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Elon Musk: At Tesla, we basically had two different chip programs: one Dojo and one. Dojo on the training side, and then what we call AI4, it's just our inference chip The AI4 is what's currently shipping in all vehicles, and we're finalizing the design of AI5, which will...

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ELON: TESLA'S AI5 CHIP IS THE SILICON VERSION OF “LESS IS MORE” "The AI5 chip will be 40 times better than the AI4 chip – not 40%, 40 times. We have a detailed understanding of the entire software and hardware stack. We are designing the hardware to address all of the pain points in software. We know what the chip needs to do, and we know, just as importantly, what the chip doesn’t need to do. A long list of deletions that are very important. As a result of these deletions, we can actually fit AI5 in a half reticle with a good margin for the traces from the memory to the Tesla chip accelerators, the ARM CPU cores, and the PCI blocks. This is a beautiful chip." Source: Elon Musk, Tesla Podcast, October 22, 2025
1:15

ELON: TESLA'S AI5 CHIP IS THE SILICON VERSION OF “LESS IS MORE” "The AI5 chip will be 40 times better than the AI4 chip – not 40%, 40 times. We have a detailed understanding of the entire software and hardware stack. We are designing the hardware to address all of the pain points in software. We know what the chip needs to do, and we know, just as importantly, what the chip doesn’t need to do. A long list of deletions that are very important. As a result of these deletions, we can actually fit AI5 in a half reticle with a good margin for the traces from the memory to the Tesla chip accelerators, the ARM CPU cores, and the PCI blocks. This is a beautiful chip." Source: Elon Musk, Tesla Podcast, October 22, 2025

Mario Nawfal

363,474 просмотров • 9 месяцев назад

Everything Elon said about Optimus at the All-In Summit today: • We’re finalizing the design of Optimus v3. That release is going to be a very remarkable robot. It will have manual dexterity comparable to a human, meaning a very complex hand, an AI mind that can navigate and comprehend reality, and will be made in very high volume. • Other robotics companies are missing those three very hard things. • I spend more mental cycles on Optimus than any other single thing. Solving real-world AI, all of the electrical-mechanical issues, the supply chain, and production challenges. • There is no supply chain for humanoid robots, so it has to be created from scratch, which requires a lot of vertical integration. None of the actuators in Optimus are available from an existing supply chain. • I think if successful, Optimus would be the biggest product ever. • The marginal cost of production, once we hit a million units per year, will probably be around $20,000. It depends on how much we spend on the AI chip in the robot, and we’ll need to achieve a lot of efficiencies in the actuators—26 actuators per arm (26 motors, gearboxes, and power electronics). The AI chip might cost $5,000 or $6,000, maybe more. At 1 million units a year, production cost will be $20,000, maybe $25,000. Price will be a function of demand. • Human hands have evolved to be incredibly sophisticated machines. Hands are a very first instrument. You can swing a baseball bat, thread a needle, play a piano or violin, and assemble a car. Hands are incredibly versatile instruments. Most of the muscles of the hands are actually in the forearm, and the hand is almost like a puppet. Human tendon evolution is incredibly good. The human hand has 27 or 28 degrees of freedom, depending on how you count it; it’s amazing. • In order to create a robot that can be a generalized humanoid, you must solve the “hands problem.” • Even though there are 10,000 to 20,000 electric motors out there, we couldn’t buy the actuators for any amount of money. We had to design every electric motor, gearbox, and controlling electronics from scratch, from first principles of physics. • Optimus is harder than developing any previous Tesla product, but not harder than Starship. • Right now, we’re struggling with the final design of the hardware, primarily the hand. The hands and forearm are the majority of the engineering difficulty of the entire robot. • If you want to do all the things that a human can do, it turns out you need a humanoid robot. If you want to do a subset, that’s much easier. Humans evolved to the shape and capability that we have for a good reason. There is value to having four fingers and a thumb; even the pinky is quite useful. Toes are much more of a question mark. • The AI5 inference chip will be 40 times better than AI4 by some measures. We know the limiting factors of the chip because the AI software and hardware teams work so closely. Effectively, the Tesla AI hardware and software teams are co-designing the chip. • The Softmax function on AI4 takes 40 steps in emulation mode, which will take only a few steps in AI5 natively. AI5 will easily handle mixed precision. • In terms of nominal raw compute, the AI5 inference chip has 8 times more compute, 9 times more memory, and 5 times more memory bandwidth compared to AI4. Because we’re addressing some core limitations and optimizations at the silicon level, we’re able to realize 40x improvements.
12:26

Everything Elon said about Optimus at the All-In Summit today: • We’re finalizing the design of Optimus v3. That release is going to be a very remarkable robot. It will have manual dexterity comparable to a human, meaning a very complex hand, an AI mind that can navigate and comprehend reality, and will be made in very high volume. • Other robotics companies are missing those three very hard things. • I spend more mental cycles on Optimus than any other single thing. Solving real-world AI, all of the electrical-mechanical issues, the supply chain, and production challenges. • There is no supply chain for humanoid robots, so it has to be created from scratch, which requires a lot of vertical integration. None of the actuators in Optimus are available from an existing supply chain. • I think if successful, Optimus would be the biggest product ever. • The marginal cost of production, once we hit a million units per year, will probably be around $20,000. It depends on how much we spend on the AI chip in the robot, and we’ll need to achieve a lot of efficiencies in the actuators—26 actuators per arm (26 motors, gearboxes, and power electronics). The AI chip might cost $5,000 or $6,000, maybe more. At 1 million units a year, production cost will be $20,000, maybe $25,000. Price will be a function of demand. • Human hands have evolved to be incredibly sophisticated machines. Hands are a very first instrument. You can swing a baseball bat, thread a needle, play a piano or violin, and assemble a car. Hands are incredibly versatile instruments. Most of the muscles of the hands are actually in the forearm, and the hand is almost like a puppet. Human tendon evolution is incredibly good. The human hand has 27 or 28 degrees of freedom, depending on how you count it; it’s amazing. • In order to create a robot that can be a generalized humanoid, you must solve the “hands problem.” • Even though there are 10,000 to 20,000 electric motors out there, we couldn’t buy the actuators for any amount of money. We had to design every electric motor, gearbox, and controlling electronics from scratch, from first principles of physics. • Optimus is harder than developing any previous Tesla product, but not harder than Starship. • Right now, we’re struggling with the final design of the hardware, primarily the hand. The hands and forearm are the majority of the engineering difficulty of the entire robot. • If you want to do all the things that a human can do, it turns out you need a humanoid robot. If you want to do a subset, that’s much easier. Humans evolved to the shape and capability that we have for a good reason. There is value to having four fingers and a thumb; even the pinky is quite useful. Toes are much more of a question mark. • The AI5 inference chip will be 40 times better than AI4 by some measures. We know the limiting factors of the chip because the AI software and hardware teams work so closely. Effectively, the Tesla AI hardware and software teams are co-designing the chip. • The Softmax function on AI4 takes 40 steps in emulation mode, which will take only a few steps in AI5 natively. AI5 will easily handle mixed precision. • In terms of nominal raw compute, the AI5 inference chip has 8 times more compute, 9 times more memory, and 5 times more memory bandwidth compared to AI4. Because we’re addressing some core limitations and optimizations at the silicon level, we’re able to realize 40x improvements.

