正在加载视频...

视频加载失败

返回首页

What actually goes into a data center? Guru Chahal🇺🇸 whiteboards the entire stack - across land, power, cooling, storage, networking, compute - and shares where we're seeing the most interesting innovation + startup opportunities → Base Power: virtual power plants from residential batteries → Periodic Labs: using AI to...

clairejyz's profile picture

Claire Zau

5,763 subscribers

36,841 次观看 • 7 天前 •via X (Twitter)

科学技术教育新闻政治
LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA
1:48

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,983 次观看 • 1 个月前

🇺🇸 Elon confirms the “Terafab” model links xAI, SpaceX, and Tesla to scale chips, energy, and factories together, aiming for terawatt-level compute output. The idea is to control the full stack: chip design, manufacturing, power generation, and deployment, with most compute eventually supporting space-based systems. So it’s like a feedback loop, more factories build more chips, which train better AI, which then designs even better factories. Because why build a factory… when you can try to build the entire stack. Source: Elon Musk Tesla
1:45

🇺🇸 Elon confirms the “Terafab” model links xAI, SpaceX, and Tesla to scale chips, energy, and factories together, aiming for terawatt-level compute output. The idea is to control the full stack: chip design, manufacturing, power generation, and deployment, with most compute eventually supporting space-based systems. So it’s like a feedback loop, more factories build more chips, which train better AI, which then designs even better factories. Because why build a factory… when you can try to build the entire stack. Source: Elon Musk Tesla

Mario Nawfal

152,538 次观看 • 4 个月前

Marc Andreessen says AI is teaching sand to think and it could be the most important technology in the history of humanity: "Imagine a form of alchemy that turns sand into thought." "Chips are made out of sand. They're made out of silicon, so they're literally made out of sand." "We plug the chip into a data center, into power, we light it up, and we put AI on it, and all of a sudden it's thinking." "We've turned sand into thought. And so it's possibly the most revolutionary technology in the history of the species." "It's certainly on par with electricity and steam power. It's certainly more important than the internet." Marc Andreessen 🇺🇸 with Joe Rogan
1:10

Marc Andreessen says AI is teaching sand to think and it could be the most important technology in the history of humanity: "Imagine a form of alchemy that turns sand into thought." "Chips are made out of sand. They're made out of silicon, so they're literally made out of sand." "We plug the chip into a data center, into power, we light it up, and we put AI on it, and all of a sudden it's thinking." "We've turned sand into thought. And so it's possibly the most revolutionary technology in the history of the species." "It's certainly on par with electricity and steam power. It's certainly more important than the internet." Marc Andreessen 🇺🇸 with Joe Rogan

a16z

203,805 次观看 • 2 个月前

They are putting DATA CENTERS in the ocean now. Panthalassa, a startup from Portland, just raised $140 MILLION. what they do: build floating platforms that sit out at sea and run AI. no power grid needed. the ocean waves make all the electricity. the seawater keeps the chips cool. How it works: big floating balls bob up and down with the waves. that motion makes power. the power runs the AI chips inside. backed by PETER THIEL. company now worth almost $1 BILLION. land is running out of room and power for AI. so the next move is simple. go to the sea.
0:26

They are putting DATA CENTERS in the ocean now. Panthalassa, a startup from Portland, just raised $140 MILLION. what they do: build floating platforms that sit out at sea and run AI. no power grid needed. the ocean waves make all the electricity. the seawater keeps the chips cool. How it works: big floating balls bob up and down with the waves. that motion makes power. the power runs the AI chips inside. backed by PETER THIEL. company now worth almost $1 BILLION. land is running out of room and power for AI. so the next move is simple. go to the sea.

shirish

1,644,809 次观看 • 1 个月前

Jensen Huang is warning that China is winning the AI energy race. $NVDA $AMD $IREN $NBIS 🇨🇳 🇺🇸 🇪🇺 The US is generations ahead on chips, but that doesn't matter if there is no energy to power them. Europe is completely irrelevant in AI and doomed already. It takes 10 years to build a new data center in Germany, as there is no power, and they are turning off nuclear power plants. The US won't let China win, so we could be at the beginning stages of an energy boom. The question is which stocks will benefit from this boom the most?
6:50

Jensen Huang is warning that China is winning the AI energy race. $NVDA $AMD $IREN $NBIS 🇨🇳 🇺🇸 🇪🇺 The US is generations ahead on chips, but that doesn't matter if there is no energy to power them. Europe is completely irrelevant in AI and doomed already. It takes 10 years to build a new data center in Germany, as there is no power, and they are turning off nuclear power plants. The US won't let China win, so we could be at the beginning stages of an energy boom. The question is which stocks will benefit from this boom the most?

