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Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about...

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Karl Mehta

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16,619 次观看 • 3 个月前 •via X (Twitter)

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Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.
1:48

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

TBPN

21,828 次观看 • 8 个月前

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire
2:24

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

KanekoaTheGreat

39,709 次观看 • 3 个月前

🚨 Sam Altman: there's a very important thing happening. I did not expect 3 or 6 months ago to be at this point we're at now” We now have a confirmed reason why OpenAI pulled out of Sora and it was as most of us expected - because they needed to concentrate all of their compute and product capacity into their next generation of models and automated agents. Sam says: "We have a few times in our history realized something really important is working or about to work so well that we have to stop a bunch of other projects. In fact, this was the original thing happened with GPT-3. We had a whole portfolio of bets at the time... we shut down many projects that were working well like robotics... so that we could concentrate our compute, our researchers, our effort into this thing that we said, okay, there's a very important thing happening." "I did not expect 3 or 6 months ago to be at this point we're at now, where something very big and important is about to happen again with this next generation of models and the agents they can power." "We need to concentrate our compute and our product capacity into these next generation of automated researchers and companies... the note under the note is it's about compute. It's always about compute."
1:13

🚨 Sam Altman: there's a very important thing happening. I did not expect 3 or 6 months ago to be at this point we're at now” We now have a confirmed reason why OpenAI pulled out of Sora and it was as most of us expected - because they needed to concentrate all of their compute and product capacity into their next generation of models and automated agents. Sam says: "We have a few times in our history realized something really important is working or about to work so well that we have to stop a bunch of other projects. In fact, this was the original thing happened with GPT-3. We had a whole portfolio of bets at the time... we shut down many projects that were working well like robotics... so that we could concentrate our compute, our researchers, our effort into this thing that we said, okay, there's a very important thing happening." "I did not expect 3 or 6 months ago to be at this point we're at now, where something very big and important is about to happen again with this next generation of models and the agents they can power." "We need to concentrate our compute and our product capacity into these next generation of automated researchers and companies... the note under the note is it's about compute. It's always about compute."

Chris

243,817 次观看 • 6 个月前

Elon Musk: Now we’re going to look at the computer for the Cybercab. The computer will be somewhat overspecified, but I think there’s a major opportunity here. Similar to Amazon Web Services, if the car is driving for 50 hours a week, that leaves more than 100 hours where the compute is sitting there unused. You could use that idle compute for distributed inference. If you have a fleet of 100 million vehicles, each with roughly a kilowatt of efficient inference compute, that’s about 100 GW of compute. That’s a massive amount of compute. And if it’s already there, you might as well use it. I think that makes a lot of sense. The autonomous future is here.
0:53

Elon Musk: Now we’re going to look at the computer for the Cybercab. The computer will be somewhat overspecified, but I think there’s a major opportunity here. Similar to Amazon Web Services, if the car is driving for 50 hours a week, that leaves more than 100 hours where the compute is sitting there unused. You could use that idle compute for distributed inference. If you have a fleet of 100 million vehicles, each with roughly a kilowatt of efficient inference compute, that’s about 100 GW of compute. That’s a massive amount of compute. And if it’s already there, you might as well use it. I think that makes a lot of sense. The autonomous future is here.

Tesla Owners Silicon Valley

58,180 次观看 • 7 天前

Mark Zuckerberg says he is not an AI researcher -- so here is the one number he obsesses over to win the superintelligence race: "I'm not an AI researcher. So it's not like I'm in there telling them what research ideas to do." "The things that I can do as CEO of the company are: I can make sure that we have the very best people and talent density. I can make sure that we have by far the highest compute per researcher, and that we do whatever it takes to go build out all that capacity." "We're building this Prometheus cluster, which is going to be the first gigawatt-plus single cluster, a contiguous cluster for training, coming online next year." "We're building a cluster in Louisiana that is going to be 5 gigawatt, and we're building several more clusters like that that are just going to be multiple gigawatts." "We're talking about many hundreds of billions of dollars of capital. So you both need to have a good business model that can support it, and you need to believe in it." The tell: the richest lab in the world is not optimizing headcount. It is optimizing compute-per-researcher, and betting hundreds of billions that whoever owns the biggest contiguous cluster owns the frontier. Talent gets you into the room. Watts decide who leaves with the model.
1:06

