Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

At Sohn, Gavin Baker provided a pretty compelling argument as to why CoreWeave's $CRWV business model is differentiated and durable, lamenting that he couldn't invest in their 2023 round at a $1B valuation (due to a conflict stemming from an existing investment in competitor Crusoe). "CoreWeave, Crusoe, Nebius, Lambda..... is the category durable today? Is it a transitional arbitrage on hyperscaler capex and token friction?" "I absolutely think it's durable... The way to think of running one of these clusters is like driving a Formula 1 race car... It looks easy but it's really hard... The reason a company like CoreWeave can charge a huge premium for their GPU hours is because all GPU hours are not the same. And those CoreWeave GPUs are being utilized 2-3x more per hour on average than the GPUs from a bottom of the barrel provider. And by the way, this all goes for Crusoe and Nebius and the other high-quality neoclouds... The hyperscalers were competing with people running these Formula 1 cars and they were doing overnight shifts in 18-wheelers trying to stay awake to deliver the lower cost. And that's not what AI is about. Now, I think they're making this mental and cultural shift and they've made it, but some of these neoclouds have a very durable business model." $CRWV $NBISshow more

Rittenhouse Research

13,795 subscribers

55,007 views • 3 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Gavin Baker Analyzes the 'Impossible' 8-Gigawatt SpaceX Compute Report “I've seen Elon Musk's companies do really impressive things, but bringing the FundaAI report of 8 gigawatts in 18 months...” "I'll never bet against Elon, but that would be a truly incredible feat." “They're monetizing at something like $50 billion a gig, and consensus estimates for next year are $73 billion.” “So forget Starlink V3, Starlink Direct to Cell, Grok 4.5, and Cursor. The sum of that probably hits a $10 billion ARR pretty quickly.” “The only companies that have brought on more than 500 megawatts of power in a year are the hyperscalers: CoreWeave, Crusoe, SpaceX. And SpaceX has brought on the most, the fastest, at the lowest cost, and people actually really do like their clusters.” “Very little is built into that stock, from my perspective, for the amount of compute that they might be able to bring on. Again, I don't think it's anywhere near 8, and it's going to be really hard, and energizing these GPUs is really hard, but they've been good at it, and it doesn't feel like those estimates are really in people's thinking.” Gavin Baker Patrick OShaughnessy

Gavin Baker Analyzes the 'Impossible' 8-Gigawatt SpaceX Compute Report “I've seen Elon Musk's companies do really impressive things, but bringing the FundaAI report of 8 gigawatts in 18 months...” "I'll never bet against Elon, but that would be a truly incredible feat." “They're monetizing at something like $50 billion a gig, and consensus estimates for next year are $73 billion.” “So forget Starlink V3, Starlink Direct to Cell, Grok 4.5, and Cursor. The sum of that probably hits a $10 billion ARR pretty quickly.” “The only companies that have brought on more than 500 megawatts of power in a year are the hyperscalers: CoreWeave, Crusoe, SpaceX. And SpaceX has brought on the most, the fastest, at the lowest cost, and people actually really do like their clusters.” “Very little is built into that stock, from my perspective, for the amount of compute that they might be able to bring on. Again, I don't think it's anywhere near 8, and it's going to be really hard, and energizing these GPUs is really hard, but they've been good at it, and it doesn't feel like those estimates are really in people's thinking.” Gavin Baker Patrick OShaughnessy

KanekoaTheGreat

44,731 views • 22 days ago

Chamath Palihapitiya just dropped the number that explains the entire AI infrastructure trade (Save this). A gigawatt of compute now costs $100 billion and when he started his Arizona data center project it was $4 to $5 billion, it has gone up 20x in a single investment cycle. The implication is not just that AI infrastructure is expensive but rather that the capital barrier to owning meaningful compute has become so high that only a handful of entities in the world can actually build it and the companies who got there early are sitting on what may be the most durable pricing power in the history of the technology industry. This is the neocloud trade. The neocloud market, purpose-built GPU cloud providers like CoreWeave, Nebius, and Lambda Labs was worth $35 billion in 2026 and is projected to reach $236 billion by 2031, compounding at 46% annually. For context, that is faster growth than cloud computing itself posted in its first decade. The reason is very simple, hyperscalers like AWS, Azure, and Google are building for everything, storage, databases, enterprise software, networking and their GPU pricing reflects the overhead of that full-stack infrastructure. Neoclouds build for one thing only, AI compute. The result is a 60% to 85% cost advantage on the same Nvidia silicon, bare metal H100s at $0.78 to $2.79 per GPU-hour on a neocloud versus $3.43 to $5.07 per GPU-hour on a hyperscaler. That spread does not close as AI demand scales but rather it widens, because hyperscalers have to amortize legacy infrastructure and margin expectations that neoclouds do not carry. Gartner projects that by 2030, neoclouds will capture 20% of the $267 billion AI cloud market, and Vultr's own analysis says at least 80% of GPU market share by end of 2026 will be held by a small group of scaled neocloud providers. Now zoom into Nebius specifically, because it is the most interesting publicly traded proxy for this trade. Nebius is the infrastructure arm of the former Yandex Russia's equivalent of Google rebuilt from the ground up after Russia's invasion of Ukraine by Arkady Volozh and relisted on Nasdaq in October 2024. The team that built it already knew how to run internet-scale infrastructure at the lowest possible cost, which is exactly the operational DNA a neocloud requires. In Q1 2026, Nebius reported revenue of $399 million and already generating serious cash on a young business with revenue growing nearly eightfold year-over-year. Then in March 2026, Meta signed a five-year infrastructure agreement with Nebius worth up to $27 billion, $12 billion in committed dedicated GPU capacity deployments beginning early 2027, plus up to $15 billion more tied to Meta purchasing Nebius's unsold third-party capacity. The deal will be executed on one of the first large-scale deployments of Nvidia's Vera Rubin platform, the next-generation architecture after Blackwell making Nebius one of a tiny number of operators in the world with confirmed priority access to the most advanced AI hardware available. Following the contract, Nebius guided to $7 to $9 billion in annualized recurring revenue for 2026 representing 540% year-over-year growth. Chamath Palihapitiya point about the $100 billion capital moat is the bear case for new entrants and the bull case for incumbents. No one can afford to build the next CoreWeave or Nebius from scratch at current hardware and power costs. The companies that are already built, already contracted, and already deploying Nvidia's latest silicon have a moat that compounds with every GPU generation cycle because they get allocations first, they deploy fastest, and their customers re-sign rather than wait for a new operator that does not yet exist. Come join Milk Road Pro for our full breakdown, the complete neocloud competitive landscape, how to think about Nebius's valuation versus CoreWeave and AI entire thesis. Link below.

