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Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models...

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Fireside Alpha

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162,832 次观看 • 28 天前 •via X (Twitter)

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Interesting that in three of my recent conversations with Krishna at Anthropic, Dylan Patel, and Gavin Baker, each said that frontier tokens are capturing the majority of the economic value. Gavin: "An overwhelming amount of the economic returns to AI at the model layer have been at the frontier. That's surprising to me, and I think it's been surprising to a lot of people. This is one of the most important questions to be answered, and you need to have a hypothesis on it as an investor." Krishna: "We think the returns to frontier intelligence are extremely high. Customers invest really heavily in more tokens with the newer models. The ones at the frontier clearly are capturing this economic value, driving meaningful ROI for customers. The returns to frontier intelligence are not slowing down." Dylan: "No one gives a crap about GPT-4 class models. They want the frontier because the frontier lets them create the economically valuable things."
2:08

Interesting that in three of my recent conversations with Krishna at Anthropic, Dylan Patel, and Gavin Baker, each said that frontier tokens are capturing the majority of the economic value. Gavin: "An overwhelming amount of the economic returns to AI at the model layer have been at the frontier. That's surprising to me, and I think it's been surprising to a lot of people. This is one of the most important questions to be answered, and you need to have a hypothesis on it as an investor." Krishna: "We think the returns to frontier intelligence are extremely high. Customers invest really heavily in more tokens with the newer models. The ones at the frontier clearly are capturing this economic value, driving meaningful ROI for customers. The returns to frontier intelligence are not slowing down." Dylan: "No one gives a crap about GPT-4 class models. They want the frontier because the frontier lets them create the economically valuable things."

Patrick OShaughnessy

121,110 次观看 • 2 个月前

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg
1:21

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Jawwwn

180,421 次观看 • 28 天前

Jensen says Open Source can be MORE expensive for enterprises, Brad Gerstner explains why: Brad Gerstner: “Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence, that they're much cheaper, etc. And Elon comes out and says, ‘Not so fast. We're entering the singularity, and the frontier models are way further ahead than people think.’ I believe that to be true. And then Jensen came out this week and said, ‘Closed models are actually cheaper if you don't have to build it for yourself, the training costs, and a lot of expertise to fine-tune, and maintain, and guardrail, and keep it safe. So he's basically making the argument that not only are the frontier models further ahead, but that the cost differential between the two is not what everybody's making it out to be, which I think explains why (closed models) continue to run away with it on the revenue side of the equation. For the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the frontier labs. I think that's what we want to see.” $NVDA
0:57

Jensen says Open Source can be MORE expensive for enterprises, Brad Gerstner explains why: Brad Gerstner: “Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence, that they're much cheaper, etc. And Elon comes out and says, ‘Not so fast. We're entering the singularity, and the frontier models are way further ahead than people think.’ I believe that to be true. And then Jensen came out this week and said, ‘Closed models are actually cheaper if you don't have to build it for yourself, the training costs, and a lot of expertise to fine-tune, and maintain, and guardrail, and keep it safe. So he's basically making the argument that not only are the frontier models further ahead, but that the cost differential between the two is not what everybody's making it out to be, which I think explains why (closed models) continue to run away with it on the revenue side of the equation. For the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the frontier labs. I think that's what we want to see.” $NVDA

The All-In Podcast

60,603 次观看 • 8 天前

Aligned with Matan Grinberg's intuition that in the next 12 months, 90% of tokens could be going to open models. We're seeing more and more companies using frontier APIs for experimenting and open-source or private models for production and larger workloads!
1:08

Aligned with Matan Grinberg's intuition that in the next 12 months, 90% of tokens could be going to open models. We're seeing more and more companies using frontier APIs for experimenting and open-source or private models for production and larger workloads!