The Humanoid Hub

238,877 просмотров • 11 месяцев назад

🚨🇺🇸 CHAMATH: ELON’S AI5 CHIP IS 40X BETTER THAN AI4 — A BEAUTIFUL DESIGN “He had these multiple efforts with Dojo and other stuff that he merged into one unit. The quote is incredible: ‘We’re going to focus TSMC and Samsung on AI5.’ By some metrics, it’ll be 40x better than AI4. With AI5, they deleted the legacy GPU — it basically is a GPU. They also deleted the image signal processor. Elon said, ‘This is a beautiful chip. I poured so much life energy into this personally. It’ll be a real winner.’” Source: Chamath Palihapitiya The All-In Podcast
0:57

🚨🇺🇸 CHAMATH: ELON’S AI5 CHIP IS 40X BETTER THAN AI4 — A BEAUTIFUL DESIGN “He had these multiple efforts with Dojo and other stuff that he merged into one unit. The quote is incredible: ‘We’re going to focus TSMC and Samsung on AI5.’ By some metrics, it’ll be 40x better than AI4. With AI5, they deleted the legacy GPU — it basically is a GPU. They also deleted the image signal processor. Elon said, ‘This is a beautiful chip. I poured so much life energy into this personally. It’ll be a real winner.’” Source: Chamath Palihapitiya The All-In Podcast

Mario Nawfal

1,016,192 просмотров • 9 месяцев назад

ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla
2:09

ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla

Mario Nawfal

225,142 просмотров • 8 месяцев назад

ELON MUSK: We believe the AI5 chip will be roughly comparable performance to an NVIDIA Blackwell, and at much less than 10% of the cost Transcription: I'm super hardcore on chips right now as you may be able to tell. I have chips on the brain. I dream about chips, Literally! Because 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 So we think we believe the AI5 chip will be probably about a third of the power of say something like a Blackwell, an NVIDIA Blackwell, which is a great chip, for roughly comparable performance. And much less than 10% of the cost. This is a chip that is very much optimized for the Tesla AI software stack. So it's not meant to be a general purpose chip, it's meant to be an amazing chip for the Tesla AI software And I mean a couple of things that I think make... like how is Tesla able to achieve such an improvement? I think it is because we are specialized. We're not trying to... you know, NVIDIA has to serve the superset of all past and future customers. So all of their requirements, all of the software that they've written has to work, which is a very difficult problem. Whereas we just need to make it work for our software. And so we're able to simplify the chip dramatically And then we also, I think we're unique in this, but like we have an integer-based system. And integer operations are fundamentally more efficient than floating point operations. So we can do floating point, but the vast majority of our inference is done in integer. Which is, if you're familiar with sort of logic gates, the simplicity of integer... it's integer is much more power efficient, much more silicon efficient, but you have to, you actually have to train for integer inference, which everyone else is training for floating point. That's kind of like a niche technical detail, but it's actually very important. So, yeah, this is going to be a great chip So this chip will be made in basically in four places: TSMC Taiwan, Samsung Korea, TSMC Arizona, and TSMC Texas. And we already know what improvements to make for AI6. So I'm hopeful that we can within less than a year of AI5 starting production, we can actually transition in the same fab to AI6 and double all of the performance metrics
3:12

ELON MUSK: We believe the AI5 chip will be roughly comparable performance to an NVIDIA Blackwell, and at much less than 10% of the cost Transcription: I'm super hardcore on chips right now as you may be able to tell. I have chips on the brain. I dream about chips, Literally! Because 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 So we think we believe the AI5 chip will be probably about a third of the power of say something like a Blackwell, an NVIDIA Blackwell, which is a great chip, for roughly comparable performance. And much less than 10% of the cost. This is a chip that is very much optimized for the Tesla AI software stack. So it's not meant to be a general purpose chip, it's meant to be an amazing chip for the Tesla AI software And I mean a couple of things that I think make... like how is Tesla able to achieve such an improvement? I think it is because we are specialized. We're not trying to... you know, NVIDIA has to serve the superset of all past and future customers. So all of their requirements, all of the software that they've written has to work, which is a very difficult problem. Whereas we just need to make it work for our software. And so we're able to simplify the chip dramatically And then we also, I think we're unique in this, but like we have an integer-based system. And integer operations are fundamentally more efficient than floating point operations. So we can do floating point, but the vast majority of our inference is done in integer. Which is, if you're familiar with sort of logic gates, the simplicity of integer... it's integer is much more power efficient, much more silicon efficient, but you have to, you actually have to train for integer inference, which everyone else is training for floating point. That's kind of like a niche technical detail, but it's actually very important. So, yeah, this is going to be a great chip So this chip will be made in basically in four places: TSMC Taiwan, Samsung Korea, TSMC Arizona, and TSMC Texas. And we already know what improvements to make for AI6. So I'm hopeful that we can within less than a year of AI5 starting production, we can actually transition in the same fab to AI6 and double all of the performance metrics

X Freeze

305,109 просмотров • 9 месяцев назад

ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."
1:52

ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."

