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One year ago, Gavin Baker was managing a large AI position. Today he is medium-small. This is not a change in thesis. Baker and Brad Gerstner both remain long SpaceX and AI infrastructure. The trimming is about price, not conviction. CPI at 4.2%. Iran war. Oil at $100. Semis... show more

Podcast Alpha

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Gavin Baker built a massive position in $ALAB around the AI infrastructure theme, and the stock has now crossed $300. He thinks AI is different and that we are NOT in a bubble. He expresses this thesis behind many of his top holdings, including $NVDA, $MU, and $AMZN.

Gavin Baker built a massive position in $ALAB around the AI infrastructure theme, and the stock has now crossed $300. He thinks AI is different and that we are NOT in a bubble. He expresses this thesis behind many of his top holdings, including $NVDA, $MU, and $AMZN.

Sam Badawi

450,333 görüntüleme • 3 ay önce

Gavin Baker just spotted a massive contradiction inside the AI market. The valuations across the AI supply chain don't add up when you hold them side by side. - Memory names: trading at 3-5x PE. - Nvidia: trading at a very low PE. - Some accelerator companies: reasonable multiples. - Power and cooling names: discounting a much higher future. These multiples can't all be right at the same time. If power and cooling names are priced correctly, then Nvidia and memory are way too cheap. They're going up a lot from here. If Nvidia and memory are priced correctly, then power and cooling will significantly underperform from here. One side is wrong. Both can't be true. Baker's word for it: the AI market is "cross-sectionally inefficient" right now. For investors, the question isn't just "am I bullish on AI?" The real question is: which part of the stack is priced correctly and which part is priced for a scenario that isn't going to play out? Note: Baker runs Atreides Management, one of the most respected tech-focused growth funds in the world. He doesn't make calls like this lightly. When the best investors in tech spot a cross-sectional mismatch this size, the trade is figuring out which side wins. Our analysts are already positioning inside the AI supply chain. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Follow their exact portfolios for $1 at Milk Road PRO, link in bio.

Gavin Baker just spotted a massive contradiction inside the AI market. The valuations across the AI supply chain don't add up when you hold them side by side. - Memory names: trading at 3-5x PE. - Nvidia: trading at a very low PE. - Some accelerator companies: reasonable multiples. - Power and cooling names: discounting a much higher future. These multiples can't all be right at the same time. If power and cooling names are priced correctly, then Nvidia and memory are way too cheap. They're going up a lot from here. If Nvidia and memory are priced correctly, then power and cooling will significantly underperform from here. One side is wrong. Both can't be true. Baker's word for it: the AI market is "cross-sectionally inefficient" right now. For investors, the question isn't just "am I bullish on AI?" The real question is: which part of the stack is priced correctly and which part is priced for a scenario that isn't going to play out? Note: Baker runs Atreides Management, one of the most respected tech-focused growth funds in the world. He doesn't make calls like this lightly. When the best investors in tech spot a cross-sectional mismatch this size, the trade is figuring out which side wins. Our analysts are already positioning inside the AI supply chain. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Follow their exact portfolios for $1 at Milk Road PRO, link in bio.

Milk Road Macro

162,479 görüntüleme • 3 ay önce

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 are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

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 are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Fireside Alpha

162,832 görüntüleme • 1 ay önce

Tom Lee says semis and AI infrastructure stocks are going to rip higher later this year. “Semis and infrastructure companies are at the center of one of the most important strategic initiatives for the US, which is AI and AI infrastructure, and that runway has years ahead. The last couple of weeks have been a rough ride. I think those names are going to bounce later this year. I don’t think the trade is over. It’s just taking a beating.” We don’t know who will ultimately build the best AI model. But we do know which companies are building the infrastructure that will make the AI revolution possible. That’s why I’m buying $CRWV, $ORCL, and $IREN.

Tom Lee says semis and AI infrastructure stocks are going to rip higher later this year. “Semis and infrastructure companies are at the center of one of the most important strategic initiatives for the US, which is AI and AI infrastructure, and that runway has years ahead. The last couple of weeks have been a rough ride. I think those names are going to bounce later this year. I don’t think the trade is over. It’s just taking a beating.” We don’t know who will ultimately build the best AI model. But we do know which companies are building the infrastructure that will make the AI revolution possible. That’s why I’m buying $CRWV, $ORCL, and $IREN.