clem 🤗

24,138 次观看 • 1 个月前

Gavin Baker says the Anthropic S-1 will break a lot of investors' brains "The Anthropic S-1 is going to be really important. And it's going to break a lot of people's brains. There are a lot of macro and value investors who are very confidently making these prognostications about AI with the assumption that tokens are subsidized." "Anthropic is generating cash. They're profitable. Open source tokens are profitable. OpenAI, if they're not generating cash, they will be imminently. SpaceX, same thing." "These macro and value investors are ignorant. They're very smart, but they're ignorant of the facts. They're making an assumption that tokens are subsidized and this is all going to collapse in some circular financing bonfire." "They're just wrong. The overwhelming majority of tokens are profitable for everyone in the chain. Everyone." "It's saying I'm very bearish on the world economy because oil is at $500 a barrel. If oil was at $500 a barrel, that'd be a good reason to be bearish. It's just not. They're just wrong. The central fact is wrong."
1:54

Gavin Baker says the Anthropic S-1 will break a lot of investors' brains "The Anthropic S-1 is going to be really important. And it's going to break a lot of people's brains. There are a lot of macro and value investors who are very confidently making these prognostications about AI with the assumption that tokens are subsidized." "Anthropic is generating cash. They're profitable. Open source tokens are profitable. OpenAI, if they're not generating cash, they will be imminently. SpaceX, same thing." "These macro and value investors are ignorant. They're very smart, but they're ignorant of the facts. They're making an assumption that tokens are subsidized and this is all going to collapse in some circular financing bonfire." "They're just wrong. The overwhelming majority of tokens are profitable for everyone in the chain. Everyone." "It's saying I'm very bearish on the world economy because oil is at $500 a barrel. If oil was at $500 a barrel, that'd be a good reason to be bearish. It's just not. They're just wrong. The central fact is wrong."

dnap

438,664 次观看 • 1 天前

$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."
0:35

$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."

Fireside Alpha

11,921 次观看 • 10 天前

CNBC described China’s open-source AI as “pushing the U.S. to compete at the lower end of the value chain,” initially trying to save face for Silicon Valley. The comments section immediately tore that framing apart: "Chinese models are approaching frontier-level capability while remaining absurdly cheap." "This is not the 'lower end' of the value chain." It is forcing expensive American models to answer a much uglier question: Why are you charging tens or even hundreds of times more for the same work? The most revealing part was that people saw through the euphemism immediately: “Lower end” is just cope. American labs are not protecting the high end. They are protecting high profit margins. China’s open-source models are turning frontier capability into a commodity, crushing prices, and freeing developers from brand worship. Suddenly, the American myth of closed-source superiority, premium pricing, and inflated valuations looks less like technological leadership— and more like an ordinary handbag with a luxury label.
1:53

CNBC described China’s open-source AI as “pushing the U.S. to compete at the lower end of the value chain,” initially trying to save face for Silicon Valley. The comments section immediately tore that framing apart: "Chinese models are approaching frontier-level capability while remaining absurdly cheap." "This is not the 'lower end' of the value chain." It is forcing expensive American models to answer a much uglier question: Why are you charging tens or even hundreds of times more for the same work? The most revealing part was that people saw through the euphemism immediately: “Lower end” is just cope. American labs are not protecting the high end. They are protecting high profit margins. China’s open-source models are turning frontier capability into a commodity, crushing prices, and freeing developers from brand worship. Suddenly, the American myth of closed-source superiority, premium pricing, and inflated valuations looks less like technological leadership— and more like an ordinary handbag with a luxury label.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

10,646 次观看 • 10 天前

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."
2:06

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

dnap

110,354 次观看 • 1 个月前

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”
0:41

Jason Calacanis: Anthropic, OpenAI and others are trying to kill OpenClaw Why? Because an open source agent platform is an existential threat to frontier model companies. @jason: “ People are going to say I'm a conspiracy theorist, but the number one goal, I believe, in the large language model, frontier model space, is to kill (OpenClaw). This is a giant movement to stop it, because this is the equivalent of having an open source Android-like player in the market, and that could be incredibly disruptive. Because, I believe, open source is going to win the day on the large language models and take 90% of the token usage, and I think the entire frontier model space could be undercut by open source. And I think they realize that SLMs, the smaller language models that are verticalized now, that will run on desktops and laptops and are even starting to run on the top ones, that is their biggest competitive threat, and I hope it happens.”

