got access to the GPT-2 API so had my "moment of magic" well before ChatGPT launched. 2) Have been using OpenAI's APIs and platform to build apps and agents for years. They *really* understand developers and have an amazing dev experience. 3) Sold the chat .com domain name to them and as a result was able to become an investor in the company. 4) They're the primary AI platform that HubSpot partners with and builds with -- as highlighted today. My congrats to the entire OpenAI team for today's event. I know how much work goes into putting together an event like this. And it was clear from the vibes how much you folks *care*. Cheers.
1:04

Woo hoo! OpenAI highlights HubSpot partnership on main stage at #DevDay. Today was a special day for me. Was so cool to see Sam Altman from OpenAI feature HubSpot from the main keynote stage at their Dev Day event. HubSpot and OpenAI are the two most impactful companies in my life. HubSpot, for obvious reasons and OpenAI for less obvious ones. My relationship with Sam and OpenAI goes back a bit: 1) Got access to the GPT-2 API so had my "moment of magic" well before ChatGPT launched. 2) Have been using OpenAI's APIs and platform to build apps and agents for years. They *really* understand developers and have an amazing dev experience. 3) Sold the chat .com domain name to them and as a result was able to become an investor in the company. 4) They're the primary AI platform that HubSpot partners with and builds with -- as highlighted today. My congrats to the entire OpenAI team for today's event. I know how much work goes into putting together an event like this. And it was clear from the vibes how much you folks *care*. Cheers.

dharmesh

57,938 views • 10 months ago

The Week Ahead In Technology for May 18, 2026. $NVDA Wednesday after the bell is the first hard test of whether $725B in 2026 hyperscaler AI capex actually lands in Jensen's revenue line. I'll be at Dell Technologies World in Las Vegas, where Michael Dell 🇺🇸 and Jensen Huang share the keynote stage Monday to likely unveil the next generation of the Dell AI Factory. Watch for the AMD angle too, after Dell's PowerEdge expansion with Instinct earlier this month. $SNPS reports the same evening as NVIDIA, a second read on AI infrastructure design demand. Lenovo Thursday on AI PCs and servers. Intuit on agentic AI in the SMB stack. Carry-over: @CerebrasSystems after its 68% IPO pop and Friday pullback, and the reported clearance of NVIDIA H200 sales to major Chinese hyperscalers following the Beijing summit. Both feed directly into how Jensen frames forward guidance. I'll be on CNBCOvertime right after the NVIDIA b
1:13

The Week Ahead In Technology for May 18, 2026. $NVDA Wednesday after the bell is the first hard test of whether $725B in 2026 hyperscaler AI capex actually lands in Jensen's revenue line. I'll be at Dell Technologies World in Las Vegas, where Michael Dell 🇺🇸 and Jensen Huang share the keynote stage Monday to likely unveil the next generation of the Dell AI Factory. Watch for the AMD angle too, after Dell's PowerEdge expansion with Instinct earlier this month. $SNPS reports the same evening as NVIDIA, a second read on AI infrastructure design demand. Lenovo Thursday on AI PCs and servers. Intuit on agentic AI in the SMB stack. Carry-over: @CerebrasSystems after its 68% IPO pop and Friday pullback, and the reported clearance of NVIDIA H200 sales to major Chinese hyperscalers following the Beijing summit. Both feed directly into how Jensen frames forward guidance. I'll be on CNBCOvertime right after the NVIDIA b

Patrick Moorhead

15,566 views • 3 months ago

NVIDIA CEO Jensen Huang at CES 2026: “We imagine that someday, a billion cars on the road will all be autonomous. You could have it as a robotaxi that you're orchestrating and renting from somebody, or you could own it and have it driving by itself. Or you could decide to drive it yourself. But every single car will have autonomous vehicle capability. Every single car will be AI-powered.”
0:21

NVIDIA CEO Jensen Huang at CES 2026: “We imagine that someday, a billion cars on the road will all be autonomous. You could have it as a robotaxi that you're orchestrating and renting from somebody, or you could own it and have it driving by itself. Or you could decide to drive it yourself. But every single car will have autonomous vehicle capability. Every single car will be AI-powered.”

Nic Cruz Patane

63,592 views • 7 months ago

Jensen Huang says NVIDIA doesn't actually build computers — and that's why every investor can't wait for them. "We don't build computers," Huang says. "We actually don't build clouds." "As it turns out, we're a computing platform company. And nobody can buy anything from us." "We vertically design, vertically integrate to design and optimize. But then we open up the entire platform at every single layer to be integrated into other companies' products." "I can't do what I do without having convinced them first." "Most of GTC is about manifesting a future that by the time my product is ready, they're going, 'What took you so long?'" Three layers, three owners: - NVIDIA owns the design - The supply chain owns the manufacturing - The clouds own the customers Huang owns the future they're all building together. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast
0:46

Jensen Huang says NVIDIA doesn't actually build computers — and that's why every investor can't wait for them. "We don't build computers," Huang says. "We actually don't build clouds." "As it turns out, we're a computing platform company. And nobody can buy anything from us." "We vertically design, vertically integrate to design and optimize. But then we open up the entire platform at every single layer to be integrated into other companies' products." "I can't do what I do without having convinced them first." "Most of GTC is about manifesting a future that by the time my product is ready, they're going, 'What took you so long?'" Three layers, three owners: - NVIDIA owns the design - The supply chain owns the manufacturing - The clouds own the customers Huang owns the future they're all building together. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

37,751 views • 2 months ago

OpSec is thrilled to confirm our attendance at the 2024 NVIDIA GTC conference on March 18-21! This event is more than just a gathering; it's a gateway to groundbreaking discoveries and invaluable connections. With over 900 sessions, 300+ exhibits, and 20+ technical workshops, we're diving deep into the latest AI advancements alongside industry luminaries, developers, researchers, and business strategists. From the highly anticipated keynote by NVIDIA CEO Jensen Huang to exclusive panels on topics like robotics, intellectual property challenges, and the role of AI in modern medicine, there's something for every interest and expertise level. With Ai Giants like Google , Amazon , Meta , Microsoft , Oracle and more in attendance, the networking opportunities are endless. Join us at #GTC2024 as we unlock new possibilities and shape the future of AI together!
0:31

OpSec is thrilled to confirm our attendance at the 2024 NVIDIA GTC conference on March 18-21! This event is more than just a gathering; it's a gateway to groundbreaking discoveries and invaluable connections. With over 900 sessions, 300+ exhibits, and 20+ technical workshops, we're diving deep into the latest AI advancements alongside industry luminaries, developers, researchers, and business strategists. From the highly anticipated keynote by NVIDIA CEO Jensen Huang to exclusive panels on topics like robotics, intellectual property challenges, and the role of AI in modern medicine, there's something for every interest and expertise level. With Ai Giants like Google , Amazon , Meta , Microsoft , Oracle and more in attendance, the networking opportunities are endless. Join us at #GTC2024 as we unlock new possibilities and shape the future of AI together!

OpSec

194,676 views • 2 years ago