Daniel

110,219 görüntüleme • 1 ay önce

AI Bull vs Bear #1: 60-70% gross margins on AI inference. Gavin Baker Gavin Baker of Atreides ran the math on BG2 Pod: inference revenue exits 2026 above $200B, and he calls $300B a low estimate for 2027. Ed Zitron's Ed Zitron bear case says costs scale with revenue, so the curve never bends. Baker's number says the unit economics already work at the inference layer. The catch: that is gross margin, not the whole P&L. It does not answer OpenAI's $21B operating loss. Where the bull margin math meets Zitron's receipts:

AI Bull vs Bear #1: 60-70% gross margins on AI inference. Gavin Baker Gavin Baker of Atreides ran the math on BG2 Pod: inference revenue exits 2026 above $200B, and he calls $300B a low estimate for 2027. Ed Zitron's Ed Zitron bear case says costs scale with revenue, so the curve never bends. Baker's number says the unit economics already work at the inference layer. The catch: that is gross margin, not the whole P&L. It does not answer OpenAI's $21B operating loss. Where the bull margin math meets Zitron's receipts:

Podcast Alpha

15,261 görüntüleme • 2 ay önce

Gavin Baker: "Anthropic is roughly four times more capital efficient than OpenAI - they're growing really fast and they're not burning that much cash" this is him explaining why he thinks token efficiency decides who wins, why xAI has the lowest cost per token of anyone, and what a Tesla board member says is actually the most advanced AI in the world right now "an Anthropic model can give you a comparable quality answer to a Google model using half as many tokens - and each token is literally cost" "xAI has the lowest cost per token because they build data centers faster and at a lower cost than everyone, and they run GPUs at a higher utilization" Tesla board member Antonio Gracias: "Tesla actually is today the most advanced AI in the world - it does the most complex thing a human does, drive a car" bookmark & watch the full conversation ↓

Gavin Baker: "Anthropic is roughly four times more capital efficient than OpenAI - they're growing really fast and they're not burning that much cash" this is him explaining why he thinks token efficiency decides who wins, why xAI has the lowest cost per token of anyone, and what a Tesla board member says is actually the most advanced AI in the world right now "an Anthropic model can give you a comparable quality answer to a Google model using half as many tokens - and each token is literally cost" "xAI has the lowest cost per token because they build data centers faster and at a lower cost than everyone, and they run GPUs at a higher utilization" Tesla board member Antonio Gracias: "Tesla actually is today the most advanced AI in the world - it does the most complex thing a human does, drive a car" bookmark & watch the full conversation ↓

Сarm1ne

128,347 görüntüleme • 1 ay önce

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George

a16z

92,161 görüntüleme • 10 ay önce

LIQUIDITY: Inside the Private Stock Market Boom Brad Gerstner (Brad Gerstner), Gavin Baker (Gavin Baker), and Kelly Rodriques (Forge) join @jason and Chamath Palihapitiya to discuss the secondary market gold rush. (0:00) Brad Gerstner, Gavin Baker, and Kelly Rodriques join the Besties! (0:47) Secondary Markets are Booming & Competing with IPOs (3:10) Why Companies are Staying Private So Long? (9:22) SPVs, the Forge-Schwab Deal, Democratizing Private Market Access (13:28) Secondary Markets as Exit Liquidity (27:00) The Private Market Bubble? (32:03) Hottest Secondary Companies Right Now Thanks to our partners for making this possible! EY (EY) - Agentic AI is introducing a new investment discipline. As AI shifts to consumption-based models, EY connects spend to enterprise value. NYSE (NYSE 🏛) - Thank you to our partner, the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE. Plaud (Plaud) - Never miss a moment. Plaud, our official wearable AI note-taking partner at All-In Liquidity Summit, captured every insight.