Mark Zuckerberg says he is not an AI researcher -- so here is the one number he obsesses over to win the superintelligence race: "I'm not an AI researcher. So it's not like I'm in there telling them what research ideas to do." "The things that I can do as CEO of the company are: I can make sure that we have the very best people and talent density. I can make sure that we have by far the highest compute per researcher, and that we do whatever it takes to go build out all that capacity." "We're building this Prometheus cluster, which is going to be the first gigawatt-plus single cluster, a contiguous cluster for training, coming online next year." "We're building a cluster in Louisiana that is going to be 5 gigawatt, and we're building several more clusters like that that are just going to be multiple gigawatts." "We're talking about many hundreds of billions of dollars of capital. So you both need to have a good business model that can support it, and you need to believe in it." The tell: the richest lab in the world is not optimizing headcount. It is optimizing compute-per-researcher, and betting hundreds of billions that whoever owns the biggest contiguous cluster owns the frontier. Talent gets you into the room. Watts decide who leaves with the model.

Karl Mehta

255,725 次观看 • 2 个月前

ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "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, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez
1:36

ELON: AI WILL HARNESS THE POWER OF THE SUN AND GALAXY FOR COMPUTE "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, you know, sort of cloud Kardashev two, Kardashev three scale compute. So I guess once you think of artificial intelligence not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of." Source: Jon Hernandez

Mario Nawfal

1,668,111 次观看 • 10 个月前

The cheapest place to put AI will be space. Elon Musk says solar panels in space produce 5 times more power than on the ground. No atmosphere, no clouds, no day-night cycle. No batteries needed. And critically, no permits. Scaling energy on Earth means fighting land use regulations, environmental reviews, and grid interconnection queues that take years. Space has none of that. The math gets wild fast. SpaceX could launch hundreds of gigawatts of AI compute into orbit annually. That's more compute than currently exists on Earth. Ten thousand Starship launches per year. One launch every hour. And you only need 20 to 30 ships to sustain that cadence. Earth gets about half a billionth of the Sun's total energy output. A millionth of the Sun's energy is 100,000 times all of civilization's current electricity production. The AI race is not a software race. It is a power plant race. And software people are about to get a very hard lesson in hardware.
2:19

The cheapest place to put AI will be space. Elon Musk says solar panels in space produce 5 times more power than on the ground. No atmosphere, no clouds, no day-night cycle. No batteries needed. And critically, no permits. Scaling energy on Earth means fighting land use regulations, environmental reviews, and grid interconnection queues that take years. Space has none of that. The math gets wild fast. SpaceX could launch hundreds of gigawatts of AI compute into orbit annually. That's more compute than currently exists on Earth. Ten thousand Starship launches per year. One launch every hour. And you only need 20 to 30 ships to sustain that cadence. Earth gets about half a billionth of the Sun's total energy output. A millionth of the Sun's energy is 100,000 times all of civilization's current electricity production. The AI race is not a software race. It is a power plant race. And software people are about to get a very hard lesson in hardware.

Shruti

11,700 次观看 • 3 个月前

OpenAI does not want to become the application layer of AI; it wants to be the platform that other application companies build on. "I think we should be more of a platform company than a product company. We will build products, of course. What I think most people want is a sort of single interface to their own personal, or their company's, AGI that can kind of help them with whatever they need, and then the ability, with an API, to build anything they want on top of it. That is the platform that we should offer to the world. We're going to sell great AI at every point on the cost-performance curve. We will be the best. You want really high-end AI to discover science? That's great. You want really inexpensive AI to do a massive amount of work that maybe doesn't require genius-level intelligence? We've got you covered there too." - Sam Altman on David Senra podcast (full video in the quoted tweet)
1:28

