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CHRIS CAMILLO ON WHY AMAZON $AMZN IS HIS BIGGEST AI BET Chris Camillo's thesis: the AI efficiency wave. Every company in the world gets massively more efficient over the next few years as they adopt AI. The biggest beneficiary of that wave is undoubtedly Amazon. Why: they spent 20...

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(MAY 2026) Chris Camillo said that Amazon would benefit from every aspect of the “AI supercycle” and said that Amazon will benefit MOST from AI advancements out of any company he knew of Yesterday, July 30th $AMZN surged after beating earnings estimates by ~$3.93/share “I think that Amazon is the ultimate beneficiary of the AI efficiency wave because it wins with AI now four ways.” “With Amazon, it's not a single bet on AI. It's an entire company-wide efficiency flywheel that benefits Amazon more than any other company I've been able to identify in the world.”
1:57

(MAY 2026) Chris Camillo said that Amazon would benefit from every aspect of the “AI supercycle” and said that Amazon will benefit MOST from AI advancements out of any company he knew of Yesterday, July 30th $AMZN surged after beating earnings estimates by ~$3.93/share “I think that Amazon is the ultimate beneficiary of the AI efficiency wave because it wins with AI now four ways.” “With Amazon, it's not a single bet on AI. It's an entire company-wide efficiency flywheel that benefits Amazon more than any other company I've been able to identify in the world.”

The Iced Coffee Hour

42,923 görüntüleme • 14 gün önce

Chris Camillo made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.
1:25

Chris Camillo made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Milk Road Stocks

41,351 görüntüleme • 19 gün önce

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.
1:25

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Milk Road Macro

55,169 görüntüleme • 2 ay önce

China is trying to pop the US AI bubble. Xi just announced China will provide 30 countries with 5,000 AI training and seminar opportunities while building international AI application cooperation centers. China and the US have a different definition of "winning" the AI race. The US strategy: Spend trillions building and controlling the AI infrastructure the world will depend on through a proprietary ecosystem. China is taking the opposite approach: Build cheaper open-source models with similar performance and encourage the world to build on top of them. The bet is simple: The winner of AI will not necessarily be whoever owns the infrastructure. .... It will be whoever builds the best companies on top of it. Just like in the post-dot-com era... The biggest winners were companies like Amazon, Google, and Microsoft that built businesses on top of open infrastructure.
0:41

China is trying to pop the US AI bubble. Xi just announced China will provide 30 countries with 5,000 AI training and seminar opportunities while building international AI application cooperation centers. China and the US have a different definition of "winning" the AI race. The US strategy: Spend trillions building and controlling the AI infrastructure the world will depend on through a proprietary ecosystem. China is taking the opposite approach: Build cheaper open-source models with similar performance and encourage the world to build on top of them. The bet is simple: The winner of AI will not necessarily be whoever owns the infrastructure. .... It will be whoever builds the best companies on top of it. Just like in the post-dot-com era... The biggest winners were companies like Amazon, Google, and Microsoft that built businesses on top of open infrastructure.

Lukas Ekwueme

195,621 görüntüleme • 11 gün önce

Ben Horowitz and Alex Rampell on AI Infrastructure, Crypto, and the Future of Venture a16z's Ben Horowitz and Alex Rampell sit down to discuss why the fundamental rules of building software companies have changed, how AI is creating massive demand for crypto infrastructure, why the next 15 years will make everyone's lives dramatically better, and more. 00:00 Intro 01:39 The new laws of physics for tech companies 06:37 Why not every legacy SaaS company is dead 10:30 America's AI infrastructure bottleneck 14:27 AI + crypto: Why they're more connected than you think 19:54 The future of VC 24:06 AI and the history of technological change benahorowitz.eth Alex Rampell
28:49