LIQUIDITY: Inside the Private Stock Market Boom Brad Gerstner (Brad Gerstner), Gavin Baker (Gavin Baker), and Kelly Rodriques (Forge) join @jason and Chamath Palihapitiya to discuss the secondary market gold rush. (0:00) Brad Gerstner, Gavin Baker, and Kelly Rodriques join the Besties! (0:47) Secondary Markets are Booming & Competing with IPOs (3:10) Why Companies are Staying Private So Long? (9:22) SPVs, the Forge-Schwab Deal, Democratizing Private Market Access (13:28) Secondary Markets as Exit Liquidity (27:00) The Private Market Bubble? (32:03) Hottest Secondary Companies Right Now Thanks to our partners for making this possible! EY (EY) - Agentic AI is introducing a new investment discipline. As AI shifts to consumption-based models, EY connects spend to enterprise value. NYSE (NYSE 🏛) - Thank you to our partner, the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE. Plaud (Plaud) - Never miss a moment. Plaud, our official wearable AI note-taking partner at All-In Liquidity Summit, captured every insight.

The All-In Podcast

128,699 görüntüleme • 2 ay önce

Nvidia $NVDA CEO Jensen Huang was asked about a recent story that said he warned that China will beat the US in the AI race “That’s not what I said. What I said was China has very good AI technology. They have many AI researchers, in fact 50% of the world’s AI researchers are in China. And they develop very good AI technology. In fact, the most popular AI models in the world today, open-source models, are from China. So, they are moving very, very fast. The United States has to continue to move incredibly fast. And otherwise, otherwise – the world is very competitive, so we have to run fast.” (H/T Dan Nystedt)

Nvidia $NVDA CEO Jensen Huang was asked about a recent story that said he warned that China will beat the US in the AI race “That’s not what I said. What I said was China has very good AI technology. They have many AI researchers, in fact 50% of the world’s AI researchers are in China. And they develop very good AI technology. In fact, the most popular AI models in the world today, open-source models, are from China. So, they are moving very, very fast. The United States has to continue to move incredibly fast. And otherwise, otherwise – the world is very competitive, so we have to run fast.” (H/T Dan Nystedt)

Evan

1,946,920 görüntüleme • 9 ay önce

Gavin Baker Gavin Baker: the Anthropic S1 is going to break a lot of people's brains. The entire AI bear case rests on one assumption, that tokens are sold below cost. What the filing settles, and who has to cover: Baker says that assumption is wrong. Open-source tokens are profitable. Anthropic is profitable and generating cash. OpenAI is close. Most tokens in the chain make money today. The S1 is the first audited document that settles it either way. Jim Chanos James Chanos has spent the year on the other side, calling the AI buildout a circular financing story. Plain version for a position holder: a lot of macro and value money is bearish on AI because it believes tokens are subsidized. If the filing shows real margins, that money covers into a re-rating and $NVDA, $TSM, $MU and the hyperscalers all move on it. If the filing shows subsidized tokens, every valuation downstream of it is sitting on sand. One document, one binary, a date on the calendar. David Sacks David Sacks and Jason Calacanis @jason worked him over on it for a full segment. Source: All-In Podcast -

Gavin Baker Gavin Baker: the Anthropic S1 is going to break a lot of people's brains. The entire AI bear case rests on one assumption, that tokens are sold below cost. What the filing settles, and who has to cover: Baker says that assumption is wrong. Open-source tokens are profitable. Anthropic is profitable and generating cash. OpenAI is close. Most tokens in the chain make money today. The S1 is the first audited document that settles it either way. Jim Chanos James Chanos has spent the year on the other side, calling the AI buildout a circular financing story. Plain version for a position holder: a lot of macro and value money is bearish on AI because it believes tokens are subsidized. If the filing shows real margins, that money covers into a re-rating and $NVDA, $TSM, $MU and the hyperscalers all move on it. If the filing shows subsidized tokens, every valuation downstream of it is sitting on sand. One document, one binary, a date on the calendar. David Sacks David Sacks and Jason Calacanis @jason worked him over on it for a full segment. Source: All-In Podcast -