DogeDesigner

265,257 просмотров • 8 месяцев назад

This is why Elon is singular. He has recently spent many weekends working with the AI5 chip team to get the project on track. Designing this chip requires deep knowledge of leading edge process node chip design and leading edge AI algorithms, neither of which Elon has deep experience in. But he learns fast and can ask the right engineering level technical questions to be able to make quick decisions. And along the way, he axed the Dojo program knowing that AI5 was more important. In 99% of other companies, both programs would have chugged along into eventual irrelevance.
1:49

This is why Elon is singular. He has recently spent many weekends working with the AI5 chip team to get the project on track. Designing this chip requires deep knowledge of leading edge process node chip design and leading edge AI algorithms, neither of which Elon has deep experience in. But he learns fast and can ask the right engineering level technical questions to be able to make quick decisions. And along the way, he axed the Dojo program knowing that AI5 was more important. In 99% of other companies, both programs would have chugged along into eventual irrelevance.

Phil Trubey

135,536 просмотров • 8 месяцев назад

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson
56:36

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson

nextbigfuture

23,809 просмотров • 1 год назад

🚨ZUCK: "Probably in 2025, Meta, as well as other companies, will have an AI that can effectively be a mid-level engineer that you have at your company that can write code. In the beginning that will be very expensive to run, then at some point a lot of the code we have in our apps will be built by AI engineers instead of people engineers. In my opinion that will augment the people working on it. My view is that in the future people will be so much more creative and freed up to do crazy things."
1:02

🚨ZUCK: "Probably in 2025, Meta, as well as other companies, will have an AI that can effectively be a mid-level engineer that you have at your company that can write code. In the beginning that will be very expensive to run, then at some point a lot of the code we have in our apps will be built by AI engineers instead of people engineers. In my opinion that will augment the people working on it. My view is that in the future people will be so much more creative and freed up to do crazy things."

Autism Capital 🧩

1,666,495 просмотров • 1 год назад

Elon Musk: In the future, every country will have its own AI clusters. “It's currently very difficult to actually build an AI cluster and have it run. It's not like just pulling a computer out of a box. They are currently very difficult to run. And are you going to be training a frontier model? Because if you're training a frontier model, then you need a massive amount of compute and a level of technical skill that only a few companies possess. But, over time, I think every country will have AI compute clusters. It's just going to be a normal thing.” Future Investment Initiative, October 29, 2024
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Elon Musk: In the future, every country will have its own AI clusters. “It's currently very difficult to actually build an AI cluster and have it run. It's not like just pulling a computer out of a box. They are currently very difficult to run. And are you going to be training a frontier model? Because if you're training a frontier model, then you need a massive amount of compute and a level of technical skill that only a few companies possess. But, over time, I think every country will have AI compute clusters. It's just going to be a normal thing.” Future Investment Initiative, October 29, 2024

ELON CLIPS

95,313 просмотров • 8 месяцев назад

Elon Musk explains Tesla’s new Megapod concept for scaling distributed AI compute: “We’re building a Megapod design that pairs Tesla AI4 computers with x86 systems in a box...essentially digital Optimus in a box Similar to how Megapack packages batteries, a Megapod would combine a large number of AI4 and x86 systems inside one deployable unit These boxes could be placed anywhere across the country or outside the country allowing us to scale AI compute using distributed electricity production There is power available all around the world, including at our Supercharger sites. We have something like 7 gigawatts of power across the Supercharger network, and that continues to grow We could place Megapods at many of these locations and use that distributed power for AI compute I think that could be quite a big deal” Instead of relying entirely on enormous centralized data centers, Tesla could deploy modular AI-compute infrastructure wherever sufficient power is already available
1:23

Elon Musk explains Tesla’s new Megapod concept for scaling distributed AI compute: “We’re building a Megapod design that pairs Tesla AI4 computers with x86 systems in a box...essentially digital Optimus in a box Similar to how Megapack packages batteries, a Megapod would combine a large number of AI4 and x86 systems inside one deployable unit These boxes could be placed anywhere across the country or outside the country allowing us to scale AI compute using distributed electricity production There is power available all around the world, including at our Supercharger sites. We have something like 7 gigawatts of power across the Supercharger network, and that continues to grow We could place Megapods at many of these locations and use that distributed power for AI compute I think that could be quite a big deal” Instead of relying entirely on enormous centralized data centers, Tesla could deploy modular AI-compute infrastructure wherever sufficient power is already available

X Freeze

17,025 просмотров • 15 дней назад

ELON MUSK: The Future of AI Power is in Space, Not on Earth. "Once you start thinking in terms of what percentage of the sun's power are you harnessing? You realize you have to go to space and you can't scale very much on Earth. All of the United States currently uses only half a terawatt per hour on average. So you know, if you say a terawatt, that would be twice as much electricity as the United States currently consumes. So that's quite a lot. It's actually very difficult to build power plants and then you don't just need the power plants, you need all of the electrical equipment. Need the electrical transformers to run the transformers. You can build power plants. That's what we did at xAI for Colossus 2. It's very difficult to scale other forms of power. You can scale potentially solar. Solar cells are already very cheap. Now put it in space and it's 10 times cheaper because you don't need any batteries. So the moment your cost of access to space becomes low. By far, the cheapest and most scalable way to generate tokens is space. It's not even close. It'll be an order of magnitude easier to scale five years from now. My prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth."
2:09

ELON MUSK: The Future of AI Power is in Space, Not on Earth. "Once you start thinking in terms of what percentage of the sun's power are you harnessing? You realize you have to go to space and you can't scale very much on Earth. All of the United States currently uses only half a terawatt per hour on average. So you know, if you say a terawatt, that would be twice as much electricity as the United States currently consumes. So that's quite a lot. It's actually very difficult to build power plants and then you don't just need the power plants, you need all of the electrical equipment. Need the electrical transformers to run the transformers. You can build power plants. That's what we did at xAI for Colossus 2. It's very difficult to scale other forms of power. You can scale potentially solar. Solar cells are already very cheap. Now put it in space and it's 10 times cheaper because you don't need any batteries. So the moment your cost of access to space becomes low. By far, the cheapest and most scalable way to generate tokens is space. It's not even close. It'll be an order of magnitude easier to scale five years from now. My prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth."