Ray Myers

84,029 次观看 • 8 个月前

Elon Musk explains the “series of miracles” xAI had to achieve to bring one gigawatt of power online for its supercomputer cluster in Memphis The xAI team coordinated dozens of gas turbines, faced permit challenges in Tennessee, and ultimately moved the power generation just across the border into Mississippi. From there, they had to run high-voltage transmission lines and build an entire power plant on the Mississippi side and it was very difficult to build that But the deeper point is even more important Most people calculate AI power needs by looking only at the GPUs. That is a serious mistake. A real data center also requires substantial power for networking, CPUs, storage, and most critically cooling In Memphis, where summer temperatures are extreme, peak cooling demand can add roughly 40% more power. On top of that, operators must maintain extra capacity so generators can be taken offline for servicing without shutting down the entire system. This redundancy typically adds another 20 to 25 percent When all of these factors are included, Elon stated that approximately 110,000 GB300 GPUs require roughly 330 megawatts of actual power generation This is why building and powering frontier AI data centers is far more difficult and far more capital intensive than it appears from the outside
2:43

Elon Musk explains the “series of miracles” xAI had to achieve to bring one gigawatt of power online for its supercomputer cluster in Memphis The xAI team coordinated dozens of gas turbines, faced permit challenges in Tennessee, and ultimately moved the power generation just across the border into Mississippi. From there, they had to run high-voltage transmission lines and build an entire power plant on the Mississippi side and it was very difficult to build that But the deeper point is even more important Most people calculate AI power needs by looking only at the GPUs. That is a serious mistake. A real data center also requires substantial power for networking, CPUs, storage, and most critically cooling In Memphis, where summer temperatures are extreme, peak cooling demand can add roughly 40% more power. On top of that, operators must maintain extra capacity so generators can be taken offline for servicing without shutting down the entire system. This redundancy typically adds another 20 to 25 percent When all of these factors are included, Elon stated that approximately 110,000 GB300 GPUs require roughly 330 megawatts of actual power generation This is why building and powering frontier AI data centers is far more difficult and far more capital intensive than it appears from the outside

X Freeze

140,274 次观看 • 3 个月前

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️
0:43

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️

Amazon

27,151 次观看 • 2 个月前

Daniel Roberts of $IREN just laid out the brutal reality of the AI infrastructure buildout. He noted we are still in the dial up era of AI. The ultimate choke point is power. It requires steel, concrete, and years of physical construction. Starting a gigawatt AI factory today means you will not see the first compute online until the 2030s. It takes 18 to 24 months just to get a utility company to confirm if a piece of land even has power access. The market is pricing in rapid software scaling, but the physical bottlenecks are severe and unavoidable. The capital moving into power generation and data center infrastructure is a multi year trend. It’s not a sprint it’s a marathon.
1:10

Daniel Roberts of $IREN just laid out the brutal reality of the AI infrastructure buildout. He noted we are still in the dial up era of AI. The ultimate choke point is power. It requires steel, concrete, and years of physical construction. Starting a gigawatt AI factory today means you will not see the first compute online until the 2030s. It takes 18 to 24 months just to get a utility company to confirm if a piece of land even has power access. The market is pricing in rapid software scaling, but the physical bottlenecks are severe and unavoidable. The capital moving into power generation and data center infrastructure is a multi year trend. It’s not a sprint it’s a marathon.

Patient Investor

176,637 次观看 • 2 个月前

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”
4:51

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”

DogeDesigner

243,448 次观看 • 13 天前

China is our adversary. They are building more power than we are, and then using it to power data centers to advance both economic interests and of course military as well. We can’t let the Chinese beat us in AI. We’ve gotta build more data centers, we’ve gotta build more power. We’ve got a lot ahead of us here because they’re beating us on this. We cannot let this happen.
3:06

China is our adversary. They are building more power than we are, and then using it to power data centers to advance both economic interests and of course military as well. We can’t let the Chinese beat us in AI. We’ve gotta build more data centers, we’ve gotta build more power. We’ve got a lot ahead of us here because they’re beating us on this. We cannot let this happen.