OpenAI does not want to become the application layer of AI; it wants to be the platform that other application companies build on. "I think we should be more of a platform company than a product company. We will build products, of course. What I think most people want is a sort of single interface to their own personal, or their company's, AGI that can kind of help them with whatever they need, and then the ability, with an API, to build anything they want on top of it. That is the platform that we should offer to the world. We're going to sell great AI at every point on the cost-performance curve. We will be the best. You want really high-end AI to discover science? That's great. You want really inexpensive AI to do a massive amount of work that maybe doesn't require genius-level intelligence? We've got you covered there too." - Sam Altman on David Senra podcast (full video in the quoted tweet)

Rohan Paul

25,077 次观看 • 1 个月前

Sam Altman: "I think we should be more of a platform company than a product company.” “We just merged ChatGPT and Codex together. So we used to have ChatGPT, Codex, and the API. And Codex, sort of unfortunately named, but that was not just coding, it could do any kind of work, which confused people." “What I think most people want is the single interface to their own personal or their company's AGI that can kind of help them with whatever they need. And then the ability with an API to build anything they want on top of it. And that is the platform that we should offer to the world." “We're going to sell great AI at every point on the cost-performance curve. You want really high end AI to discover science, that's great. You want really inexpensive AI to do a massive amount of volume of work that maybe doesn't require genius level intelligence, we got you covered there too.” “I don't think we should go build every product category. I don't think we should go try to compete with all of our customers. I don't think we should try to subsume the entire economy. I think we should offer this platform and try to have 100 million new businesses and 8 billion people use it in all kinds of new ways."
2:11

Sam Altman: "I think we should be more of a platform company than a product company.” “We just merged ChatGPT and Codex together. So we used to have ChatGPT, Codex, and the API. And Codex, sort of unfortunately named, but that was not just coding, it could do any kind of work, which confused people." “What I think most people want is the single interface to their own personal or their company's AGI that can kind of help them with whatever they need. And then the ability with an API to build anything they want on top of it. And that is the platform that we should offer to the world." “We're going to sell great AI at every point on the cost-performance curve. You want really high end AI to discover science, that's great. You want really inexpensive AI to do a massive amount of volume of work that maybe doesn't require genius level intelligence, we got you covered there too.” “I don't think we should go build every product category. I don't think we should go try to compete with all of our customers. I don't think we should try to subsume the entire economy. I think we should offer this platform and try to have 100 million new businesses and 8 billion people use it in all kinds of new ways."

dnap

322,713 次观看 • 1 个月前

“There are more companies than ideas by quite a bit. Compute is large enough such that it's not obvious that you need that much more compute to prove some idea. AlexNet was built on 2 GPUs. The transformer was built on 8 to 64 GPUs. Which would be, what, 2 GPUs of today? You could argue that o1 reasoning was not the most compute heavy thing in the world. For research, you definitely need some amount of compute, but it's far from obvious that you need the absolutely largest amount of compute. If everyone is within the same paradigm, then compute becomes one of the big differentiators.” Ilya Sutskever
2:03

“There are more companies than ideas by quite a bit. Compute is large enough such that it's not obvious that you need that much more compute to prove some idea. AlexNet was built on 2 GPUs. The transformer was built on 8 to 64 GPUs. Which would be, what, 2 GPUs of today? You could argue that o1 reasoning was not the most compute heavy thing in the world. For research, you definitely need some amount of compute, but it's far from obvious that you need the absolutely largest amount of compute. If everyone is within the same paradigm, then compute becomes one of the big differentiators.” Ilya Sutskever