The All-In Podcast

64,611 次观看 • 4 个月前

Palantir is playing an integral role in the AI Revolution, and Akshay Krishnaswamy summarized it best⚡️ “Our conviction here at Palantir is that really it constitutes a new category in the AI stack...Of course there's raw energy. You then have chips, you have data centers, you have the frontier models that are increasingly commoditized and available but increasingly powerful as well. And then there's everything you need to get from that to differentiated outcomes, products, and services. And we are maniacally focused on providing this AI infrastructure for developer teams, for enterprises, for everybody looking to achieve value with AI.”
0:37

Palantir is playing an integral role in the AI Revolution, and Akshay Krishnaswamy summarized it best⚡️ “Our conviction here at Palantir is that really it constitutes a new category in the AI stack...Of course there's raw energy. You then have chips, you have data centers, you have the frontier models that are increasingly commoditized and available but increasingly powerful as well. And then there's everything you need to get from that to differentiated outcomes, products, and services. And we are maniacally focused on providing this AI infrastructure for developer teams, for enterprises, for everybody looking to achieve value with AI.”

Eliano A. Younes

11,513 次观看 • 1 年前

Factory (Factory) CEO Matan Grinberg (Matan Grinberg) says "In the next 12 months, 90% of tokens will be going to open models." Enterprises are already shifting rapidly.. "At the beginning of the year, <1% of their tokens were going to open models." "Around March, it crossed 1%... & in May it crossed 10%." "These open models are incredibly performant, incredibly cheap, incredibly fast." While frontier closed models aren't going away: "They'll still have a place, but I think that place will be shrinking—at least in token share." And by the end of 2026? "At least in the enterprise, we'll probably cross the 50% threshold."
2:40

Factory (Factory) CEO Matan Grinberg (Matan Grinberg) says "In the next 12 months, 90% of tokens will be going to open models." Enterprises are already shifting rapidly.. "At the beginning of the year, <1% of their tokens were going to open models." "Around March, it crossed 1%... & in May it crossed 10%." "These open models are incredibly performant, incredibly cheap, incredibly fast." While frontier closed models aren't going away: "They'll still have a place, but I think that place will be shrinking—at least in token share." And by the end of 2026? "At least in the enterprise, we'll probably cross the 50% threshold."

Molly O’Shea

120,949 次观看 • 1 个月前

Chamath: Frontier AI Leaders “Created a Total F*cking Mess” Short-sighted fearmongering and immaturity from frontier AI leaders has created deep mistrust, threatening AI’s potential as an open engine of economic mobility. That mistrust gives hyperscalers the chance to position themselves as trusted gatekeepers, using KYC, audit trails, and compliance infrastructure to turn AI into an oligopoly. Chamath Palihapitiya on the All-In Pod: “I think the leaders of the frontier labs leave a lot to be desired. I think what we're seeing is a consistent pattern of evasiveness and immaturity, and I think that does a huge disservice to the entire movement of AI. The key to a vibrant life is rooted in economic mobility, and I think AI is the grand leveler. It is the thing that can enable everyone to have unique amounts of economic mobility because they are unencumbered to figure out what their upper bound is. And against that backdrop, we have to live in this constant doomerism, hype cycle, naivety, and I think it holds us back. How does it hold us back? Tactically, number one, it creates mistrust. I think that Silicon Valley was already decaying in the prestige that it held in American society. We built important things. Then we veered away from that, and we started building less important things. And now we're at a point where we've potentially started to rebuild important things again, but we have this veneer of negativity and mistrust that are created in large part because we just cannot get our sh*t together. And the leaders of the frontier labs are public enemy number one. Number two, I think what it creates, which I think is bad, but what it creates is an incredible opportunity for the hyperscalers. And the very simple opportunity is to convince governments all around the world, not just America, that they should be the gatekeeper. A: You can't trust these guys. B: These models are all over the place. C: Let us be the ones that provision them to the world. We will wrap it in KYC. I've been now talking about KYC for a while, right? Who are these customers? Do they have identification? Why are they allowed to run these models? What are they prompting? Let's keep them so that there's an audit trail. All of these things are going to become issues. The Frontier Lab folks made it an issue because of how they've handled all of this up until now. And what does that create? Now that creates an oligopoly for AI, the most powerful economically leveling instrument we've ever seen in the hands of maybe a handful of hyperscalers, who by the way, would make an incredibly compelling argument, and they would be right. And the only counterfactual to it would be, ‘Well, trust us, guys, it should actually be much more open and in a far more distributed environment.’ Can you imagine the cost and the complexity if you ask the neoscaler to build the same robust KYC or the same VPC infrastructure that Amazon and Microsoft and Google have spent decades investing trillions of dollars in? It's an impossibility, Jason. So you can take all of those datacenters off the map. You can take all of the neoscaler market off the map. All of this was preventable. So instead of a diverse, robust, open ecosystem giving a tool that is the fundamental unlock for humans, we are now going to debate gatekeeping and duopoly versus oligopoly. They have created a total f*cking mess, and it's a shame.”
3:26