Podcast Alpha

29,416 görüntüleme • 14 gün önce

Bottleneck trade: buy whatever AI can't get enough of. That trade is ending. Gavin Baker Gavin Baker of Atreides Management told Jordi Hays on TBPN: the tell was Ajinomoto - maker of ABF substrate, critical for semiconductor packaging - declining to raise prices at peak demand. Constrained suppliers who don't extract rent are signaling the squeeze is over. The next game is harder: finding companies with enduring franchise value once supply normalizes. That's a different analysis than "find the constraint and buy the input." Baker's framework for the post-bottleneck era, and where SpaceX sits in it: Source: TBPN -

Bottleneck trade: buy whatever AI can't get enough of. That trade is ending. Gavin Baker Gavin Baker of Atreides Management told Jordi Hays on TBPN: the tell was Ajinomoto - maker of ABF substrate, critical for semiconductor packaging - declining to raise prices at peak demand. Constrained suppliers who don't extract rent are signaling the squeeze is over. The next game is harder: finding companies with enduring franchise value once supply normalizes. That's a different analysis than "find the constraint and buy the input." Baker's framework for the post-bottleneck era, and where SpaceX sits in it: Source: TBPN -

Podcast Alpha

16,343 görüntüleme • 2 ay önce

Why is OpenAI cutting codex pricing right now? Gavin Baker Gavin Baker of Atreides Management thinks every major player knows the answer - and is acting on it privately. Baker told John Coogan on TBPN: OpenAI's codex price cuts are not a margin decision. They're a strategic move to stay in the recursive self-improvement loop - the cycle where AI improves its own code. Companies that lose coding token share now may find themselves outside that loop when it matters most. Baker's read on $META: Zuckerberg has no articulated product anchor for "personal superintelligence." But the mechanism that forced his hand in 2022 - the stock - is likely to activate again. What the end game looks like and who survives it: Source: TBPN -

Why is OpenAI cutting codex pricing right now? Gavin Baker Gavin Baker of Atreides Management thinks every major player knows the answer - and is acting on it privately. Baker told John Coogan on TBPN: OpenAI's codex price cuts are not a margin decision. They're a strategic move to stay in the recursive self-improvement loop - the cycle where AI improves its own code. Companies that lose coding token share now may find themselves outside that loop when it matters most. Baker's read on $META: Zuckerberg has no articulated product anchor for "personal superintelligence." But the mechanism that forced his hand in 2022 - the stock - is likely to activate again. What the end game looks like and who survives it: Source: TBPN -

Podcast Alpha

41,051 görüntüleme • 2 ay önce

⚡ Gavin Baker on why Elon's data center strategy is printing money — and Brad Gerstner on why nobody saw it coming: "If you can borrow money at 6, 7, 8% and invest in something with a 55% ARR, I'm not the most sophisticated thinker, but that math maths... We do know from Jensen that Elon Musk brings data centers up faster than anyone, 122 days. Speed is literally cost." "This whole category of taking all of this compute, which he's uniquely good at standing up, and then reselling it in a way that's highly profitable was not in a lot of people's forecasts — now it's a major component of the forecast." — Gavin Baker & Brad Gerstner on Bg2 Pod / BGGB Pod As Jensen Huang said, “Elon is an N of 1.”

⚡ Gavin Baker on why Elon's data center strategy is printing money — and Brad Gerstner on why nobody saw it coming: "If you can borrow money at 6, 7, 8% and invest in something with a 55% ARR, I'm not the most sophisticated thinker, but that math maths... We do know from Jensen that Elon Musk brings data centers up faster than anyone, 122 days. Speed is literally cost." "This whole category of taking all of this compute, which he's uniquely good at standing up, and then reselling it in a way that's highly profitable was not in a lot of people's forecasts — now it's a major component of the forecast." — Gavin Baker & Brad Gerstner on Bg2 Pod / BGGB Pod As Jensen Huang said, “Elon is an N of 1.”

bg2clips

15,672 görüntüleme • 2 ay önce

🚨Gavin Baker: Apple's ineptitude in AI is shocking, "it almost feels like they're trying to lose." @jason: “Apple has bought back, let this sink in, $700B worth of shares over the past decade.” Gavin Baker: “Maybe they should have spent $200B less and used that for data centers to be a real competitor in AI." "And I just continue to be baffled, you know, they’re comfortable being late to markets, the iPhone was not the first smartphone.” “But I’m shocked at their inaction and ineptitude in AI and how bad the products are from a user perspective. They’re terrible." Jason: "Siri is worse. How is that possible?” Gavin: “Incompetence is indistinguishable from malice, but it almost feels like they’re trying to lose."