Dwarkesh Patel

203,605 次观看 • 10 个月前

ELON MUSK: The future is fundamentally AI and Robots. “Our AI revenue will exceed all other SpaceX revenue probably in September, like next month, and will significantly exceed all other SpaceX revenue in the fourth quarter. So, AI has become an extremely important part of SpaceX’s future. I think it’s actually vital that we succeed in AI, not just in hardware, but also in software. So, yeah, the future is fundamentally AI and robots. Assuming civilization continues to progress, I think that AI will probably, the amount of digital intelligence will probably be more than a trillion times the amount of biological intelligence. So, not sort of equal to human intelligence, but probably a trillion times higher. I’d say a billion times higher than the amount of artificial intelligence that we have today. I’d say a billion times is an easy prediction, and probably a trillion. So, as you harness more and more of the sun’s energy, the ability to turn that into intelligence is fundamentally a digital computer thing, because it’s pretty hard for humans to go live in deep space without any support. I mean, some of the math is interesting to think about, which is that if you increased civilizational energy usage, the amount of energy that we have harnessed as a civilization by a factor of a million, you would still be using much less than one millionth of the sun’s energy. Now, most of this is in deep space, obviously, but the future is very much AI, very much, and I suppose it was always going to be that way. But it’s important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems, and this is why I think it’s essential that SpaceX succeed, not just with AI hardware, but also with AI software.”
3:08

ELON MUSK: The future is fundamentally AI and Robots. “Our AI revenue will exceed all other SpaceX revenue probably in September, like next month, and will significantly exceed all other SpaceX revenue in the fourth quarter. So, AI has become an extremely important part of SpaceX’s future. I think it’s actually vital that we succeed in AI, not just in hardware, but also in software. So, yeah, the future is fundamentally AI and robots. Assuming civilization continues to progress, I think that AI will probably, the amount of digital intelligence will probably be more than a trillion times the amount of biological intelligence. So, not sort of equal to human intelligence, but probably a trillion times higher. I’d say a billion times higher than the amount of artificial intelligence that we have today. I’d say a billion times is an easy prediction, and probably a trillion. So, as you harness more and more of the sun’s energy, the ability to turn that into intelligence is fundamentally a digital computer thing, because it’s pretty hard for humans to go live in deep space without any support. I mean, some of the math is interesting to think about, which is that if you increased civilizational energy usage, the amount of energy that we have harnessed as a civilization by a factor of a million, you would still be using much less than one millionth of the sun’s energy. Now, most of this is in deep space, obviously, but the future is very much AI, very much, and I suppose it was always going to be that way. But it’s important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems, and this is why I think it’s essential that SpaceX succeed, not just with AI hardware, but also with AI software.”

DogeDesigner

68,365 次观看 • 1 个月前

ELON: AI CLUSTERS WILL BECOME A NORMAL THING EVERY COUNTRY HAS Compute is becoming a new currency. While building a "frontier model" today is a high-stakes gauntlet that requires a level of technical skill only a few companies possess, he predicts that AI compute clusters are about to become as essential to a nation as a power grid or a military. By 2026, "AI Sovereignty" will be the only thing keeping nations from becoming digital colonies of Silicon Valley or Beijing: “Probably all countries will have their own AI clusters over time. It is currently very difficult to actually build an AI cluster and have it run... because if you are 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 is just going to be a normal thing that every country has.” Source: vitrupo Elon Musk
1:03

ELON: AI CLUSTERS WILL BECOME A NORMAL THING EVERY COUNTRY HAS Compute is becoming a new currency. While building a "frontier model" today is a high-stakes gauntlet that requires a level of technical skill only a few companies possess, he predicts that AI compute clusters are about to become as essential to a nation as a power grid or a military. By 2026, "AI Sovereignty" will be the only thing keeping nations from becoming digital colonies of Silicon Valley or Beijing: “Probably all countries will have their own AI clusters over time. It is currently very difficult to actually build an AI cluster and have it run... because if you are 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 is just going to be a normal thing that every country has.” Source: vitrupo Elon Musk

Mario Nawfal

20,502 次观看 • 9 个月前

"It all comes down to compute." Dmitri Alperovitch from Silverado Policy Accelerator explains: "The single most important input to winning is compute the processing power used to train and run AI models. Let me say that plainly, because it is defining that everything that congress and this committee do on AI policy. The binding constraint in this competition is not talent, it is not data, and it is not cash. Both the United States and China have talented researchers and financial resources, and we have learned that frontier models trained on generic data routinely outperform smaller models, trained on more specialized inputs. It all comes down to compute."
0:33