Chamath: Frontier AI Leaders “Created a Total F*cking Mess” Short-sighted fearmongering and immaturity from frontier AI leaders has created deep mistrust, threatening AI’s potential as an open engine of economic mobility. That mistrust gives hyperscalers the chance to position themselves as trusted gatekeepers, using KYC, audit trails, and compliance infrastructure to turn AI into an oligopoly. Chamath Palihapitiya on the All-In Pod: “I think the leaders of the frontier labs leave a lot to be desired. I think what we're seeing is a consistent pattern of evasiveness and immaturity, and I think that does a huge disservice to the entire movement of AI. The key to a vibrant life is rooted in economic mobility, and I think AI is the grand leveler. It is the thing that can enable everyone to have unique amounts of economic mobility because they are unencumbered to figure out what their upper bound is. And against that backdrop, we have to live in this constant doomerism, hype cycle, naivety, and I think it holds us back. How does it hold us back? Tactically, number one, it creates mistrust. I think that Silicon Valley was already decaying in the prestige that it held in American society. We built important things. Then we veered away from that, and we started building less important things. And now we're at a point where we've potentially started to rebuild important things again, but we have this veneer of negativity and mistrust that are created in large part because we just cannot get our sh*t together. And the leaders of the frontier labs are public enemy number one. Number two, I think what it creates, which I think is bad, but what it creates is an incredible opportunity for the hyperscalers. And the very simple opportunity is to convince governments all around the world, not just America, that they should be the gatekeeper. A: You can't trust these guys. B: These models are all over the place. C: Let us be the ones that provision them to the world. We will wrap it in KYC. I've been now talking about KYC for a while, right? Who are these customers? Do they have identification? Why are they allowed to run these models? What are they prompting? Let's keep them so that there's an audit trail. All of these things are going to become issues. The Frontier Lab folks made it an issue because of how they've handled all of this up until now. And what does that create? Now that creates an oligopoly for AI, the most powerful economically leveling instrument we've ever seen in the hands of maybe a handful of hyperscalers, who by the way, would make an incredibly compelling argument, and they would be right. And the only counterfactual to it would be, ‘Well, trust us, guys, it should actually be much more open and in a far more distributed environment.’ Can you imagine the cost and the complexity if you ask the neoscaler to build the same robust KYC or the same VPC infrastructure that Amazon and Microsoft and Google have spent decades investing trillions of dollars in? It's an impossibility, Jason. So you can take all of those datacenters off the map. You can take all of the neoscaler market off the map. All of this was preventable. So instead of a diverse, robust, open ecosystem giving a tool that is the fundamental unlock for humans, we are now going to debate gatekeeping and duopoly versus oligopoly. They have created a total f*cking mess, and it's a shame.”

The All-In Podcast

141,660 次观看 • 1 个月前

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇
2:00

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇

MosesMee

14,108 次观看 • 1 年前

SemiAnalysis Dylan Patel: “If you don’t use more tokens, you’ll never escape the permanent underclass. Either you use more tokens and generate outsized economic value from them… a lot of people are doing it the boring lazy way — ‘I guess I’ll just work one hour a day instead of eight and have AI do most of my job.’ That’s the boring way. The cool way is: I’ll still work eight hours a day, I’ll do 8x the work, and maybe I’ll make 5x the money… There’s three problems: using more tokens, generating value from those tokens, and capturing that value. If you don’t do these three things, you’ll never escape the permanent underclass.”
1:12

SemiAnalysis Dylan Patel: “If you don’t use more tokens, you’ll never escape the permanent underclass. Either you use more tokens and generate outsized economic value from them… a lot of people are doing it the boring lazy way — ‘I guess I’ll just work one hour a day instead of eight and have AI do most of my job.’ That’s the boring way. The cool way is: I’ll still work eight hours a day, I’ll do 8x the work, and maybe I’ll make 5x the money… There’s three problems: using more tokens, generating value from those tokens, and capturing that value. If you don’t do these three things, you’ll never escape the permanent underclass.”