Kevin O'Leary aka Mr. Wonderful

19,394 次观看 • 3 个月前

Bitzero is a power, permit, and land company. What they've done is search the globe looking for the lowest cost of power, sustainable electric power, some nuclear power, sub six cents a kilowatt hour. You can mine bitcoin on their land or you can do Ethereum, or you can build a data center. Everybody in AI has to have power, land, permits, and water. BitZero has them. It's an infrastructure play and I find a lot less risky than figuring out who's going to win in AI. Everybody needs what BitZero has, power.
1:11

Bitzero is a power, permit, and land company. What they've done is search the globe looking for the lowest cost of power, sustainable electric power, some nuclear power, sub six cents a kilowatt hour. You can mine bitcoin on their land or you can do Ethereum, or you can build a data center. Everybody in AI has to have power, land, permits, and water. BitZero has them. It's an infrastructure play and I find a lot less risky than figuring out who's going to win in AI. Everybody needs what BitZero has, power.

Kevin O'Leary aka Mr. Wonderful

18,648 次观看 • 8 个月前

NVIDIA CEO Jensen Huang explains the architecture of the AI revolution AI is fundamentally about thinking—and that requires supercomputers. We’ve created a new industry: AI infrastructure. It will be as foundational as the electricity and internet infrastructures—permanent for every society. This is a transformative time; how we deliver and produce intelligence is changing. Each layer of the AI stack is growing: 1. Energy 2. Chips 3. Infrastructure 4. AI models 5. AI applications We’re witnessing a complete revolution across the stack, with opportunities at every layer. NVIDIA intends to participate across the entire stack.
1:34

NVIDIA CEO Jensen Huang explains the architecture of the AI revolution AI is fundamentally about thinking—and that requires supercomputers. We’ve created a new industry: AI infrastructure. It will be as foundational as the electricity and internet infrastructures—permanent for every society. This is a transformative time; how we deliver and produce intelligence is changing. Each layer of the AI stack is growing: 1. Energy 2. Chips 3. Infrastructure 4. AI models 5. AI applications We’re witnessing a complete revolution across the stack, with opportunities at every layer. NVIDIA intends to participate across the entire stack.

Ask Perplexity

64,013 次观看 • 10 个月前

Elon Musk just put a number on the flaw at the center of Nvidia’s empire. Wall Street has not done the math yet. Nvidia’s Blackwell is the most sought-after silicon on Earth. Every AI lab wants it. Every sovereign nation is bidding for it. Blackwell runs every model, for every company, in every data center on the planet. That universality built the empire. It is also the fracture point. Musk: “We believe the AI5 chip will be about a third of the power of an Nvidia Blackwell for roughly comparable performance. And much less than 10% of the cost.” One-third the power. Comparable performance. Less than ten percent of the cost. Musk: “This is a chip that is very much optimized for the Tesla AI software stack. It’s not meant to be a general purpose chip.” Nvidia builds silicon that serves a million different customers. Every transistor spent on universal compatibility is a transistor not dedicated to one task. Tesla is building silicon for exactly one customer. Itself. When you strip away every function you will never call, you do not get a lesser chip. You get a weapon. Here is what the market refuses to see. Data centers drink unlimited power from the grid. Robots run on batteries. Musk: “In order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient.” You cannot put a Blackwell inside a walking machine. It would drain the battery before it crossed the room. The entire AI revolution lives inside air-conditioned buildings bolted to the electrical grid. Musk is not competing for that market. He is engineering the silicon that survives outside of it. One-third the power is not a spec sheet footnote. It is the physics threshold that severs intelligence from the wall socket. Without that number, every robot on Earth stays tethered. With it, the algorithm walks. Less than ten percent of the cost is not a pricing strategy. It is the line where a machine brain stops being a capital expenditure and becomes a commodity component. When the chip inside a humanoid costs less than the motors in its legs, you do not manufacture hundreds of robots. You manufacture millions. Wall Street is valuing the AI revolution by who dominates the data center. Musk is building the only silicon designed to leave one. Nvidia built the brain of the cloud. Musk is building the brain of the physical world. No one has priced that in yet.
0:56