Chamath Palihapitiya just dropped the number that explains the entire AI infrastructure trade (Save this). A gigawatt of compute now costs $100 billion and when he started his Arizona data center project it was $4 to $5 billion, it has gone up 20x in a single investment cycle. The implication is not just that AI infrastructure is expensive but rather that the capital barrier to owning meaningful compute has become so high that only a handful of entities in the world can actually build it and the companies who got there early are sitting on what may be the most durable pricing power in the history of the technology industry. This is the neocloud trade. The neocloud market, purpose-built GPU cloud providers like CoreWeave, Nebius, and Lambda Labs was worth $35 billion in 2026 and is projected to reach $236 billion by 2031, compounding at 46% annually. For context, that is faster growth than cloud computing itself posted in its first decade. The reason is very simple, hyperscalers like AWS, Azure, and Google are building for everything, storage, databases, enterprise software, networking and their GPU pricing reflects the overhead of that full-stack infrastructure. Neoclouds build for one thing only, AI compute. The result is a 60% to 85% cost advantage on the same Nvidia silicon, bare metal H100s at $0.78 to $2.79 per GPU-hour on a neocloud versus $3.43 to $5.07 per GPU-hour on a hyperscaler. That spread does not close as AI demand scales but rather it widens, because hyperscalers have to amortize legacy infrastructure and margin expectations that neoclouds do not carry. Gartner projects that by 2030, neoclouds will capture 20% of the $267 billion AI cloud market, and Vultr's own analysis says at least 80% of GPU market share by end of 2026 will be held by a small group of scaled neocloud providers. Now zoom into Nebius specifically, because it is the most interesting publicly traded proxy for this trade. Nebius is the infrastructure arm of the former Yandex Russia's equivalent of Google rebuilt from the ground up after Russia's invasion of Ukraine by Arkady Volozh and relisted on Nasdaq in October 2024. The team that built it already knew how to run internet-scale infrastructure at the lowest possible cost, which is exactly the operational DNA a neocloud requires. In Q1 2026, Nebius reported revenue of $399 million and already generating serious cash on a young business with revenue growing nearly eightfold year-over-year. Then in March 2026, Meta signed a five-year infrastructure agreement with Nebius worth up to $27 billion, $12 billion in committed dedicated GPU capacity deployments beginning early 2027, plus up to $15 billion more tied to Meta purchasing Nebius's unsold third-party capacity. The deal will be executed on one of the first large-scale deployments of Nvidia's Vera Rubin platform, the next-generation architecture after Blackwell making Nebius one of a tiny number of operators in the world with confirmed priority access to the most advanced AI hardware available. Following the contract, Nebius guided to $7 to $9 billion in annualized recurring revenue for 2026 representing 540% year-over-year growth. Chamath Palihapitiya point about the $100 billion capital moat is the bear case for new entrants and the bull case for incumbents. No one can afford to build the next CoreWeave or Nebius from scratch at current hardware and power costs. The companies that are already built, already contracted, and already deploying Nvidia's latest silicon have a moat that compounds with every GPU generation cycle because they get allocations first, they deploy fastest, and their customers re-sign rather than wait for a new operator that does not yet exist. Come join Milk Road Pro for our full breakdown, the complete neocloud competitive landscape, how to think about Nebius's valuation versus CoreWeave and AI entire thesis. Link below.