DogeDesigner

37,916 просмотров • 6 месяцев назад

Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)
0:53

Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)

Rohan Paul

334,691 просмотров • 10 месяцев назад

Etched is deploying two new technologies in chip design: low-voltage inference and cluster-scale memory. CEO Gavin Uberti says they'll make their chips much more power-efficient and way, way faster than today's leading GPUs. He breaks it down: "We looked at a lot of early research directions, and we realized the key things that models need are way more compute and way faster memory." "If you think about inference, there are two key parts: prefill and decode. For prefill, it's a compute-bound problem. You need to have more FLOPS, more operations per second on each of your chips." "On our GPU, the bottleneck's actually thermals. You can't really run a GPU at more than around 50% of what it could theoretically do, or it'll melt." "So we're using a new technology today called low-voltage inference to try to solve this problem. You bring the voltage of the chip down dramatically, which allows us to have way, way better efficiency in terms of how much power is drawn per unit of math, and thus fit way way more flops onto the chip..." "For decode, it's all about bandwidth. Not just bandwidth on a chip, but bandwidth across your cluster. That's why we have this technology we call cluster-scale memory. It reduces the amount of time it takes to communicate from one chip to another dramatically." "As a result we can go use all of our HBM, HBM bandwidth, SRAM, SRAM bandwidth, and our scale-up domain as a single coherent pool. And that means if you're a user, you can go get much faster tokens per second, while still keeping your costs low."
3:19

Etched is deploying two new technologies in chip design: low-voltage inference and cluster-scale memory. CEO Gavin Uberti says they'll make their chips much more power-efficient and way, way faster than today's leading GPUs. He breaks it down: "We looked at a lot of early research directions, and we realized the key things that models need are way more compute and way faster memory." "If you think about inference, there are two key parts: prefill and decode. For prefill, it's a compute-bound problem. You need to have more FLOPS, more operations per second on each of your chips." "On our GPU, the bottleneck's actually thermals. You can't really run a GPU at more than around 50% of what it could theoretically do, or it'll melt." "So we're using a new technology today called low-voltage inference to try to solve this problem. You bring the voltage of the chip down dramatically, which allows us to have way, way better efficiency in terms of how much power is drawn per unit of math, and thus fit way way more flops onto the chip..." "For decode, it's all about bandwidth. Not just bandwidth on a chip, but bandwidth across your cluster. That's why we have this technology we call cluster-scale memory. It reduces the amount of time it takes to communicate from one chip to another dramatically." "As a result we can go use all of our HBM, HBM bandwidth, SRAM, SRAM bandwidth, and our scale-up domain as a single coherent pool. And that means if you're a user, you can go get much faster tokens per second, while still keeping your costs low."

TBPN

20,404 просмотров • 1 месяц назад

AMD CEO LISA SU HAS SAID THE WORLD NEEDS ANOTHER 100X MORE COMPUTE IN THE NEXT 4-5 YEARS She even coined a unit for where that leads: the yottaflop. That is 10 to the 24th power in flops, a one followed by 24 zeros, roughly 100 times more compute than exists today. Her answer to what all of it is for: today's models are already strong, but "it can get so much better." The use case she calls closest to home is writing software, where AI tools are already lifting developer productivity. "AI is really gonna be everywhere and it's really for everyone." Where she thinks we are: "still in the very early innings of really unlocking the power of AI."
1:21

AMD CEO LISA SU HAS SAID THE WORLD NEEDS ANOTHER 100X MORE COMPUTE IN THE NEXT 4-5 YEARS She even coined a unit for where that leads: the yottaflop. That is 10 to the 24th power in flops, a one followed by 24 zeros, roughly 100 times more compute than exists today. Her answer to what all of it is for: today's models are already strong, but "it can get so much better." The use case she calls closest to home is writing software, where AI tools are already lifting developer productivity. "AI is really gonna be everywhere and it's really for everyone." Where she thinks we are: "still in the very early innings of really unlocking the power of AI."