Elon Musk just put a number on the flaw at the center of Nvidia’s empire. Wall Street has not done the math yet. Nvidia’s Blackwell is the most sought-after silicon on Earth. Every AI lab wants it. Every sovereign nation is bidding for it. Blackwell runs every model, for every company, in every data center on the planet. That universality built the empire. It is also the fracture point. Musk: “We believe the AI5 chip will be about a third of the power of an Nvidia Blackwell for roughly comparable performance. And much less than 10% of the cost.” One-third the power. Comparable performance. Less than ten percent of the cost. Musk: “This is a chip that is very much optimized for the Tesla AI software stack. It’s not meant to be a general purpose chip.” Nvidia builds silicon that serves a million different customers. Every transistor spent on universal compatibility is a transistor not dedicated to one task. Tesla is building silicon for exactly one customer. Itself. When you strip away every function you will never call, you do not get a lesser chip. You get a weapon. Here is what the market refuses to see. Data centers drink unlimited power from the grid. Robots run on batteries. Musk: “In order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient.” You cannot put a Blackwell inside a walking machine. It would drain the battery before it crossed the room. The entire AI revolution lives inside air-conditioned buildings bolted to the electrical grid. Musk is not competing for that market. He is engineering the silicon that survives outside of it. One-third the power is not a spec sheet footnote. It is the physics threshold that severs intelligence from the wall socket. Without that number, every robot on Earth stays tethered. With it, the algorithm walks. Less than ten percent of the cost is not a pricing strategy. It is the line where a machine brain stops being a capital expenditure and becomes a commodity component. When the chip inside a humanoid costs less than the motors in its legs, you do not manufacture hundreds of robots. You manufacture millions. Wall Street is valuing the AI revolution by who dominates the data center. Musk is building the only silicon designed to leave one. Nvidia built the brain of the cloud. Musk is building the brain of the physical world. No one has priced that in yet.

Dustin

160,573 次观看 • 3 个月前

AI in the network is shifting the conversation beyond GPUs. At MWC 2026, Intel's Kevork Kechichian, EVP & GM of the Data Center Group, explains why inference workloads are bringing CPUs back into focus, especially in telco environments where power, space, and efficiency matter. With platforms like Intel Xeon and Clearwater Forest, operators are seeing up to 30% performance gains and 60% better power efficiency, helping scale AI workloads without overhauling infrastructure. As networks evolve toward AI-driven operations and 6G, one principle is becoming clear: The future of AI infrastructure is about using the right compute for the right workload.
1:14

AI in the network is shifting the conversation beyond GPUs. At MWC 2026, Intel's Kevork Kechichian, EVP & GM of the Data Center Group, explains why inference workloads are bringing CPUs back into focus, especially in telco environments where power, space, and efficiency matter. With platforms like Intel Xeon and Clearwater Forest, operators are seeing up to 30% performance gains and 60% better power efficiency, helping scale AI workloads without overhauling infrastructure. As networks evolve toward AI-driven operations and 6G, one principle is becoming clear: The future of AI infrastructure is about using the right compute for the right workload.

Six Five Media

131,501 次观看 • 4 个月前

🚀 Introducing the AI Alliance: Shaping the Future of AI and Data Security We’re proud to unveil the AI Alliance, a collaboration of expert teams from ARC, DMAIL.AI and XAlpha AI Agent to name a few, who are working together to drive innovation in AI and data security. By leveraging the power of LLMs (Large Language Models), we’re building the foundation for future AI applications. 🌐✨ 💡 This is just the beginning! Stay tuned for more insights and updates from this recently held AI Alliance AMA. We’ll dive deeper into how these teams are helping to shape the future of AI.
0:55

🚀 Introducing the AI Alliance: Shaping the Future of AI and Data Security We’re proud to unveil the AI Alliance, a collaboration of expert teams from ARC, DMAIL.AI and XAlpha AI Agent to name a few, who are working together to drive innovation in AI and data security. By leveraging the power of LLMs (Large Language Models), we’re building the foundation for future AI applications. 🌐✨ 💡 This is just the beginning! Stay tuned for more insights and updates from this recently held AI Alliance AMA. We’ll dive deeper into how these teams are helping to shape the future of AI.