🚨Gavin Baker: Apple's ineptitude in AI is shocking, "it almost feels like they're trying to lose." @jason: “Apple has bought back, let this sink in, $700B worth of shares over the past decade.” Gavin Baker: “Maybe they should have spent $200B less and used that for data centers to be a real competitor in AI." "And I just continue to be baffled, you know, they’re comfortable being late to markets, the iPhone was not the first smartphone.” “But I’m shocked at their inaction and ineptitude in AI and how bad the products are from a user perspective. They’re terrible." Jason: "Siri is worse. How is that possible?” Gavin: “Incompetence is indistinguishable from malice, but it almost feels like they’re trying to lose."

The All-In Podcast

224,567 görüntüleme • 1 yıl önce

Gavin Baker just posed the trillion dollar question, who's actually going to pay for all this AI spending? Baker frames the whole AI capex debate around one question, since even if hyperscalers are under earning today and compute pricing normalizes, someone has to pay for that recovered cash flow and that money comes from only two places, faster economic growth or labor substitution. The scale of the number itself is what makes the debate matter. There's roughly $25 trillion in global knowledge work spending and even a conservative 20% token spend ratio against that total comp base implies $5 trillion in potential AI spend, an amount that has to be funded by either productivity gains or replaced headcount. Real company data shows token spend already climbing toward that range. Ramp's own economist reported AI adoption crossing 50% of US businesses by March 2026, up from 35% a year earlier, and average monthly AI token spend across Ramp's customer base has grown 13 times since January 2025. Among the most aggressive adopters, that spend is becoming a serious share of total labor cost rather than a rounding error. SemiAnalysis reportedly runs AI token spend at 30% of total compensation spend and some companies have pushed that ratio as high as 50%, putting them well ahead of the 20-25% range typical even among heavily AI-pilled firms. The labor substitution side of Gavin Baker framework is already visible in company financials. Gross profit dollars per full-time employee at AI native companies tracked by a16z and Carta are running meaningfully higher than prior startup generations, showing these companies are staying lean rather than scaling headcount alongside revenue. Founder led companies are sending a different signal than the substitution story alone would suggest. Rather than replacing existing staff, most founder controlled companies aren't running large-scale layoffs even as they adopt AI heavily, which points toward AI spend layering on top of existing headcount to chase new growth rather than simply cutting costs. That distinction matters because it's exactly the bull case Baker is describing. Ramp's Spring 2026 report found companies investing the most in AI more than doubled their revenue since ChatGPT launched, while companies with zero AI spend grew only 15% and Ramp separately found heavy AI spenders growing revenue roughly twice as fast as low spend peers. Put together, the evidence leans toward growth rather than pure substitution funding this spend.