WOLF

212,885 просмотров • 20 дней назад

FULL TRANSCRIPT OF ELON'S CYBERCAB AND ROBOVAN PRESENTATION 00:00 Welcome 01:16 Cybercab & Future of transportation 04:33 Cost 05:53 Timeline 07:13 Self-driving technology 10:05 Inductive charging 10:24 The cities of the future 11:04 Robovan 12:13 Optimus Welcome Welcome to the We, Robot party. We have quite a show for you tonight. I think you're going to like it. As you can see, I just arrived in the Robotaxi, the Cybercab. And there's 20 more where that came from. So they've been traveling, there's no people in them. As you can see, the car is just going by with no people. We have 50 fully autonomous cars here tonight. So you'll see model Y's and the Cybercabs, all driverless. You'll be able to take a ride in the Cybercab. There's no steering wheel or pedals. So I hope this goes well, we'll find out. You see a lot of sci-fi movies where the future is dark and dismal, where it's not a future you want to be in. So, you know, I love Blade Runner, but I don't know if we want that future. We want that duster he's wearing, but not the bleak apocalypse. We want to have a fun, exciting future that, if you could look in a crystal ball and see the future, you'd be like, yes, I wish I could be there now. That's what we want. Cybercab & Future of transportation So, when we think about transport today, there's a lot of pain that we take for granted, that we think is normal. Like having to drive around LA in 3 hours of traffic. Yeah, people that live in LA, I mean, you know, try to get from Pasadena to El Segundo during rush hour. You can fly to another city faster than you can get to LA. And you have to drive the whole way, unless you're in a Tesla. Of course, our Tesla already does quite well at this supervised self-driving. So, supervised full self-driving is actually working quite well. I'm sure there's people in the crowd who are using that. So, we'll move from supervised full self-driving to unsupervised full self-driving where the car, you could fall asleep and wake up at your destination. But there's also a challenge for a lot of people that cars cost too much. I mean, when you factor in everything that goes into a car and the car insurance and the car payments, storage of the car, it's very expensive. You say, like, how many hours a week are cars used? Your average passenger car is only used about 10 hours a week out of 168 hours. So, the vast majority of the time cars are just doing nothing. But if they're autonomous, they could be used, I don't know, five times more, maybe ten times more. So you could actually, for the same car, would have five times as much value, maybe ten times as much value. There's 168 hours in the week, and like I said, only ten of them are used for driving. And then, a bunch of those hours are looking for a parking spot, which can be pretty annoying at times. So, with autonomy, you get your time back. This is a very big deal. So it's not just, it'll save lives, like a lot of lives and prevent injuries. I think we'll see autonomous cars become ten times safer than a human. I mean, if you think of times past where there used to be an elevator operator in every elevator but once in a while, they get tired and accidentally shear somebody in half. Now, we have automated elevators. You just get an elevator and you press a button and you don't even think about it and it just takes you to the floor. And if you did see an elevator operator with a big relay switch, you'd be like, that's weird. That's how cars will be. And it's not just the lives saved in injuries, but if you think about the cumulative time that people spend in a car and the time that they will get back that they can now spend, well, I guess, on their phones or watching a movie or doing work or whatever you want to do you can think of the car in autonomous world as being like just little lounge. You're just sitting in a comfortable little lounge and you can do whatever you want while you're in this comfortable little lounge. And when you get out, you will be at your destination. So, yeah, it's gonna be awesome. Cost So, in fact, I think the cost of autonomous transport will be so low that you can think of it like individualized mass transit. The average cost of a bus per mile for a city, not the ticket price, because that is subsidized, but the average price is about a dollar a mile, whereas the cost of Cybercab we think probably over time, the operating cost is probably going to be around twenty cents a mile. Including taxes and everything else, it probably ends up being 30 or 40 cents a mile. And you will be able to buy one. And we expect the cost to be below $30,000. And I think there'll be an interesting business model where, let's say somebody is an Uber or Lyft driver today where they can actually sort of manage a fleet of cars and like, sort of manage, I don't know, 10, 20 cars and just take care of them. Like a shepherd tends their flock. You have a little flock of cars and you're the shepherd and you take care of your flock of cars. I think that would be pretty cool. I think it's going to be a glorious future. It's going to be really something special. Timeline We do expect actually to start fully autonomous unsupervised FSD in Texas and California next year. And that's obviously, that's with the Model 3 and Model Y. And then we expect to be in production with the Cybercab, which is really highly optimized for autonomous transport in probably, I tend to be a little optimistic with time frames, but in 2026. So, yeah, before 2027, let me put it that way. And we'll make this vehicle in very high volume. But well, before that, you will experience a robotic taxi via the Model 3 and Model Y program and model S and X, too. But the Model 3 and Y will achieve unsupervised full self-driving with permission, in wherever regulators essentially approve it. In the US, and then to follow outside the US. And Cybertruck, too. All our cars are basically, all cars that we make. Let's not get nuanced here. Self-driving technology One of the reasons why the computer can be so much better than a person is that we have