Wall St Engine

71,377 次观看 • 3 个月前

🇺🇸 Tucker: "There's no conversations about the benefits of AI..." Tucker argues that the exploding AI boom will trigger massive investments in power generation, infrastructure, and economic development, with only the negative effects to humanity being discussed. "You're telling me I can't have electricity of water because the machines need it? What is going on?" As demand for AI continues to surge, it could become one of the biggest infrastructure and economic shifts in decades. Source: TCN, / Writer: Val
1:44

🇺🇸 Tucker: "There's no conversations about the benefits of AI..." Tucker argues that the exploding AI boom will trigger massive investments in power generation, infrastructure, and economic development, with only the negative effects to humanity being discussed. "You're telling me I can't have electricity of water because the machines need it? What is going on?" As demand for AI continues to surge, it could become one of the biggest infrastructure and economic shifts in decades. Source: TCN, / Writer: Val

Mario Nawfal

51,954 次观看 • 1 个月前

Ex-DeepMind Researcher, Misha Laskin: The real battle isn't open source vs. closed, it's who controls AI infrastructure Sovereigns and enterprises are spending trillions building "AI factories", massive GPU data centers that produce tokens "but to produce tokens, you need a powerful model, the brain of the operation"
1:20

Ex-DeepMind Researcher, Misha Laskin: The real battle isn't open source vs. closed, it's who controls AI infrastructure Sovereigns and enterprises are spending trillions building "AI factories", massive GPU data centers that produce tokens "but to produce tokens, you need a powerful model, the brain of the operation"

Haider.

31,121 次观看 • 7 个月前

The German Federal Innovation Agency is running a €125m competition to fund 3 new Frontier AI labs in Europe! "Next Frontier AI" is a pan-European initiative led by SPRIND, Federal Agency for Breakthrough Innovation to create three globally relevant Frontier AI labs. It starts with a €125m challenge where up to 10 teams receive funding over 24 months to build frontier-lab capabilities, including team, infrastructure, prototypes, evaluation discipline, and early pilots. The best-performing teams will then receive structured support toward raising ~€1 billion each. Europe has some of the top AI companies in the world, but as a continent we are massively dependent on frontier labs from other countries. This initiative seeks to change that and I am HERE FOR IT.
1:30

The German Federal Innovation Agency is running a €125m competition to fund 3 new Frontier AI labs in Europe! "Next Frontier AI" is a pan-European initiative led by SPRIND, Federal Agency for Breakthrough Innovation to create three globally relevant Frontier AI labs. It starts with a €125m challenge where up to 10 teams receive funding over 24 months to build frontier-lab capabilities, including team, infrastructure, prototypes, evaluation discipline, and early pilots. The best-performing teams will then receive structured support toward raising ~€1 billion each. Europe has some of the top AI companies in the world, but as a continent we are massively dependent on frontier labs from other countries. This initiative seeks to change that and I am HERE FOR IT.

Seb Johnson

24,124 次观看 • 4 个月前

🇺🇸 Bret Johnsen says Starship, Starlink, and massive data centers are becoming the backbone of the next technological era. As AI's demand for computing power explodes, SpaceX is building the infrastructure to connect, power, and scale it globally. The race for AI dominance may not be won by software alone… but it could depend on who controls the infrastructure of Earth and space. Source: SpaceX, Gavin Baker, Elon Musk / Writer: Val
2:58

🇺🇸 Bret Johnsen says Starship, Starlink, and massive data centers are becoming the backbone of the next technological era. As AI's demand for computing power explodes, SpaceX is building the infrastructure to connect, power, and scale it globally. The race for AI dominance may not be won by software alone… but it could depend on who controls the infrastructure of Earth and space. Source: SpaceX, Gavin Baker, Elon Musk / Writer: Val