Gavin Baker just posed the trillion dollar question, who's actually going to pay for all this AI spending? Baker frames the whole AI capex debate around one question, since even if hyperscalers are under earning today and compute pricing normalizes, someone has to pay for that recovered cash flow and that money comes from only two places, faster economic growth or labor substitution. The scale of the number itself is what makes the debate matter. There's roughly $25 trillion in global knowledge work spending and even a conservative 20% token spend ratio against that total comp base implies $5 trillion in potential AI spend, an amount that has to be funded by either productivity gains or replaced headcount. Real company data shows token spend already climbing toward that range. Ramp's own economist reported AI adoption crossing 50% of US businesses by March 2026, up from 35% a year earlier, and average monthly AI token spend across Ramp's customer base has grown 13 times since January 2025. Among the most aggressive adopters, that spend is becoming a serious share of total labor cost rather than a rounding error. SemiAnalysis reportedly runs AI token spend at 30% of total compensation spend and some companies have pushed that ratio as high as 50%, putting them well ahead of the 20-25% range typical even among heavily AI-pilled firms. The labor substitution side of Gavin Baker framework is already visible in company financials. Gross profit dollars per full-time employee at AI native companies tracked by a16z and Carta are running meaningfully higher than prior startup generations, showing these companies are staying lean rather than scaling headcount alongside revenue. Founder led companies are sending a different signal than the substitution story alone would suggest. Rather than replacing existing staff, most founder controlled companies aren't running large-scale layoffs even as they adopt AI heavily, which points toward AI spend layering on top of existing headcount to chase new growth rather than simply cutting costs. That distinction matters because it's exactly the bull case Baker is describing. Ramp's Spring 2026 report found companies investing the most in AI more than doubled their revenue since ChatGPT launched, while companies with zero AI spend grew only 15% and Ramp separately found heavy AI spenders growing revenue roughly twice as fast as low spend peers. Put together, the evidence leans toward growth rather than pure substitution funding this spend.

Milk Road AI

30,966 görüntüleme • 22 gün önce

Jensen Huang looked at both scoreboards and picked one word for China. Might. Not growth. Not progress. Might. The word for power before it tells you what it wants. Huang: “50% of the world’s AI researchers are Chinese. 70% of last year’s AI patents are published by China.” Half the researchers. Most of the patents. One flag. Huang: “The ecosystem of AI in China is vibrant, rich, incredibly innovative.” That’s not a compliment. That’s the one man alive who can see both scoreboards, telling you the game’s already been called. Researchers and patents count what’s already been built. Schools count what’s coming next. Huang: “I think it’s like 9 out of the 10 top science and technology schools in the world are now in China. They lead in science and technology in many different fields.” A ranking isn’t a fact. It’s a photograph, and a photograph starts dying the moment the shutter closes. Huang: “This has completely flipped in the last half to a decade. We used to lead most of them. Now they lead most of them.” Five years ago that photograph had America’s name in the corner. Nobody rang a bell when it changed hands, least of all Washington. The flip finished before most people knew there was a game at all. Huang: “They have a large population of highly qualified students. They work incredibly hard. This is a country with enormous might.” Not luck. Not a shortcut. Scale and effort, compounding year over year, on a clock the West assumed it still owned. The photograph isn’t done developing. Not theirs. Not ours. Might is doing two jobs here. One already happened. China built it. The other hasn’t. That half is still unclaimed. Nobody claims it for you. Not China. Not Washington. Not luck. China’s might is a fact. Ours is still a maybe.

Jensen Huang looked at both scoreboards and picked one word for China. Might. Not growth. Not progress. Might. The word for power before it tells you what it wants. Huang: “50% of the world’s AI researchers are Chinese. 70% of last year’s AI patents are published by China.” Half the researchers. Most of the patents. One flag. Huang: “The ecosystem of AI in China is vibrant, rich, incredibly innovative.” That’s not a compliment. That’s the one man alive who can see both scoreboards, telling you the game’s already been called. Researchers and patents count what’s already been built. Schools count what’s coming next. Huang: “I think it’s like 9 out of the 10 top science and technology schools in the world are now in China. They lead in science and technology in many different fields.” A ranking isn’t a fact. It’s a photograph, and a photograph starts dying the moment the shutter closes. Huang: “This has completely flipped in the last half to a decade. We used to lead most of them. Now they lead most of them.” Five years ago that photograph had America’s name in the corner. Nobody rang a bell when it changed hands, least of all Washington. The flip finished before most people knew there was a game at all. Huang: “They have a large population of highly qualified students. They work incredibly hard. This is a country with enormous might.” Not luck. Not a shortcut. Scale and effort, compounding year over year, on a clock the West assumed it still owned. The photograph isn’t done developing. Not theirs. Not ours. Might is doing two jobs here. One already happened. China built it. The other hasn’t. That half is still unclaimed. Nobody claims it for you. Not China. Not Washington. Not luck. China’s might is a fact. Ours is still a maybe.