Ben Horowitz and Alex Rampell on AI Infrastructure, Crypto, and the Future of Venture a16z's Ben Horowitz and Alex Rampell sit down to discuss why the fundamental rules of building software companies have changed, how AI is creating massive demand for crypto infrastructure, why the next 15 years will make everyone's lives dramatically better, and more. 00:00 Intro 01:39 The new laws of physics for tech companies 06:37 Why not every legacy SaaS company is dead 10:30 America's AI infrastructure bottleneck 14:27 AI + crypto: Why they're more connected than you think 19:54 The future of VC 24:06 AI and the history of technological change benahorowitz.eth Alex Rampell

a16z

24,904 görüntüleme • 4 ay önce

CHRIS CAMILLO SAYS ONE OF THE EASIEST WAY TO GET RICH RIGHT NOW IS BECOMING THE "AI GUY" FOR PEOPLE WHO REFUSE TO LEARN AI "There's a pretty big arbitrage window there for anyone who's willing to simply learn AI and be helpful to someone that is either unwilling to learn AI or just too slow to adopt." - Chris Camillo "There are tens of millions of companies, small, medium, big, and most of them are not even touching AI yet." He points to institutional private equity now planning to spend tens of billions of dollars just helping enterprises onboard AI, because most companies haven't touched it yet. His comparison: it took companies two decades to fully embrace social media, and over a decade to adopt search advertising at scale. "I think that arbitrage window is gonna last a while. Not months. Years." We haven't even started yet.
2:52

CHRIS CAMILLO SAYS ONE OF THE EASIEST WAY TO GET RICH RIGHT NOW IS BECOMING THE "AI GUY" FOR PEOPLE WHO REFUSE TO LEARN AI "There's a pretty big arbitrage window there for anyone who's willing to simply learn AI and be helpful to someone that is either unwilling to learn AI or just too slow to adopt." - Chris Camillo "There are tens of millions of companies, small, medium, big, and most of them are not even touching AI yet." He points to institutional private equity now planning to spend tens of billions of dollars just helping enterprises onboard AI, because most companies haven't touched it yet. His comparison: it took companies two decades to fully embrace social media, and over a decade to adopt search advertising at scale. "I think that arbitrage window is gonna last a while. Not months. Years." We haven't even started yet.

WOLF

34,044 görüntüleme • 1 ay önce

This is why Amazon is spending $200 billion. Andy Jassy, CEO of Amazon, says AI is the biggest technology transformation of our lifetimes. It will reinvent every customer experience we know and create entirely new ones we never imagined. His proof? After 3 years, AI is already running at $15B, which is 260x what AWS was doing at the same point. AWS built one of the most valuable businesses in history. AI is moving faster. Watch his CNBC interview with Cramer.
0:38

This is why Amazon is spending $200 billion. Andy Jassy, CEO of Amazon, says AI is the biggest technology transformation of our lifetimes. It will reinvent every customer experience we know and create entirely new ones we never imagined. His proof? After 3 years, AI is already running at $15B, which is 260x what AWS was doing at the same point. AWS built one of the most valuable businesses in history. AI is moving faster. Watch his CNBC interview with Cramer.

Lark Davis

27,192 görüntüleme • 3 ay önce

Ben Horowitz on the infrastructure behind the AI economy: "Crypto is the natural money for AI because it’s internet-native money." "AI is global. Crypto is global." "There needs to be not just a ledger of money, but probably a ledger of truth for AI to really fulfill its potential." "I think people are probably underestimating how crypto and AI work together to form the AI economy." "Networks and computers tend to grow together, and I think that AI is obviously a new kind of computer and crypto is a new kind of network." benahorowitz.eth on Moonshots with Peter H. Diamandis, MD
2:16

Ben Horowitz on the infrastructure behind the AI economy: "Crypto is the natural money for AI because it’s internet-native money." "AI is global. Crypto is global." "There needs to be not just a ledger of money, but probably a ledger of truth for AI to really fulfill its potential." "I think people are probably underestimating how crypto and AI work together to form the AI economy." "Networks and computers tend to grow together, and I think that AI is obviously a new kind of computer and crypto is a new kind of network." benahorowitz.eth on Moonshots with Peter H. Diamandis, MD

a16z

237,529 görüntüleme • 5 ay önce

Trump’s economic advisor: "Credit card spending is through the roof. They're spending more on gasoline but they're spending more on everything else too." Imagine being so out of touch you think it’s a win that people are struggling so bad that we have to survive on credit cards.
0:24

Trump’s economic advisor: "Credit card spending is through the roof. They're spending more on gasoline but they're spending more on everything else too." Imagine being so out of touch you think it’s a win that people are struggling so bad that we have to survive on credit cards.