Milk Road AI

139,047 views • 2 months ago

CoreWeave co-founder brannin mcbee reveals the A100 demand through 2029 is a big narrative violation for a market that thought GPUs would only have 2 to 3 years of useful life: "You don't need the latest generation GPU for every workload. You can think about it as a matrix of different sizes of models versus different sizes of GPUs, and it all just gets filled in volumetrically and economically." "That A100 GPU will cost less on a dollar per hour basis than a brand-new GB300 GPU. But the workload fits most efficiently on that A100, and it ultimately comes down to the engineering organizations making those requests." "It's been a pretty big narrative violation for the market that thought that these GPUs would only have two to three years of useful life, and instead we're contracting GPUs out through its ninth year of life. We expect to see that repeated across subsequent SKUs as well." CoreWeave

MTS

11,653 views • 14 days ago

Dan on why hyperscalers will be a worse business model over time even as growth accelerates: "AWS, Azure, GCP are going to accelerate for a while just because their customer base -- Anthropic, OpenAI -- are growing at an enormous pace. The problem is you went from a dynamic where their customer base was like every corporation in the world and therefore they had fragmentation and it was a really good business. Going forward it's highly unlikely that LLMs are not concentrated in the hands of 4 or 5 companies. Those companies right now, are cashflow negative, and therefore they're looking for compute anywhere they can get it. In the next 5 to 10 years, they'll be generating enormous amounts of free cash flow. When that happens, they're likely to insource the compute. Right now, they look at the hyperscalers as more of a financing mechanism. But I don't think they are better than the LLMs at building data centers. Then you have this dynamic of neoclouds. I don't think they're going away like people thought, because they're better at running GPU clusters than the traditional hyperscalers, and there's a lot of interest from NVIDIA to make sure that their customer base is diversified."

Dan on why hyperscalers will be a worse business model over time even as growth accelerates: "AWS, Azure, GCP are going to accelerate for a while just because their customer base -- Anthropic, OpenAI -- are growing at an enormous pace. The problem is you went from a dynamic where their customer base was like every corporation in the world and therefore they had fragmentation and it was a really good business. Going forward it's highly unlikely that LLMs are not concentrated in the hands of 4 or 5 companies. Those companies right now, are cashflow negative, and therefore they're looking for compute anywhere they can get it. In the next 5 to 10 years, they'll be generating enormous amounts of free cash flow. When that happens, they're likely to insource the compute. Right now, they look at the hyperscalers as more of a financing mechanism. But I don't think they are better than the LLMs at building data centers. Then you have this dynamic of neoclouds. I don't think they're going away like people thought, because they're better at running GPU clusters than the traditional hyperscalers, and there's a lot of interest from NVIDIA to make sure that their customer base is diversified."

Patrick OShaughnessy

341,768 views • 6 months ago

Brad Gerstner Brad Gerstner discussing why CoreWeave $CRWV is the only neocloud position he likes.. Interesting to hear from someone who knows Jensen, Altman, Satya etc. very well.. "We were investors in CoreWeave when it was a private company. We've been investors, you know, as they entered the public market and it's pulled back here, we've added to our position. We're not adding to other neoclouds. We don't think other neoclouds are created equal. We think CoreWeave stands alone in terms of its performance, the software that it's build on top of the cloud, its execution capability, its strategic importance to Nvidia in terms of deploying Rubin, etcetera. So we think it makes a really interesting opportunity."

Brad Gerstner Brad Gerstner discussing why CoreWeave $CRWV is the only neocloud position he likes.. Interesting to hear from someone who knows Jensen, Altman, Satya etc. very well.. "We were investors in CoreWeave when it was a private company. We've been investors, you know, as they entered the public market and it's pulled back here, we've added to our position. We're not adding to other neoclouds. We don't think other neoclouds are created equal. We think CoreWeave stands alone in terms of its performance, the software that it's build on top of the cloud, its execution capability, its strategic importance to Nvidia in terms of deploying Rubin, etcetera. So we think it makes a really interesting opportunity."

Rittenhouse Research

195,455 views • 7 months ago

Chamath: “The Palantir short is stupid.” “The Palantir short is stupid, and I think that those people will lose money.” “The thing that the people that are shorting this company don't understand is that all of these other businesses that you put up there, there is a viable competitor of some kind that you can switch to.” “Look at the one with the lowest multiple to sales, MongoDB. There's 90 versions of what MongoDB does.” “I'm not gonna say whether MongoDB is good or bad. It’s actually a good company. It's an extremely well run business, but it's not unique. It's just extremely well run.” “Snowflake is not unique, but it is well run.” “Palantir is both unique and well run, and there's no clear alternative, so there's no place to churn to.” “And so I think the reason why it has a premium valuation is because the duration and the durability of these cash flows are much longer than what you would typically see in any of these other companies.” “And if people took 1/1000th of a second to actually use their brain, they'd come to that conclusion.”

Chamath: “The Palantir short is stupid.” “The Palantir short is stupid, and I think that those people will lose money.” “The thing that the people that are shorting this company don't understand is that all of these other businesses that you put up there, there is a viable competitor of some kind that you can switch to.” “Look at the one with the lowest multiple to sales, MongoDB. There's 90 versions of what MongoDB does.” “I'm not gonna say whether MongoDB is good or bad. It’s actually a good company. It's an extremely well run business, but it's not unique. It's just extremely well run.” “Snowflake is not unique, but it is well run.” “Palantir is both unique and well run, and there's no clear alternative, so there's no place to churn to.” “And so I think the reason why it has a premium valuation is because the duration and the durability of these cash flows are much longer than what you would typically see in any of these other companies.” “And if people took 1/1000th of a second to actually use their brain, they'd come to that conclusion.”