millions of cars that are training on driving. It's like living millions of lives simultaneously and seeing very unusual situations that a person in their entire lifetime would not see. With that amount of training data, it's obviously going to be much better than what a human could be because you can't live a million lives. And it's also, it can see in all directions simultaneously and it doesn't get tired or text or any of those things. So, it will naturally be, like I said 10, 20, 30 times safer than a human, just for all those reasons. And I want to emphasize that the solution that we have is, AI and vision. So, there's no expensive equipment needed. The Model 3 and Model Y and S and X that we make today will be capable of full autonomy, unsupervised. And that means that our cost of producing the vehicle is low. Now, we are going to actually over-spec the computer for the Cybercab. So, our AI 5 computer will be somewhat over-spec'd because I think there's actually also an opportunity, sort of like an Amazon Web Services, where if the car is driving for 50 hours a week, there's still over 100 hours left and there's a potential there to have a massive amount of distributed inference compute, where if you've got like a fleet of 100 million vehicles and a kilowatt of efficient inference compute, you have 100 gigawatts of compute, which is really quite substantial. And if it's there, you might as well use it so that I think will make sense. So, our autonomous future is here. As I said, we've got 50 Teslas driving autonomously. We're trying to give you a sense of what cities will be like in the future. And when you get in, you'll see like, it's really quite a wild experience to just be in a car with no steering wheel, no pedals, no controls, and it feels great. So we have enough vehicles here, so everyone should be able to try it out and experience the set that we've built here. It's a very big set. So it's like really we've used I don't know, 20, 30 acres or something like that. It's really big. So, it goes on, the ride's long. And we set it up to feel like a ride, like a park ride. So, it'll be cool and you'll get to experience it tonight. Inductive charging Something we're also doing is and it's really high time we did this is inductive charging. So, the robotaxi has no plug. It just goes over the inductive charger and charges. So, yeah, it's kind of how it should be. The cities of the future One of the things that is really interesting is how will this affect the cities that we live in. And when you drive around a city, or when the car drives you around the city, you'll see there's a lot of parking lots. There's parking lots everywhere, parking garages. What would happen if you have an autonomous world is that you can now turn parking lots into parks. And so, from we're taking the inglot out of parking lot. You're welcome. So, there's a lot of opportunity to create green space in the cities that we live in. So, like, that would be quite fantastic. Robovan Oh, and also, what happens if you need a vehicle that is bigger than a Model Y? The Robovan. We're going to make this and it's going to look like that. Now, can you imagine going down the streets and you see this coming towards you? That'd be sick. So this can carry up to 20 people, and it can also transport goods. You can configure it for goods transport within a city. Or transport of up to 20 people at a time. The Robovan is what's gonna solve for high density. If you want to take a sports team somewhere or you're looking to really get the cost of travel down to, I don't know, 5, 10 cents a mile, then you can use the Robovan. One of the things we want to do, and we've seen this with the Cybertruck, is we want to change the look of the roads. The future should look like the future. Optimus Speaking of robots. Everything we've developed for our cars, the batteries, power electronics, the advanced motors, gearboxes, the software, the AI inference computer, it all actually applies to a humanoid robot. The same techniques. It's just a robot with arms and legs instead of a robot with wheels. We've made a lot of progress with Optimus. And as you can see, we started up with someone in a robot suit. And then, we've progressed dramatically, year after year. So, if you extrapolate this, you're really going to have something spectacular, something that anyone could own. So, you can have your own personal R2-D2-C3PO. And I think at scale, this would cost something like, I don't know, $20,000, $30,000, probably less than a car is my prediction, long-term. It'll take us a minute to get to the long term. But fundamentally, at scale, the Optimus robot, you should be able to buy an Optimus robot for, I think, probably $20,000 to $30,000, long-term. And what can it do? It'll basically do anything you want. It can be a teacher or babysit your kids, it can walk your dog, mow your lawn, get the groceries, just be your friend, serve drinks whatever you can think of, it will do. And, yeah, it's going to be awesome. I think this will be the biggest product ever of any kind, because I think everyone of the 8 billion people of Earth, I think everyone's going to want their Optimus buddy. And there's going to be maybe two. And then, they'll be producing products and services. I predict, actually, provided we address risks of digital superintelligence, 80% probability of good outcome, look on the bright side, the cup is 80% full, the cost of products and services will decline dramatically. And basically, anyone will be able to have any products and services they want. It will be an age of abundance the likes of which people have not, almost no one has envisioned. It will be something special. So now, one of the things we wanted to show tonight was that Optimus is not a canned video. It's not walled off. The Optimus robots will walk among you. Please, please be nice to the Optimus robots. You'll be able to walk right up to them and they'll serve drinks at the bar. I mean, it's a wild experience just to have humanoid robots and they're there, you're just in front of you. So yeah, with that, let's party!
15:37