Power to the People ☭🕊

30,836 görüntüleme • 3 ay önce

When asked about whether AI stocks are priced too high, Jeremy Siegel said: "I think the biggest risk in AI investing is not whether it will work or not, but can it be done more cheaply?” Firstly, Siegel is a professor at the Wharton School of Business and has been analyzing markets for decades. His point is AI will work and transform the economy—there’s no doubt in this. The real risk is whether tech companies are spending too much ($1 trillion) on data centers to power AI. He pointed to a historical example: During the dot-com boom in the late 1990s, telecom companies laid thousands of miles of fiber optic cables across the country. They spent BILLIONS doing this. Then engineers discovered multiplexing—a way to send a thousand times more data through the same cables. Suddenly, all that infrastructure spending was unnecessary, contributing to the inevitable crash. Siegel is suggesting something similar could happen with AI. What if someone figures out how to run AI much more efficiently? The technology might work perfectly, but the current approach could be massively overbuilt. PS - Siegel covers this in more detail on his interview with CNBC. If you'd like to watch this to learn: - The 3 reasons why AI will transform the world just like the internet did in 90s - Why the biggest risk right now is if it can run more efficiently - How to position yourself when the inevitable crash happens RT and comment "SIEGEL" and I'll DM it to you immediately.
1:13

When asked about whether AI stocks are priced too high, Jeremy Siegel said: "I think the biggest risk in AI investing is not whether it will work or not, but can it be done more cheaply?” Firstly, Siegel is a professor at the Wharton School of Business and has been analyzing markets for decades. His point is AI will work and transform the economy—there’s no doubt in this. The real risk is whether tech companies are spending too much ($1 trillion) on data centers to power AI. He pointed to a historical example: During the dot-com boom in the late 1990s, telecom companies laid thousands of miles of fiber optic cables across the country. They spent BILLIONS doing this. Then engineers discovered multiplexing—a way to send a thousand times more data through the same cables. Suddenly, all that infrastructure spending was unnecessary, contributing to the inevitable crash. Siegel is suggesting something similar could happen with AI. What if someone figures out how to run AI much more efficiently? The technology might work perfectly, but the current approach could be massively overbuilt. PS - Siegel covers this in more detail on his interview with CNBC. If you'd like to watch this to learn: - The 3 reasons why AI will transform the world just like the internet did in 90s - Why the biggest risk right now is if it can run more efficiently - How to position yourself when the inevitable crash happens RT and comment "SIEGEL" and I'll DM it to you immediately.

Felix Prehn 🐶

88,093 görüntüleme • 8 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.
0:42

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

110,076 görüntüleme • 26 gün önce

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?
1:33

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

Ricardo

2,968,734 görüntüleme • 2 ay önce

Elon Musk on the biggest danger of AI and robotics: “I think probably the biggest danger of AI or maybe the biggest danger of AI and robotics going wrong is government People who are opposed to corporations or worried about corporations should really worry the most about government. Government is just a corporation in the limit; it is the biggest corporation with a monopoly on violence The government could potentially use AI and robotics to suppress the population. That’s a serious concern” Elon says the real threat is Big Government armed with superintelligence
0:49

Elon Musk on the biggest danger of AI and robotics: “I think probably the biggest danger of AI or maybe the biggest danger of AI and robotics going wrong is government People who are opposed to corporations or worried about corporations should really worry the most about government. Government is just a corporation in the limit; it is the biggest corporation with a monopoly on violence The government could potentially use AI and robotics to suppress the population. That’s a serious concern” Elon says the real threat is Big Government armed with superintelligence

X Freeze

719,784 görüntüleme • 5 ay önce

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round
17:23

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

a16z crypto

24,239 görüntüleme • 3 ay önce

Gokul explains why outcome-based software companies like Zendesk are more exposed to AI than systems of record like NetSuite, and why public markets are not distinguishing between the two. He argues that the only way AI-native startups can disrupt systems of record is by spending 1-2 years building migration tools to get data off of incumbent platforms. "The software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Instead of paying for 50 Zendesk seats, you can pay for 20 and I can have 30 AI agents sitting next to Zendesk. For these companies you need to change your pricing model to be based on outcome. It's going to be hard for them to stay public. The companies that are less exposed are ones based on data that has been collected and captured over a period of time. ERP is a great example. There is no compelling reason for someone to put their career at stake by ripping out NetSuite. NetSuite has more time to build AI agents on top of it because they have the data, they can train the AI agent on top of it and bundle it. I think the public markets do not distinguish between these two types of companies."
3:06