The All-In Podcast

282,007 views • 9 months ago

Gavin Baker (Gavin Baker) says the disaggregation of inference can extend GPU useful lives from 3-4 years to 10-15. That may single-handedly save private credit and reduce the financing rates for GPUs, which will drive demand and help finance the build-out. "The disaggregation of prefill and inference is going to be amazing for the useful lives of GPU and may single-handedly save private credit. Private credit is in pain from these SaaS loans. But there's a lot of private credit in GPUs too. They were underwriting that to 3-4. The disaggregation of inference means that these GPUs are going to have 10 or 15-year lives. The AI skeptics are like, "Oh, these companies are all cooking their books. The useful life of a GPU is only a year or two. The useful life of a CPU is only four years because the rapid technological change." No. What rapid technological change has done with the disaggregation of prefill and inference is you can put a Cerebras system or Groq LPUs effectively in front of a Hopper or even an Ampere, use that Hopper and Ampere for prefill, and extend the useful life of that GPU until it melts. This is going to be really good for the whole private credit industry. It's gonna help finance the AI build-out. Because if you can start to finance GPUs at 5% or 6% instead of – I think CoreWeave's lowest financing was low sevens – that actually mathematically changes the cost to finance this build-out."

Gavin Baker (Gavin Baker) says the disaggregation of inference can extend GPU useful lives from 3-4 years to 10-15. That may single-handedly save private credit and reduce the financing rates for GPUs, which will drive demand and help finance the build-out. "The disaggregation of prefill and inference is going to be amazing for the useful lives of GPU and may single-handedly save private credit. Private credit is in pain from these SaaS loans. But there's a lot of private credit in GPUs too. They were underwriting that to 3-4. The disaggregation of inference means that these GPUs are going to have 10 or 15-year lives. The AI skeptics are like, "Oh, these companies are all cooking their books. The useful life of a GPU is only a year or two. The useful life of a CPU is only four years because the rapid technological change." No. What rapid technological change has done with the disaggregation of prefill and inference is you can put a Cerebras system or Groq LPUs effectively in front of a Hopper or even an Ampere, use that Hopper and Ampere for prefill, and extend the useful life of that GPU until it melts. This is going to be really good for the whole private credit industry. It's gonna help finance the AI build-out. Because if you can start to finance GPUs at 5% or 6% instead of – I think CoreWeave's lowest financing was low sevens – that actually mathematically changes the cost to finance this build-out."

Invest Like the Best

211,336 views • 3 months ago

The market is watching xAI charge $50 billion per gigawatt and the rest of the neocloud sector run up is just getting started (Save this). According to Gavin Baker of Atreides Management, this is the most important number in AI infrastructure right now, xAI is monetizing compute at $50 billion per gigawatt on the Google deal, 2 to 3 times what any neocloud competitor charges. Google is paying $920 million per month for access to roughly 110,000 Nvidia GPUs through June 2029, and Anthropic is paying $1.25 billion per month for Colossus 1's 300 megawatts. Baker's point is simple that stop tracking rocket launches, stop tracking GPU orders, model gigawatt additions. At $50 billion per gigawatt, every new gigawatt that xAI energizes over the next 12 months is a revenue event that the market has not yet priced in. But this is not just an xAI story but rather why neocloud stocks are one of the most mispriced assets in the entire AI stack. Neoclouds charge $17 to $25 billion per gigawatt in contract value, a dramatic discount to xAI's pricing, but still an extraordinary business model when the underlying infrastructure costs $9 to $12 million per megawatt to operate and customers are signing 5-year locked contracts. H100 GPU-hours from neoclouds like Nebius at $2.95 per GPU-hour are 66% cheaper than hyperscaler rates, which is the structural reason enterprise AI teams are shifting spend to neoclouds at an accelerating pace. The neocloud market is projected to grow 69% annually through 2030 to reach nearly $180 billion and right now only a handful of public companies offer direct exposure to it. Nebius is the standout among the publicly traded neoclouds. It reported Q1 2026 AI cloud revenue of $399 million, an 841% increase year over year beating estimates, with its CEO stating that demand continues to exceed available capacity and customers are actively being turned away. Nebius commands a 20 to 25% revenue premium over peers thanks to its full-stack software offering, European sovereign positioning, and data residency advantages that physically prevent hyperscalers from competing for a large portion of its customer base. It has $49 billion in contracted backlog with Meta, Microsoft, and Nvidia meaning its revenue trajectory for the next three to five years is not a forecast, it is a schedule. The competitive moat is in power, permits, and speed exactly what xAI has proven is the true bottleneck. Jensen Huang said publicly that xAI deploys data centers faster than anyone else in the ecosystem, and Baker called out that this deployment speed advantage directly translates to monetization speed, every week of earlier energization at these pricing levels is worth hundreds of millions in revenue. Neoclouds with secured power, permits, and long-term customer contracts are not in a fair race against companies still waiting on grid connections and zoning approvals. The companies with the most locked in gigawatts coming online in 2026 and 2027 are about to have very good years.