ARC

20,658 次观看 • 1 年前

Elon Musk drops a massive prediction about the immediate future of AI and infrastructure: we are running out of power — “My guess is that people start getting where they can't turn the chips on for large clusters towards the end of this year.” Musk argues that while we are solving the chip shortage, we are sprinting toward a new wall: electricity. He envisions a future where we must unlock power constraints by going to space, potentially generating “hundreds of gigawatts per year” in orbit—enough to “lap the US” in total power capacity every few years.
1:38

Elon Musk drops a massive prediction about the immediate future of AI and infrastructure: we are running out of power — “My guess is that people start getting where they can't turn the chips on for large clusters towards the end of this year.” Musk argues that while we are solving the chip shortage, we are sprinting toward a new wall: electricity. He envisions a future where we must unlock power constraints by going to space, potentially generating “hundreds of gigawatts per year” in orbit—enough to “lap the US” in total power capacity every few years.

Ian Miles Cheong

32,697 次观看 • 5 个月前

Would you look at this. It turns out the future isn’t wind and solar, It’s nuclear power Happening Now: Construction on 3 Nuclear Power Plants has begun to meet Google’s net zero company goals after demands for more power increased with ai “Oak Ridge, Tennessee, they're building three phases of experimental nuclear power plants here. These are called SMRs. Small modular reactors, smaller, cheaper, and safer than traditional power plants. Instead of fuel rods, they use these fuel pebbles. Cut it in half and you can see the simulated specs of uranium in there. These contain the byproducts. The client for all this is Google. Google's trying to reach its goals of being a net zero company, so they need a lot more clean power now that they're using all this AI stuff. So this company called Kairos Power is gonna build them with luck by 2030, a fleet of small modular reactors for clean, safe nuclear power forever.”
0:49

Would you look at this. It turns out the future isn’t wind and solar, It’s nuclear power Happening Now: Construction on 3 Nuclear Power Plants has begun to meet Google’s net zero company goals after demands for more power increased with ai “Oak Ridge, Tennessee, they're building three phases of experimental nuclear power plants here. These are called SMRs. Small modular reactors, smaller, cheaper, and safer than traditional power plants. Instead of fuel rods, they use these fuel pebbles. Cut it in half and you can see the simulated specs of uranium in there. These contain the byproducts. The client for all this is Google. Google's trying to reach its goals of being a net zero company, so they need a lot more clean power now that they're using all this AI stuff. So this company called Kairos Power is gonna build them with luck by 2030, a fleet of small modular reactors for clean, safe nuclear power forever.”

Wall Street Apes

156,172 次观看 • 1 年前

Elon Musk: For the next few years, I think America is likely to win the artificial intelligence race. But that early lead is fragile and short-lived. Ultimately, the global victor will be decided by a single factor: it will be a function of who controls the AI chip fabrication. The factories that make the AI chips, who controls them? That is where the real power lies. If those facilities are controlled, if more of them are controlled by China, then China will win the future of AI. Right now, almost all the advanced AI chip factories, they call them fabs, are located in Taiwan. That immense concentration of manufacturing creates a massive vulnerability for the rest of the globe. If China invades Taiwan, what happens to the world? Well, if they were to invade in the near term, the entire world would essentially be cut off from advanced AI chips overnight. Everything would grind to a halt. Currently, one hundred percent of advanced AI chips are made in Taiwan. We are relying entirely on a single location for the critical hardware that will define the next era of human technology and military dominance. Bringing that manufacturing power back home and securing our own supply chain is absolutely essential for national security, and the harsh reality is that we are simply not doing enough to prepare.
1:29

Elon Musk: For the next few years, I think America is likely to win the artificial intelligence race. But that early lead is fragile and short-lived. Ultimately, the global victor will be decided by a single factor: it will be a function of who controls the AI chip fabrication. The factories that make the AI chips, who controls them? That is where the real power lies. If those facilities are controlled, if more of them are controlled by China, then China will win the future of AI. Right now, almost all the advanced AI chip factories, they call them fabs, are located in Taiwan. That immense concentration of manufacturing creates a massive vulnerability for the rest of the globe. If China invades Taiwan, what happens to the world? Well, if they were to invade in the near term, the entire world would essentially be cut off from advanced AI chips overnight. Everything would grind to a halt. Currently, one hundred percent of advanced AI chips are made in Taiwan. We are relying entirely on a single location for the critical hardware that will define the next era of human technology and military dominance. Bringing that manufacturing power back home and securing our own supply chain is absolutely essential for national security, and the harsh reality is that we are simply not doing enough to prepare.

Ian Miles Cheong

408,156 次观看 • 3 个月前

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg
1:13

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg

The All-In Podcast

107,012 次观看 • 10 个月前