"It all comes down to compute." Dmitri Alperovitch from Silverado Policy Accelerator explains: "The single most important input to winning is compute the processing power used to train and run AI models. Let me say that plainly, because it is defining that everything that congress and this committee do on AI policy. The binding constraint in this competition is not talent, it is not data, and it is not cash. Both the United States and China have talented researchers and financial resources, and we have learned that frontier models trained on generic data routinely outperform smaller models, trained on more specialized inputs. It all comes down to compute."

Select Committee on China

41,578 次观看 • 5 个月前

🚨ELON: AI COMPUTE WILL BE CHEAPEST IN SPACE “Once we get solar domestically at scale and launch Starship at scale, the cheapest way to do AI compute will be in space. With full reusability, propellant cost per flight is close to a million dollars... That’s about a million dollars to transport 10 megawatts of AI compute.” Source: Philip Johnston
1:29

🚨ELON: AI COMPUTE WILL BE CHEAPEST IN SPACE “Once we get solar domestically at scale and launch Starship at scale, the cheapest way to do AI compute will be in space. With full reusability, propellant cost per flight is close to a million dollars... That’s about a million dollars to transport 10 megawatts of AI compute.” Source: Philip Johnston

Mario Nawfal

35,283 次观看 • 8 个月前

Elon Musk laid out the most ambitious compute expansion in human history and it ends with harnessing the Sun "We'll be launching with SpaceX orbital data centers at the 100 to 200 gigawatt per year level. Not cumulative; I mean per year" And this is just step one, the next step is Scale further from Earth to launch a full terawatt per year of AI compute into orbit It gets even crazier from here When even a terawatt isn't enough....Go to the Moon. Build factories. Build AI satellites Deploy a mass driver - the thing you only read about in sci-fi novels and push output to thousands of gigawatts per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the sun's energy "It's difficult to imagine what an intelligence of that scale would think about but it's going to be incredibly exciting"
1:13

Elon Musk laid out the most ambitious compute expansion in human history and it ends with harnessing the Sun "We'll be launching with SpaceX orbital data centers at the 100 to 200 gigawatt per year level. Not cumulative; I mean per year" And this is just step one, the next step is Scale further from Earth to launch a full terawatt per year of AI compute into orbit It gets even crazier from here When even a terawatt isn't enough....Go to the Moon. Build factories. Build AI satellites Deploy a mass driver - the thing you only read about in sci-fi novels and push output to thousands of gigawatts per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the sun's energy "It's difficult to imagine what an intelligence of that scale would think about but it's going to be incredibly exciting"

X Freeze

16,467 次观看 • 6 个月前

How can OpenAI with $13 billion in revenues make $1.4 trillion of spend commitments? (Source: Bg2 Pod ) Sam Altman: “First of all. We’re doing well more revenue than that. Second of all, Brad, if you want to sell your shares, I'll find you a buyer. I just, enough. I think there's a lot of people who would love to buy OpenAI shares. I think people who talk with a lot of breathless concern about our compute stuff or whatever, that would be thrilled to buy shares. So I think we could sell your shares or anybody else's to some of the people who are making the most noise on Twitter about this very quickly. We do plan for revenue to grow steeply. Revenue is growing steeply. We are taking a forward bet that it's going to continue to grow and that not only will ChatGPT keep growing, but we will be able to become one of the important AI clouds, that our consumer device business will be a significant and important thing, that AI that can automate science will create huge value. There are not many times that I want to be a public company, but one of the rare times it's appealing is when those people are writing these ridiculous OpenAI is about to go out of business. I would love to tell them they could just short the stock, and I would love to see them get burned on that. But we carefully plan. We understand where the technology, where the capability is going to grow and how the products we can build around that and the revenue we can generate. We might screw it up. This is the bet that we're making and we're taking a risk along with that. A certain risk is if we don't have the compute, we will not be able to generate the revenue or make the models at this kind of scale.” Satya Nadella: “And let me just say one thing as both a partner and an investor. There is not been a single business plan that I've seen from OpenAI that they've put in and not beaten it. So in some sense, this is the one place where in terms of their growth and just even the business, it's been unbelievable execution, quite frankly. I mean, obviously, OpenAI, everyone talks about all the success and the usage and what have you. But even I'd say all up, the business execution has been just pretty unbelievable.”
2:19