The market is watching xAI charge $50 billion per gigawatt and the rest of the neocloud sector run up is just getting started (Save this). According to Gavin Baker of Atreides Management, this is the most important number in AI infrastructure right now, xAI is monetizing compute at $50 billion per gigawatt on the Google deal, 2 to 3 times what any neocloud competitor charges. Google is paying $920 million per month for access to roughly 110,000 Nvidia GPUs through June 2029, and Anthropic is paying $1.25 billion per month for Colossus 1's 300 megawatts. Baker's point is simple that stop tracking rocket launches, stop tracking GPU orders, model gigawatt additions. At $50 billion per gigawatt, every new gigawatt that xAI energizes over the next 12 months is a revenue event that the market has not yet priced in. But this is not just an xAI story but rather why neocloud stocks are one of the most mispriced assets in the entire AI stack. Neoclouds charge $17 to $25 billion per gigawatt in contract value, a dramatic discount to xAI's pricing, but still an extraordinary business model when the underlying infrastructure costs $9 to $12 million per megawatt to operate and customers are signing 5-year locked contracts. H100 GPU-hours from neoclouds like Nebius at $2.95 per GPU-hour are 66% cheaper than hyperscaler rates, which is the structural reason enterprise AI teams are shifting spend to neoclouds at an accelerating pace. The neocloud market is projected to grow 69% annually through 2030 to reach nearly $180 billion and right now only a handful of public companies offer direct exposure to it. Nebius is the standout among the publicly traded neoclouds. It reported Q1 2026 AI cloud revenue of $399 million, an 841% increase year over year beating estimates, with its CEO stating that demand continues to exceed available capacity and customers are actively being turned away. Nebius commands a 20 to 25% revenue premium over peers thanks to its full-stack software offering, European sovereign positioning, and data residency advantages that physically prevent hyperscalers from competing for a large portion of its customer base. It has $49 billion in contracted backlog with Meta, Microsoft, and Nvidia meaning its revenue trajectory for the next three to five years is not a forecast, it is a schedule. The competitive moat is in power, permits, and speed exactly what xAI has proven is the true bottleneck. Jensen Huang said publicly that xAI deploys data centers faster than anyone else in the ecosystem, and Baker called out that this deployment speed advantage directly translates to monetization speed, every week of earlier energization at these pricing levels is worth hundreds of millions in revenue. Neoclouds with secured power, permits, and long-term customer contracts are not in a fair race against companies still waiting on grid connections and zoning approvals. The companies with the most locked in gigawatts coming online in 2026 and 2027 are about to have very good years.

Milk Road AI

74,945 views • 2 months ago

Marina Purkiss, "These marches. I actually think what you're doing there by saying these are, uh, like Suella Bravo and other people calling them hate marches is it's actually doing the opposite of what we're trying to do here" "If we're serious about tackling anti Semitism, we need to stop being lazy and reckless with what it means. It doesn't mean the thousands of people taking to the streets because they are despairing at, uh, the actions of the Israeli government" "Now, I have seen you in a clip on GB News, and you were talking about how you think the rise in anti Semitism is due to, like, the BBC and Sky News slurring what Israel is doing" "Not that this is right, but there is a spike in anti Semitism directly as a result of the Israeli government's actions since October 7th" "And by the way, that's not my opinion. That is data" Jeremy Vine, "The main connection Marina's making here is the actions of the state of Israel being linked to lives in this country of Jewish people who are trying to go about their daily lives" Marina Purkiss, "Yeah. But I think for me, the person that is actually making such a case for this rise in anti Semitism is Benjamin Netanyahu and the Israeli government because they are trying to make it impossible to distinguish between criticism of Israel and the Jewish identity"

Marina Purkiss, "These marches. I actually think what you're doing there by saying these are, uh, like Suella Bravo and other people calling them hate marches is it's actually doing the opposite of what we're trying to do here" "If we're serious about tackling anti Semitism, we need to stop being lazy and reckless with what it means. It doesn't mean the thousands of people taking to the streets because they are despairing at, uh, the actions of the Israeli government" "Now, I have seen you in a clip on GB News, and you were talking about how you think the rise in anti Semitism is due to, like, the BBC and Sky News slurring what Israel is doing" "Not that this is right, but there is a spike in anti Semitism directly as a result of the Israeli government's actions since October 7th" "And by the way, that's not my opinion. That is data" Jeremy Vine, "The main connection Marina's making here is the actions of the state of Israel being linked to lives in this country of Jewish people who are trying to go about their daily lives" Marina Purkiss, "Yeah. But I think for me, the person that is actually making such a case for this rise in anti Semitism is Benjamin Netanyahu and the Israeli government because they are trying to make it impossible to distinguish between criticism of Israel and the Jewish identity"