FULL TRANSCRIPT OF ELON'S CYBERCAB AND ROBOVAN PRESENTATION 00:00 Welcome 01:16 Cybercab & Future of transportation 04:33 Cost 05:53 Timeline 07:13 Self-driving technology 10:05 Inductive charging 10:24 The cities of the future 11:04 Robovan 12:13 Optimus Welcome Welcome to the We, Robot party. We have quite a show for you tonight. I think you're going to like it. As you can see, I just arrived in the Robotaxi, the Cybercab. And there's 20 more where that came from. So they've been traveling, there's no people in them. As you can see, the car is just going by with no people. We have 50 fully autonomous cars here tonight. So you'll see model Y's and the Cybercabs, all driverless. You'll be able to take a ride in the Cybercab. There's no steering wheel or pedals. So I hope this goes well, we'll find out. You see a lot of sci-fi movies where the future is dark and dismal, where it's not a future you want to be in. So, you know, I love Blade Runner, but I don't know if we want that future. We want that duster he's wearing, but not the bleak apocalypse. We want to have a fun, exciting future that, if you could look in a crystal ball and see the future, you'd be like, yes, I wish I could be there now. That's what we want. Cybercab & Future of transportation So, when we think about transport today, there's a lot of pain that we take for granted, that we think is normal. Like having to drive around LA in 3 hours of traffic. Yeah, people that live in LA, I mean, you know, try to get from Pasadena to El Segundo during rush hour. You can fly to another city faster than you can get to LA. And you have to drive the whole way, unless you're in a Tesla. Of course, our Tesla already does quite well at this supervised self-driving. So, supervised full self-driving is actually working quite well. I'm sure there's people in the crowd who are using that. So, we'll move from supervised full self-driving to unsupervised full self-driving where the car, you could fall asleep and wake up at your destination. But there's also a challenge for a lot of people that cars cost too much. I mean, when you factor in everything that goes into a car and the car insurance and the car payments, storage of the car, it's very expensive. You say, like, how many hours a week are cars used? Your average passenger car is only used about 10 hours a week out of 168 hours. So, the vast majority of the time cars are just doing nothing. But if they're autonomous, they could be used, I don't know, five times more, maybe ten times more. So you could actually, for the same car, would have five times as much value, maybe ten times as much value. There's 168 hours in the week, and like I said, only ten of them are used for driving. And then, a bunch of those hours are looking for a parking spot, which can be pretty annoying at times. So, with autonomy, you get your time back. This is a very big deal. So it's not just, it'll save lives, like a lot of lives and prevent injuries. I think we'll see autonomous cars become ten times safer than a human. I mean, if you think of times past where there used to be an elevator operator in every elevator but once in a while, they get tired and accidentally shear somebody in half. Now, we have automated elevators. You just get an elevator and you press a button and you don't even think about it and it just takes you to the floor. And if you did see an elevator operator with a big relay switch, you'd be like, that's weird. That's how cars will be. And it's not just the lives saved in injuries, but if you think about the cumulative time that people spend in a car and the time that they will get back that they can now spend, well, I guess, on their phones or watching a movie or doing work or whatever you want to do you can think of the car in autonomous world as being like just little lounge. You're just sitting in a comfortable little lounge and you can do whatever you want while you're in this comfortable little lounge. And when you get out, you will be at your destination. So, yeah, it's gonna be awesome. Cost So, in fact, I think the cost of autonomous transport will be so low that you can think of it like individualized mass transit. The average cost of a bus per mile for a city, not the ticket price, because that is subsidized, but the average price is about a dollar a mile, whereas the cost of Cybercab we think probably over time, the operating cost is probably going to be around twenty cents a mile. Including taxes and everything else, it probably ends up being 30 or 40 cents a mile. And you will be able to buy one. And we expect the cost to be below $30,000. And I think there'll be an interesting business model where, let's say somebody is an Uber or Lyft driver today where they can actually sort of manage a fleet of cars and like, sort of manage, I don't know, 10, 20 cars and just take care of them. Like a shepherd tends their flock. You have a little flock of cars and you're the shepherd and you take care of your flock of cars. I think that would be pretty cool. I think it's going to be a glorious future. It's going to be really something special. Timeline We do expect actually to start fully autonomous unsupervised FSD in Texas and California next year. And that's obviously, that's with the Model 3 and Model Y. And then we expect to be in production with the Cybercab, which is really highly optimized for autonomous transport in probably, I tend to be a little optimistic with time frames, but in 2026. So, yeah, before 2027, let me put it that way. And we'll make this vehicle in very high volume. But well, before that, you will experience a robotic taxi via the Model 3 and Model Y program and model S and X, too. But the Model 3 and Y will achieve unsupervised full self-driving with permission, in wherever regulators essentially approve it. In the US, and then to follow outside the US. And Cybertruck, too. All our cars are basically, all cars that we make. Let's not get nuanced here. Self-driving technology One of the reasons why the computer can be so much better than a person is that we have millions of cars that are training on driving. It's like living millions of lives simultaneously and seeing very unusual situations that a person in their entire lifetime would not see. With that amount of training data, it's obviously going to be much better than what a human could be because you can't live a million lives. And it's also, it can see in all directions simultaneously and it doesn't get tired or text or any of those things. So, it will naturally be, like I said 10, 20, 30 times safer than a human, just for all those reasons. And I want to emphasize that the solution that we have is, AI and vision. So, there's no expensive equipment needed. The Model 3 and Model Y and S and X that we make today will be capable of full autonomy, unsupervised. And that means that our cost of producing the vehicle is low. Now, we are going to actually over-spec the computer for the Cybercab. So, our AI 5 computer will be somewhat over-spec'd because I think there's actually also an opportunity, sort of like an Amazon Web Services, where if the car is driving for 50 hours a week, there's still over 100 hours left and there's a potential there to have a massive amount of distributed inference compute, where if you've got like a fleet of 100 million vehicles and a kilowatt of efficient inference compute, you have 100 gigawatts of compute, which is really quite substantial. And if it's there, you might as well use it so that I think will make sense. So, our autonomous future is here. As I said, we've got 50 Teslas driving autonomously. We're trying to give you a sense of what cities will be like in the future. And when you get in, you'll see like, it's really quite a wild experience to just be in a car with no steering wheel, no pedals, no controls, and it feels great. So we have enough vehicles here, so everyone should be able to try it out and experience the set that we've built here. It's a very big set. So it's like really we've used I don't know, 20, 30 acres or something like that. It's really big. So, it goes on, the ride's long. And we set it up to feel like a ride, like a park ride. So, it'll be cool and you'll get to experience it tonight. Inductive charging Something we're also doing is and it's really high time we did this is inductive charging. So, the robotaxi has no plug. It just goes over the inductive charger and charges. So, yeah, it's kind of how it should be. The cities of the future One of the things that is really interesting is how will this affect the cities that we live in. And when you drive around a city, or when the car drives you around the city, you'll see there's a lot of parking lots. There's parking lots everywhere, parking garages. What would happen if you have an autonomous world is that you can now turn parking lots into parks. And so, from we're taking the inglot out of parking lot. You're welcome. So, there's a lot of opportunity to create green space in the cities that we live in. So, like, that would be quite fantastic. Robovan Oh, and also, what happens if you need a vehicle that is bigger than a Model Y? The Robovan. We're going to make this and it's going to look like that. Now, can you imagine going down the streets and you see this coming towards you? That'd be sick. So this can carry up to 20 people, and it can also transport goods. You can configure it for goods transport within a city. Or transport of up to 20 people at a time. The Robovan is what's gonna solve for high density. If you want to take a sports team somewhere or you're looking to really get the cost of travel down to, I don't know, 5, 10 cents a mile, then you can use the Robovan. One of the things we want to do, and we've seen this with the Cybertruck, is we want to change the look of the roads. The future should look like the future. Optimus Speaking of robots. Everything we've developed for our cars, the batteries, power electronics, the advanced motors, gearboxes, the software, the AI inference computer, it all actually applies to a humanoid robot. The same techniques. It's just a robot with arms and legs instead of a robot with wheels. We've made a lot of progress with Optimus. And as you can see, we started up with someone in a robot suit. And then, we've progressed dramatically, year after year. So, if you extrapolate this, you're really going to have something spectacular, something that anyone could own. So, you can have your own personal R2-D2-C3PO. And I think at scale, this would cost something like, I don't know, $20,000, $30,000, probably less than a car is my prediction, long-term. It'll take us a minute to get to the long term. But fundamentally, at scale, the Optimus robot, you should be able to buy an Optimus robot for, I think, probably $20,000 to $30,000, long-term. And what can it do? It'll basically do anything you want. It can be a teacher or babysit your kids, it can walk your dog, mow your lawn, get the groceries, just be your friend, serve drinks whatever you can think of, it will do. And, yeah, it's going to be awesome. I think this will be the biggest product ever of any kind, because I think everyone of the 8 billion people of Earth, I think everyone's going to want their Optimus buddy. And there's going to be maybe two. And then, they'll be producing products and services. I predict, actually, provided we address risks of digital superintelligence, 80% probability of good outcome, look on the bright side, the cup is 80% full, the cost of products and services will decline dramatically. And basically, anyone will be able to have any products and services they want. It will be an age of abundance the likes of which people have not, almost no one has envisioned. It will be something special. So now, one of the things we wanted to show tonight was that Optimus is not a canned video. It's not walled off. The Optimus robots will walk among you. Please, please be nice to the Optimus robots. You'll be able to walk right up to them and they'll serve drinks at the bar. I mean, it's a wild experience just to have humanoid robots and they're there, you're just in front of you. So yeah, with that, let's party!