How can OpenAI with $13 billion in revenues make $1.4 trillion of spend commitments? (Source: Bg2 Pod ) Sam Altman: “First of all. We’re doing well more revenue than that. Second of all, Brad, if you want to sell your shares, I'll find you a buyer. I just, enough. I think there's a lot of people who would love to buy OpenAI shares. I think people who talk with a lot of breathless concern about our compute stuff or whatever, that would be thrilled to buy shares. So I think we could sell your shares or anybody else's to some of the people who are making the most noise on Twitter about this very quickly. We do plan for revenue to grow steeply. Revenue is growing steeply. We are taking a forward bet that it's going to continue to grow and that not only will ChatGPT keep growing, but we will be able to become one of the important AI clouds, that our consumer device business will be a significant and important thing, that AI that can automate science will create huge value. There are not many times that I want to be a public company, but one of the rare times it's appealing is when those people are writing these ridiculous OpenAI is about to go out of business. I would love to tell them they could just short the stock, and I would love to see them get burned on that. But we carefully plan. We understand where the technology, where the capability is going to grow and how the products we can build around that and the revenue we can generate. We might screw it up. This is the bet that we're making and we're taking a risk along with that. A certain risk is if we don't have the compute, we will not be able to generate the revenue or make the models at this kind of scale.” Satya Nadella: “And let me just say one thing as both a partner and an investor. There is not been a single business plan that I've seen from OpenAI that they've put in and not beaten it. So in some sense, this is the one place where in terms of their growth and just even the business, it's been unbelievable execution, quite frankly. I mean, obviously, OpenAI, everyone talks about all the success and the usage and what have you. But even I'd say all up, the business execution has been just pretty unbelievable.”