Dustin

15,569 görüntüleme • 1 ay önce

🤖 Microsoft’s approach to headcount in the AI era: "I will say we will grow a headcount, but the way I look at it is that headcount we grow will grow with a lot more leverage than the headcount we had pre ai. And that's the adjustment. I think structurally you are seeing first, right? Which is one you called it 'getting fit.' — Satya Nadella on Bg2 Pod with Brad Gerstner and Sam Altman w/ Brad Gerstner adding: "I think we're on the verge of incredible economic productivity growth."

🤖 Microsoft’s approach to headcount in the AI era: "I will say we will grow a headcount, but the way I look at it is that headcount we grow will grow with a lot more leverage than the headcount we had pre ai. And that's the adjustment. I think structurally you are seeing first, right? Which is one you called it 'getting fit.' — Satya Nadella on Bg2 Pod with Brad Gerstner and Sam Altman w/ Brad Gerstner adding: "I think we're on the verge of incredible economic productivity growth."

bg2clips

18,368 görüntüleme • 9 ay önce

"Firms installing windows in Utah grew 60% last year. They're one of the heaviest users of AI. A construction firm in Florida grew 65% over the last year." Ramp CEO Eric Glyman (Eric Glyman) on why AI is creating a K-shaped economy: "Companies that are not adopting AI whatsoever — growth rates in the range of 3% to 5% per year." "The difference in growth rate is currently about 6x to 7x and it's accelerating." "While people are pontificating about it, there are businesses that are growing at rates never seen before in American history." The Hill & Valley Forum 2026 The Hill & Valley Forum Ramp

"Firms installing windows in Utah grew 60% last year. They're one of the heaviest users of AI. A construction firm in Florida grew 65% over the last year." Ramp CEO Eric Glyman (Eric Glyman) on why AI is creating a K-shaped economy: "Companies that are not adopting AI whatsoever — growth rates in the range of 3% to 5% per year." "The difference in growth rate is currently about 6x to 7x and it's accelerating." "While people are pontificating about it, there are businesses that are growing at rates never seen before in American history." The Hill & Valley Forum 2026 The Hill & Valley Forum Ramp

The Hill & Valley Forum

22,404 görüntüleme • 4 ay önce

Jordi Visser: The Most Profitable Phase of the AI Trade May Be Over. Is Crypto Next? On July 25, 2026, veteran macro investor Jordi Visser Jordi Visser said on Anthony Pompliano’s show that people are increasingly accepting a new reality: Bitcoin is not a global currency, it will not replace the U.S. dollar, and stablecoins are more likely to replace SWIFT. On AI, he said the most profitable phase of the AI trade may already be over, though that does not mean the AI story is over. As traditional finance and crypto begin to converge, tokenization and stablecoin infrastructure may enter the mainstream earlier than many expect. Source:

Jordi Visser: The Most Profitable Phase of the AI Trade May Be Over. Is Crypto Next? On July 25, 2026, veteran macro investor Jordi Visser Jordi Visser said on Anthony Pompliano’s show that people are increasingly accepting a new reality: Bitcoin is not a global currency, it will not replace the U.S. dollar, and stablecoins are more likely to replace SWIFT. On AI, he said the most profitable phase of the AI trade may already be over, though that does not mean the AI story is over. As traditional finance and crypto begin to converge, tokenization and stablecoin infrastructure may enter the mainstream earlier than many expect. Source:

Wu Blockchain

15,918 görüntüleme • 1 ay önce

The stock market is at all-time highs… but is there a way to actually avoid the next crash? What if one signal has perfectly called every major recession? The “AI Job Apocalypse” that everyone feared? Top AI CEOs are now walking it back! And $TSLA is set up beautifully — both technically and with major company moves that could drive the next leg of all-time highs. Let’s discuss:

The stock market is at all-time highs… but is there a way to actually avoid the next crash? What if one signal has perfectly called every major recession? The “AI Job Apocalypse” that everyone feared? Top AI CEOs are now walking it back! And $TSLA is set up beautifully — both technically and with major company moves that could drive the next leg of all-time highs. Let’s discuss:

NicholasGibbs

13,492 görüntüleme • 3 ay önce