Mario Nawfal

241,051 просмотров • 1 год назад

SAM ALTMAN BELIEVES AGI IS SOLVED “So now we're starting to look ahead to superintelligence.” - “When we started OpenAI, almost nine years ago now, we believed that AI could become the most impactful technology in human history. We didn't know exactly how we were going to get there, but we believed it was possible and that if we succeeded, we wanted to make sure that it benefited everyone. At the time, very few people believed in AGI. We kept learning by doing. We had some breakthroughs. We had some setbacks. We got lucky in some places. We got unlucky in some places. And in the way that technology moves forward, we now are in a place where everyone can see this tremendous impact that AI is going to have in the future. So now we're starting to look ahead to superintelligence. And even more than before, our focus must be on wide and fair access. This is a technology that will reshape the global economy and really the whole way we live our lives. It's critical that superintelligence becomes cheap, broadly available, and not that concentrated with any one person, company, or country. We, not just OpenAI, but the whole industry, we are building something PROFOUND. This is a kind of BRAIN OF THE WORLD. It'll be personal, adaptable, it'll be easy to use, it'll give people incredible superpowers that were sort of science fiction only a couple of years ago. The limit won't be the algorithms and the research, but it'll increasingly become the physical instantiation that it takes to make this work. Chips, cables, servers, energy, everything that you need to power this brain. And the more of it, the better. I think that Norway offers more of that potential right here in Europe. It will contribute to the overall compute power needed to drive the next wave of AI breakthroughs and deployment and economic progress for Europe and Europe. I'm incredibly excited about what this will create for the future. Thank you.”
1:38

SAM ALTMAN BELIEVES AGI IS SOLVED “So now we're starting to look ahead to superintelligence.” - “When we started OpenAI, almost nine years ago now, we believed that AI could become the most impactful technology in human history. We didn't know exactly how we were going to get there, but we believed it was possible and that if we succeeded, we wanted to make sure that it benefited everyone. At the time, very few people believed in AGI. We kept learning by doing. We had some breakthroughs. We had some setbacks. We got lucky in some places. We got unlucky in some places. And in the way that technology moves forward, we now are in a place where everyone can see this tremendous impact that AI is going to have in the future. So now we're starting to look ahead to superintelligence. And even more than before, our focus must be on wide and fair access. This is a technology that will reshape the global economy and really the whole way we live our lives. It's critical that superintelligence becomes cheap, broadly available, and not that concentrated with any one person, company, or country. We, not just OpenAI, but the whole industry, we are building something PROFOUND. This is a kind of BRAIN OF THE WORLD. It'll be personal, adaptable, it'll be easy to use, it'll give people incredible superpowers that were sort of science fiction only a couple of years ago. The limit won't be the algorithms and the research, but it'll increasingly become the physical instantiation that it takes to make this work. Chips, cables, servers, energy, everything that you need to power this brain. And the more of it, the better. I think that Norway offers more of that potential right here in Europe. It will contribute to the overall compute power needed to drive the next wave of AI breakthroughs and deployment and economic progress for Europe and Europe. I'm incredibly excited about what this will create for the future. Thank you.”

NIK

390,619 просмотров • 1 год назад

ELON: AI BOTS WILL CRUSH SOCIAL MEDIA UNLESS USERS PAY A LITTLE "One of the things we're trying to figure out on the X platform is how to deal with that because it really, we really are at the point where even with open source, readily available AI, you can actually be better than humans at passing these tests. So that’s sort of where we're thinking we might have to charge some very tiny amount of money, 0.30 cents a day effectively, to deal with the onslaught of AI-powered bots. But it will be, I think, perhaps an insurmountable problem next year. And then you have to worry about manipulation of information, making something seem very popular when in fact it is not, because it's getting boosted by likes and reposts from AI-powered bots. So somewhat inevitably it leads to some small payment in order to dramatically increase the cost of a bot. I think probably any social media system that doesn't do that will simply be overrun by bots.” Source: Vocal Vignettes Elon Musk
0:58

ELON: AI BOTS WILL CRUSH SOCIAL MEDIA UNLESS USERS PAY A LITTLE "One of the things we're trying to figure out on the X platform is how to deal with that because it really, we really are at the point where even with open source, readily available AI, you can actually be better than humans at passing these tests. So that’s sort of where we're thinking we might have to charge some very tiny amount of money, 0.30 cents a day effectively, to deal with the onslaught of AI-powered bots. But it will be, I think, perhaps an insurmountable problem next year. And then you have to worry about manipulation of information, making something seem very popular when in fact it is not, because it's getting boosted by likes and reposts from AI-powered bots. So somewhat inevitably it leads to some small payment in order to dramatically increase the cost of a bot. I think probably any social media system that doesn't do that will simply be overrun by bots.” Source: Vocal Vignettes Elon Musk

Mario Nawfal

68,426 просмотров • 8 месяцев назад

ELON MUSK: "When you have solar in space, you get five times more effectiveness, maybe even more than that, than solar on the ground, because it's always cold, so you don't have a day, night cycle or weather, and you get about 30% more power in space because you don't have atmospheric attenuation of the power, the net effect in solar is five times more. Any given solar panel will do five times more energy in space than on the ground."
0:38

ELON MUSK: "When you have solar in space, you get five times more effectiveness, maybe even more than that, than solar on the ground, because it's always cold, so you don't have a day, night cycle or weather, and you get about 30% more power in space because you don't have atmospheric attenuation of the power, the net effect in solar is five times more. Any given solar panel will do five times more energy in space than on the ground."

DogeDesigner

35,114 просмотров • 6 месяцев назад