tae kim

1,566,511 次观看 • 11 个月前

Sam Altman just dropped the most important interview of 2025. And buried in it are four numbers that explain why everything you think about AI is wrong. Here's what he revealed: Number 1: AI companies are generating 10 TRILLION tokens per day. Humans? Average 20,000 tokens per day. Sam's exact words: "Models will output more tokens than all of humanity put together. Then 10x that. Then 100x that." We're not talking about AI assisting human work anymore. We're talking about AI replacing the entire volume of human intellectual output on the planet. And most people have no idea this shift already happened. Number 2: OpenAI's enterprise business is CRUSHING consumer. Everyone thinks OpenAI is ChatGPT for normies. Wrong. Sam just revealed: "Enterprise growth OUTPACED consumer growth this year." The API business is growing faster than ChatGPT. Over 1 million enterprise users already. "If we had double the compute, we'd be at double the revenue right now." Translation: OpenAI isn't compute-constrained by technology. They're revenue-constrained by infrastructure. The bottleneck is supply and not demand. Every dollar of compute they add prints money. Number 3: GPT-5.2 beats you at 74% of your job. Sam revealed OpenAI's internal GDP-Val benchmark. It measures how AI performs on knowledge work tasks across 40+ verticals. The results: GPT-5.2 beats or ties expert-level knowledge workers at 74.1% of tasks. Legal analysis. PowerPoint decks. Web apps. Financial modeling. Customer support. Sam's description: "A co-worker you can assign an hour's worth of tasks to and get something you prefer back 3 out of 4 times." Three years ago, ChatGPT launched at basically 0% on this scale. Now it's at 74%. And that's not GPT-6. That's what's available RIGHT NOW. Most companies haven't even started using this yet. But here's what Sam said about the gap between capability and adoption: "The overhang is going to be massive. Most people are still asking similar questions they did in the GPT-4 realm." Translation: The models can do 10x more than people have figured out how to use them for. Which means there's a HUGE arbitrage opportunity. Early adopters who actually integrate this into workflows will dominate their industries before competitors even understand what happened. Number 4: AGI already happened. And nobody noticed. Sam's exact quote: "AGI kind of went whooshing by. We're in this fuzzy period where some people think we have it and some don't." Read that again. The CEO of OpenAI just said AGI might have already arrived and we're arguing about definitions while it's actively replacing knowledge work. He even moved the goalposts. The new benchmark: "Superintelligence" = when AI can be a better president or CEO than any human. Not "as good as." BETTER than. We went from "can AI pass a Turing test" to "can AI run countries better than humans" in 3 years. So what does this actually mean? The AI revolution isn't about chatbots getting smarter. It's about the complete replacement of human intellectual output with machine output. At scale. Across every industry. Faster than anyone's prepared for. And the companies positioning for this RIGHT NOW are the ones printing money. OpenAI's enterprise growth is outpacing consumer because businesses see what's coming. They're not buying "AI tools." They're buying the ability to 10x output without 10x-ing headcount. Sam said they'll triple their compute next year. Then triple it again. Revenue is growing even faster than that. "We have never found a situation where we can't monetize all the compute we have." If he isn't lying then that's literally a printing press. The market still doesn't get it. Everyone's focused on "AI bubble" fears while OpenAI is solving the only problem that matters: turning compute into revenue at a faster rate than they're spending. They're not hoping demand catches up to supply. Demand is already 2x ahead of what they can deliver. Meanwhile, most knowledge workers are still using GPT-4 prompts on GPT-5.2. The capability overhang is massive. The arbitrage window is open. And it's closing fast. If you're running a B2B business and you're not integrating AI at the level Sam just described, you're not "waiting to see how it plays out." You're getting crushed by competitors who already figured it out. The companies that win in 2026 won't be the ones with the best AI. They'll be the ones who understood what Sam just laid out 6 months before everyone else did.
1:33

Sam Altman just dropped the most important interview of 2025. And buried in it are four numbers that explain why everything you think about AI is wrong. Here's what he revealed: Number 1: AI companies are generating 10 TRILLION tokens per day. Humans? Average 20,000 tokens per day. Sam's exact words: "Models will output more tokens than all of humanity put together. Then 10x that. Then 100x that." We're not talking about AI assisting human work anymore. We're talking about AI replacing the entire volume of human intellectual output on the planet. And most people have no idea this shift already happened. Number 2: OpenAI's enterprise business is CRUSHING consumer. Everyone thinks OpenAI is ChatGPT for normies. Wrong. Sam just revealed: "Enterprise growth OUTPACED consumer growth this year." The API business is growing faster than ChatGPT. Over 1 million enterprise users already. "If we had double the compute, we'd be at double the revenue right now." Translation: OpenAI isn't compute-constrained by technology. They're revenue-constrained by infrastructure. The bottleneck is supply and not demand. Every dollar of compute they add prints money. Number 3: GPT-5.2 beats you at 74% of your job. Sam revealed OpenAI's internal GDP-Val benchmark. It measures how AI performs on knowledge work tasks across 40+ verticals. The results: GPT-5.2 beats or ties expert-level knowledge workers at 74.1% of tasks. Legal analysis. PowerPoint decks. Web apps. Financial modeling. Customer support. Sam's description: "A co-worker you can assign an hour's worth of tasks to and get something you prefer back 3 out of 4 times." Three years ago, ChatGPT launched at basically 0% on this scale. Now it's at 74%. And that's not GPT-6. That's what's available RIGHT NOW. Most companies haven't even started using this yet. But here's what Sam said about the gap between capability and adoption: "The overhang is going to be massive. Most people are still asking similar questions they did in the GPT-4 realm." Translation: The models can do 10x more than people have figured out how to use them for. Which means there's a HUGE arbitrage opportunity. Early adopters who actually integrate this into workflows will dominate their industries before competitors even understand what happened. Number 4: AGI already happened. And nobody noticed. Sam's exact quote: "AGI kind of went whooshing by. We're in this fuzzy period where some people think we have it and some don't." Read that again. The CEO of OpenAI just said AGI might have already arrived and we're arguing about definitions while it's actively replacing knowledge work. He even moved the goalposts. The new benchmark: "Superintelligence" = when AI can be a better president or CEO than any human. Not "as good as." BETTER than. We went from "can AI pass a Turing test" to "can AI run countries better than humans" in 3 years. So what does this actually mean? The AI revolution isn't about chatbots getting smarter. It's about the complete replacement of human intellectual output with machine output. At scale. Across every industry. Faster than anyone's prepared for. And the companies positioning for this RIGHT NOW are the ones printing money. OpenAI's enterprise growth is outpacing consumer because businesses see what's coming. They're not buying "AI tools." They're buying the ability to 10x output without 10x-ing headcount. Sam said they'll triple their compute next year. Then triple it again. Revenue is growing even faster than that. "We have never found a situation where we can't monetize all the compute we have." If he isn't lying then that's literally a printing press. The market still doesn't get it. Everyone's focused on "AI bubble" fears while OpenAI is solving the only problem that matters: turning compute into revenue at a faster rate than they're spending. They're not hoping demand catches up to supply. Demand is already 2x ahead of what they can deliver. Meanwhile, most knowledge workers are still using GPT-4 prompts on GPT-5.2. The capability overhang is massive. The arbitrage window is open. And it's closing fast. If you're running a B2B business and you're not integrating AI at the level Sam just described, you're not "waiting to see how it plays out." You're getting crushed by competitors who already figured it out. The companies that win in 2026 won't be the ones with the best AI. They'll be the ones who understood what Sam just laid out 6 months before everyone else did.