Farrukh

40,484 views • 3 months ago

CoreWeave and Nebius are not tech companies. They are equipment leasing businesses. Jim Chanos on iConnections: strip the AI narrative and you have companies that buy GPUs from $NVDA and rent them to hyperscalers. The economics confirm it - mid-to-high single-digit pre-tax returns on capital where the data is available. His rule: a middleman in a supply chain should never trade at a higher multiple than the company that controls its supply. Nvidia sets GPU prices. CoreWeave takes them. TSMC sets chip supply. Neo clouds depend on it. The market has this relationship inverted. That is the compression trade. Full supply chain breakdown and what it means for neo cloud valuations: Source: iConnections -

CoreWeave and Nebius are not tech companies. They are equipment leasing businesses. Jim Chanos on iConnections: strip the AI narrative and you have companies that buy GPUs from $NVDA and rent them to hyperscalers. The economics confirm it - mid-to-high single-digit pre-tax returns on capital where the data is available. His rule: a middleman in a supply chain should never trade at a higher multiple than the company that controls its supply. Nvidia sets GPU prices. CoreWeave takes them. TSMC sets chip supply. Neo clouds depend on it. The market has this relationship inverted. That is the compression trade. Full supply chain breakdown and what it means for neo cloud valuations: Source: iConnections -

Podcast Alpha

65,844 views • 2 months ago

If you hold $CRWV, Dylan Patel just named your real risk, and it is not performance. Dylan Patel of SemiAnalysis: CoreWeave benchmarks above Amazon and Google on GPUs, because hyperscaler multi-tenant security overhead hurts rented-rack performance. The weakness is the balance sheet. Neoclouds pre-sell compute six months before it is live, funded by debt backed by paper contracts. The first wobble already showed up: a Crusoe customer asked to pause construction. Watch the contract book, not the benchmarks. The neocloud thesis in full, from SemiAnalysis on Sequoia Capital: Source: Sequoia Capital -

If you hold $CRWV, Dylan Patel just named your real risk, and it is not performance. Dylan Patel of SemiAnalysis: CoreWeave benchmarks above Amazon and Google on GPUs, because hyperscaler multi-tenant security overhead hurts rented-rack performance. The weakness is the balance sheet. Neoclouds pre-sell compute six months before it is live, funded by debt backed by paper contracts. The first wobble already showed up: a Crusoe customer asked to pause construction. Watch the contract book, not the benchmarks. The neocloud thesis in full, from SemiAnalysis on Sequoia Capital: Source: Sequoia Capital -

Podcast Alpha

55,590 views • 1 month ago

.Stephen Miller: "Let's not pretend for a moment that these Radical Leftists — these terrorists — are operating from a place of sincere political conviction... The leftist is fundamentally motivated by envy, by hatred, by jealousy. The leftist looks at what is beautiful and what is good and what is natural and is filled with envy and hatred. The leftist looks at a perfect family with the perfect life and a perfect job and perfect kids, that goes to church every Sunday, and is filled with a feeling of inadequacy and jealousy — and they covet and they turn those emotions ultimately into a desire to subjugate, to oppress, and to inflict pain and suffering. It's not a coincidence that when you look at these violent Antifa demonstrations and you see any photograph of those who are assembled — to be blunt, not one of the people that is demonstrating looks like a normal person. Not one looks normal. They’re all deformed in some way in their appearance, in their dress, in their mannerisms... Their outer appearance becomes a manifestation of their inner hatred."

.Stephen Miller: "Let's not pretend for a moment that these Radical Leftists — these terrorists — are operating from a place of sincere political conviction... The leftist is fundamentally motivated by envy, by hatred, by jealousy. The leftist looks at what is beautiful and what is good and what is natural and is filled with envy and hatred. The leftist looks at a perfect family with the perfect life and a perfect job and perfect kids, that goes to church every Sunday, and is filled with a feeling of inadequacy and jealousy — and they covet and they turn those emotions ultimately into a desire to subjugate, to oppress, and to inflict pain and suffering. It's not a coincidence that when you look at these violent Antifa demonstrations and you see any photograph of those who are assembled — to be blunt, not one of the people that is demonstrating looks like a normal person. Not one looks normal. They’re all deformed in some way in their appearance, in their dress, in their mannerisms... Their outer appearance becomes a manifestation of their inner hatred."

Rapid Response 47

625,698 views • 1 month ago

💻 I just wanted to show how easy it is getting a GPU in the regular way compared to the 🇪🇺 EU's "AI Factory" plan where you have to apply for a proposal Funnily enough Lambda actually shows "Design your AI Factory" on their landing, maybe they're trying to get that juicy EU money too (but I don't think they have servers in EU anyway) So I sign up/login, select what GPU I want, like 8x H100s, which is $24/hour, select the location, add a filesystem and launch the server Then about 5 minutes later, I have a running 8x H100 cluster, with a Jupyter notebook ready with Terminal access and I can see and work with my GPUs! And no Lambda did not ask me if I was mindful of "Individual, and Social and Environmental Well-Being", and I did not need to apply to some proposal, and wait months. They just gave me a GPU to build a business on, within 5 minutes, as it should be! If the EU wants to help AI startups, the infrastructure is already there! Just fund/subsidize GPU rent prices for European citizens and businesses on existing European hosting companies like Hetzner or OVHcloud that already have GPUs (where the process of getting a server is pretty much the same as Lambda btw) For example, a 8x H100 is $24/hour now but with EU's funding could be $12/hour, giving European startups an unfair advantage to compete with the rest of the world for training and inference (generating) Personally I don't think you should mess with the market like that, but this was the EU's intention, so then do it properly! I thought about it in the shower this morning and realized I guess the fundamental problem in the EU is they just don't respect technology or the people making it. And they don't listen to them like they do elsewhere in for example US or China. You have lots of European founders who'd tell you the same I tell you here, but they're never heard by the EU either In the US you have the top tech CEOs and founders at dinner with the president regularly to advise him and it feels more properly run and they actually listen to smart people In China you have essentially technocrats running the country and fair you can disagree with their system (see Jack Ma etc. not great oaky) but they do understand tech as we can see from how fast they progress and deploy it But the EU just never listens to skilled people, it's always design by committee by midwits and the EU is just systemically rekt like that. It's not a meritocracy at all But I'm a European and an eternal optimist, so maybe we can help improve it by telling them how to do it then (like this tweet) See how easy it could be Ursula von der Leyen