Mario Nawfal

29,950 次观看 • 2 个月前

Brad Gerstner: Companies Will Pay 5x More for the Best AI, No Evidence of Pricing Pressure from Open Source Brad Gerstner: “Jason, you talked about summarizing a document, it may take 20,000 cheap tokens to do. Of course, shoot that to a lagging model or an open source model. But if you're talking about replacing a software engineer for two hours, that may take two million expensive tokens, and the consequence of using something that's 95% as good is really high. Because you have a long-running task, and if the task breaks early, or it breaks in the middle, or it breaks at the end, there's a huge cost to that.” @jason: “You still burn the tokens, right? And back to this analogy I was using, you're pulling the slot machine, and you lose.” Brad: “And (you lose) the time and the compute. So if an AI agent is replacing a $200 an hour consultant, right? Take that as an example. So three consulting firms, they're competing. They need the smartest consultant. They're charging $200 an hour. The difference between spending $3 on a cheap model or $15 on an expensive model to replace a $200/hour consultant, it's just irrelevant. That inference cost difference is irrelevant if you're getting something that's bulletproof for $15, and so I think that's what we're seeing play out. The best evidence for all of this is just revenue growth. I'm talking about, what is Anthropic's revenue growth compared to OpenAI, compared to the open source models? Millions of independent actors are choosing every single day. The open source companies are growing, right? But they're growing selling something that is really, really cheap. And there's room in every single market for premium products, for mid-tier products, and for commodity products, and I think we see a lot of this token growth, people are speculating that the intelligence gap between that commodity stuff and the frontier stuff is going to collapse to the point that people won't pay for the frontier stuff. There is no evidence of that on the field today.”
1:50

Brad Gerstner: Companies Will Pay 5x More for the Best AI, No Evidence of Pricing Pressure from Open Source Brad Gerstner: “Jason, you talked about summarizing a document, it may take 20,000 cheap tokens to do. Of course, shoot that to a lagging model or an open source model. But if you're talking about replacing a software engineer for two hours, that may take two million expensive tokens, and the consequence of using something that's 95% as good is really high. Because you have a long-running task, and if the task breaks early, or it breaks in the middle, or it breaks at the end, there's a huge cost to that.” @jason: “You still burn the tokens, right? And back to this analogy I was using, you're pulling the slot machine, and you lose.” Brad: “And (you lose) the time and the compute. So if an AI agent is replacing a $200 an hour consultant, right? Take that as an example. So three consulting firms, they're competing. They need the smartest consultant. They're charging $200 an hour. The difference between spending $3 on a cheap model or $15 on an expensive model to replace a $200/hour consultant, it's just irrelevant. That inference cost difference is irrelevant if you're getting something that's bulletproof for $15, and so I think that's what we're seeing play out. The best evidence for all of this is just revenue growth. I'm talking about, what is Anthropic's revenue growth compared to OpenAI, compared to the open source models? Millions of independent actors are choosing every single day. The open source companies are growing, right? But they're growing selling something that is really, really cheap. And there's room in every single market for premium products, for mid-tier products, and for commodity products, and I think we see a lot of this token growth, people are speculating that the intelligence gap between that commodity stuff and the frontier stuff is going to collapse to the point that people won't pay for the frontier stuff. There is no evidence of that on the field today.”

The All-In Podcast

52,289 次观看 • 1 个月前

Palantir CEO Alex Karp on what customers actually want, the real business of frontier labs, and the importance of open source models: “What the technical customers want is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it's not being transferred to someone else.” "Who owns the data? Are the prompts secure? Is this being transferred to you?" "If it was so valuable, and I can make you a billion dollars, wouldn't I say I'll make you a billion dollars and I want 30%? Why are they charging for tokens if it's so valuable?"
2:49

Palantir CEO Alex Karp on what customers actually want, the real business of frontier labs, and the importance of open source models: “What the technical customers want is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it's not being transferred to someone else.” "Who owns the data? Are the prompts secure? Is this being transferred to you?" "If it was so valuable, and I can make you a billion dollars, wouldn't I say I'll make you a billion dollars and I want 30%? Why are they charging for tokens if it's so valuable?"

Palantir

4,504,829 次观看 • 1 个月前