Ricardo

358,836 次观看 • 9 个月前

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."
1:53

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."

Trade Whisperer

180,543 次观看 • 2 个月前

Jensen Huang, CEO of NVIDIA, laid out the compute math almost nobody priced in: reasoning AI needs 1,000x more compute than generative AI. Then you multiply by 100x more users. "In order for AI to go through understanding, reasoning, planning, using tools to take action, the amount of computation necessary compared to generative AI is like a thousand times more." "In two years time, the number of cars you need in the world grew by a thousand times. In two years time, the number of airplanes you need in the world grew by 2,000 times. Whatever metric you want to use, the thousand times difference is incredible." "But then you multiply that by the number of people who now want to use it by a hundred times. Which is the reason why GPU consumption is going through the roof." "Even GPUs we sold 4 or 5 years ago are now rising in price faster than good wine. It has defied what everybody said was going to happen." The reasoning era did not make intelligence cheaper to run. It made a single answer cost 1,000x more compute, then handed that answer to 100x more people. Anyone still budgeting AI around "inference gets cheap" is planning for a curve that already snapped.
0:58

Jensen Huang, CEO of NVIDIA, laid out the compute math almost nobody priced in: reasoning AI needs 1,000x more compute than generative AI. Then you multiply by 100x more users. "In order for AI to go through understanding, reasoning, planning, using tools to take action, the amount of computation necessary compared to generative AI is like a thousand times more." "In two years time, the number of cars you need in the world grew by a thousand times. In two years time, the number of airplanes you need in the world grew by 2,000 times. Whatever metric you want to use, the thousand times difference is incredible." "But then you multiply that by the number of people who now want to use it by a hundred times. Which is the reason why GPU consumption is going through the roof." "Even GPUs we sold 4 or 5 years ago are now rising in price faster than good wine. It has defied what everybody said was going to happen." The reasoning era did not make intelligence cheaper to run. It made a single answer cost 1,000x more compute, then handed that answer to 100x more people. Anyone still budgeting AI around "inference gets cheap" is planning for a curve that already snapped.

Karl Mehta

54,717 次观看 • 2 个月前

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.
0:23

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.

Milk Road AI

419,755 次观看 • 4 个月前