💻 I just wanted to show how easy it is getting a GPU in the regular way compared to the 🇪🇺 EU's "AI Factory" plan where you have to apply for a proposal Funnily enough Lambda actually shows "Design your AI Factory" on their landing, maybe they're trying to get that juicy EU money too (but I don't think they have servers in EU anyway) So I sign up/login, select what GPU I want, like 8x H100s, which is $24/hour, select the location, add a filesystem and launch the server Then about 5 minutes later, I have a running 8x H100 cluster, with a Jupyter notebook ready with Terminal access and I can see and work with my GPUs! And no Lambda did not ask me if I was mindful of "Individual, and Social and Environmental Well-Being", and I did not need to apply to some proposal, and wait months. They just gave me a GPU to build a business on, within 5 minutes, as it should be! If the EU wants to help AI startups, the infrastructure is already there! Just fund/subsidize GPU rent prices for European citizens and businesses on existing European hosting companies like Hetzner or OVHcloud that already have GPUs (where the process of getting a server is pretty much the same as Lambda btw) For example, a 8x H100 is $24/hour now but with EU's funding could be $12/hour, giving European startups an unfair advantage to compete with the rest of the world for training and inference (generating) Personally I don't think you should mess with the market like that, but this was the EU's intention, so then do it properly! I thought about it in the shower this morning and realized I guess the fundamental problem in the EU is they just don't respect technology or the people making it. And they don't listen to them like they do elsewhere in for example US or China. You have lots of European founders who'd tell you the same I tell you here, but they're never heard by the EU either In the US you have the top tech CEOs and founders at dinner with the president regularly to advise him and it feels more properly run and they actually listen to smart people In China you have essentially technocrats running the country and fair you can disagree with their system (see Jack Ma etc. not great oaky) but they do understand tech as we can see from how fast they progress and deploy it But the EU just never listens to skilled people, it's always design by committee by midwits and the EU is just systemically rekt like that. It's not a meritocracy at all But I'm a European and an eternal optimist, so maybe we can help improve it by telling them how to do it then (like this tweet) See how easy it could be Ursula von der Leyen

@levelsio

601,519 views • 10 months ago

The majority of neoclouds will eventually go out of business but here is the winning formula if you want to win. (Save this). The core problem for the industry is that the economics of running GPU infrastructure only work at massive scale, with cheap financing and investment grade customers backing long term contracts. A lot of the names crowding the middle column of that chart are Bitcoin miners who converted their rigs into GPU racks chasing the AI trend, rather than companies built from the ground up for this business, which is exactly the kind of opportunistic entrant that gets wiped out when capital tightens or utilization dips. Nebius sits in the Neocloud Giants tier alongside CoreWeave, Lambda and Crusoe, and today's Q2 2026 print showed exactly why it's pulling away from the pack rather than getting lumped in with the 78 emerging players facing consolidation risk. Revenue hit $582 million, up 454% year over year, with annualized recurring revenue reaching $3.0 billion by the end of June, up 58% quarter over quarter. The company won four separate customer agreements each worth over $1 billion in total contract value and total contract value won during the quarter jumped 4x versus the prior period, a growth rate most of the smaller neoclouds on that chart simply can't match without hyperscaler grade balance sheets. Here's the vertical stack that sets Nebius apart from most names on that chart. Unlike pure GPU rental shops that lease space in someone else's data center, Nebius designs its own data centers, builds its own server racks and motherboards, procures its own compute, and runs a proprietary AI specific cloud platform layer on top of all of it. That full stack control, from silicon to software, is precisely what most of the emerging neoclouds in the chart's middle column lack, since converting a Bitcoin mining facility gives you power and cooling, but not in house rack engineering or a purpose built cloud software layer. Nebius has also been shifting from leased to owned infrastructure, with more than 75% of its contracted power now sitting at facilities it directly controls, up sharply from a mostly leased model just a year ago. That ownership shift is the difference between capturing margin over the long run versus being at the mercy of a landlord's lease terms, which is a structural advantage over neoclouds still renting third party space. Now for the pricing power piece. Nebius disclosed today that it's now charging $40-50 million per megawatt on new capacity deals, already signing its first one at that price this week, up from roughly $12 million per megawatt on its 2026 base contracts. Management also said it could sell its entire 2027 capacity right now on these terms but is deliberately holding some back for near term customer needs, a level of pricing leverage that tells you demand is outstripping supply for anyone offering real scale and reliability, exactly the customer profile the smaller, undercapitalized neoclouds struggle to attract. Nebius isn't a single product company either, which matters given how many names on that chart have no other legs to stand on if GPU rental margins compress. The company owns Avride, an autonomous driving and delivery robotics business with partnerships with Uber and Hyundai, TripleTen, a tech re skilling edtech platform and holds equity stakes in ClickHouse, the database company it spun out and recently backed in a funding round, and in Toloka, an AI data-labeling platform that sold a majority stake to Bezos Expeditions and Shopify in 2025. Those side businesses give Nebius optionality and diversified cash flow that a converted mining rig operator simply doesn't have. Bullish on Nebius, make sure to follow Melvin for more AI infrastructure insights, and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, you can check out the link below for more.