Gokul explains why outcome-based software companies like Zendesk are more exposed to AI than systems of record like NetSuite, and why public markets are not distinguishing between the two. He argues that the only way AI-native startups can disrupt systems of record is by spending 1-2 years building migration tools to get data off of incumbent platforms. "The software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Instead of paying for 50 Zendesk seats, you can pay for 20 and I can have 30 AI agents sitting next to Zendesk. For these companies you need to change your pricing model to be based on outcome. It's going to be hard for them to stay public. The companies that are less exposed are ones based on data that has been collected and captured over a period of time. ERP is a great example. There is no compelling reason for someone to put their career at stake by ripping out NetSuite. NetSuite has more time to build AI agents on top of it because they have the data, they can train the AI agent on top of it and bundle it. I think the public markets do not distinguish between these two types of companies."

Patrick OShaughnessy

393,820 görüntüleme • 6 ay önce

Dan Ives on CNBC said the AI Revolution could drive nearly $4T of spending over the next 3-4 years and believes the industry is still only “15-20%” through the broader infrastructure buildout cycle. He also called quantum computing a “derivative play on AI” and highlighted quantum stocks $IBM, $IONQ, $QBTS, and $RGTI as part of the next layer of the AI ecosystem. More importantly, Dan Ives said this next phase increasingly expands beyond just $NVDA into hyperscalers, power infrastructure, datacenters, and eventually quantum itself as the AI arms race between the U.S. and China continues accelerating. He also reiterated that demand for AI infrastructure is still accelerating and does not yet include physical AI or China, reinforcing his bullish view across the broader ecosystem tied to compute, power, and infrastructure.
5:34

Dan Ives on CNBC said the AI Revolution could drive nearly $4T of spending over the next 3-4 years and believes the industry is still only “15-20%” through the broader infrastructure buildout cycle. He also called quantum computing a “derivative play on AI” and highlighted quantum stocks $IBM, $IONQ, $QBTS, and $RGTI as part of the next layer of the AI ecosystem. More importantly, Dan Ives said this next phase increasingly expands beyond just $NVDA into hyperscalers, power infrastructure, datacenters, and eventually quantum itself as the AI arms race between the U.S. and China continues accelerating. He also reiterated that demand for AI infrastructure is still accelerating and does not yet include physical AI or China, reinforcing his bullish view across the broader ecosystem tied to compute, power, and infrastructure.

Sam Badawi

65,947 görüntüleme • 2 ay önce

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 görüntüleme • 2 ay önce

Is AI really a bubble, or are we just early? Jeff Lutz 🔋 makes a good point: not every AI bet will work, but it’s hard to ignore what the biggest players are doing. NVIDIA, hyperscalers, Elon Musk and some of the world’s largest capital allocators are still spending billions to build more AI infrastructure. The hype will come and go. But if the spending keeps growing, maybe the more interesting question is: what do they see that the rest of the market doesn’t?
3:56

Is AI really a bubble, or are we just early? Jeff Lutz 🔋 makes a good point: not every AI bet will work, but it’s hard to ignore what the biggest players are doing. NVIDIA, hyperscalers, Elon Musk and some of the world’s largest capital allocators are still spending billions to build more AI infrastructure. The hype will come and go. But if the spending keeps growing, maybe the more interesting question is: what do they see that the rest of the market doesn’t?

Herbert Ong

22,497 görüntüleme • 3 gün önce

Blackrock CEO Larry Fink on if AI is a bubble: “I don’t think there’s any uncertainty about AI. There’s no question that hundreds of billions of dollars is needed to build this out. The capex is going to drive more global growth. I sincerely believe there is no bubble”
0:42

Blackrock CEO Larry Fink on if AI is a bubble: “I don’t think there’s any uncertainty about AI. There’s no question that hundreds of billions of dollars is needed to build this out. The capex is going to drive more global growth. I sincerely believe there is no bubble”

Small Cap Snipa

97,110 görüntüleme • 6 ay önce