Melvin

37,428 views • 16 days ago

Brian sits on the board of Y Combinator. He said the last batch had 175 companies and only 16 of them weren't enterprise. "Here are the reasons I think it's happening. Number one, when ChatGPT came out, people were afraid it was going to kill their business. Number two, the business model is tricky. There is no consumer business model for AI that I've seen. For example, ChatGPT, there's three ways it can monetize subscriptions. Unfortunately, they're probably going to hit a local maximum percentage of users. Ads, they're hitting a local maximum because Claude and Gemini are not going to do ads. And e-commerce, they shut down the third party apps. And so the first thing is you need to have a business model around consumer AI. People are not trained to pay for information. The second problem is distribution is mature. Like the app store. Now again, top three apps in the app Store are AI, so it does prove you have something revolutionary, you'll find your way to the top. The third thing is, while I think Silicon Valley, we like to describe ourselves as rebels. I think it's very trend based and vibe based. And I think the trend is enterprise. Maybe finally the reason people aren't doing consumer companies is that they're just harder. You have to be good at a lot more things. You generally have to be better at design, marketing, culture, press. It's not purely technology and sales. But my prediction is that we're living in the age of enterprise AI, and I think in the next 12 to 24 months you're gonna see the beginning of a consumer AI renaissance. Almost every app on my home screen has not changed since AI, including Airbnb. I think that's gonna change in two years."

Brian sits on the board of Y Combinator. He said the last batch had 175 companies and only 16 of them weren't enterprise. "Here are the reasons I think it's happening. Number one, when ChatGPT came out, people were afraid it was going to kill their business. Number two, the business model is tricky. There is no consumer business model for AI that I've seen. For example, ChatGPT, there's three ways it can monetize subscriptions. Unfortunately, they're probably going to hit a local maximum percentage of users. Ads, they're hitting a local maximum because Claude and Gemini are not going to do ads. And e-commerce, they shut down the third party apps. And so the first thing is you need to have a business model around consumer AI. People are not trained to pay for information. The second problem is distribution is mature. Like the app store. Now again, top three apps in the app Store are AI, so it does prove you have something revolutionary, you'll find your way to the top. The third thing is, while I think Silicon Valley, we like to describe ourselves as rebels. I think it's very trend based and vibe based. And I think the trend is enterprise. Maybe finally the reason people aren't doing consumer companies is that they're just harder. You have to be good at a lot more things. You generally have to be better at design, marketing, culture, press. It's not purely technology and sales. But my prediction is that we're living in the age of enterprise AI, and I think in the next 12 to 24 months you're gonna see the beginning of a consumer AI renaissance. Almost every app on my home screen has not changed since AI, including Airbnb. I think that's gonna change in two years."

Patrick OShaughnessy

285,938 views • 3 months ago

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.”

Chamath: Frontier AI Leaders “Created a Total Fcking 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 sht 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 views • 2 months ago

Joe Lonsdale: The people in charge of the sociology department at Yale and the education school at Stanford are still god**mn socialists who hate business and are bad for our civilization. But they've learned not to say certain things... A lot of people say, 'Oh, I'm not hearing this stuff anymore. It must be gone.' It's not gone. It's going to come out again as soon as they win. ZUBY: interviews Joe Lonsdale for Real Talk with Zuby Zuby: I feel like there's a change that is happening over the last couple of years with the pendulum starting to swing back. Joe: It's happening in some areas and others. Zuby: How do you see it? Joe: A lot of this, again, is tied to Marxists and socialists who are actively plotting to take over institutions. That's what they've done for the last 60 years. There's the very famous march through the institutions... I thought it was a conspiracy theory when I first heard about it. But it's very clear they've done this very successfully. And you can think of it almost like a virus... In this case, I think the virus has learned to hide itself... A lot of the people who run all of these conquered institutions haven't changed. The people in charge of the sociology department at Yale and the people in charge of the education school at Stanford are still godd*mn socialists who hate businesses and who are bad for our civilization. But they've learned not to say certain things. They've learned not to very publicly and openly say, 'We shouldn't have advanced math anymore,' which is what the education department in general is doing. They're going around getting rid of advanced math for equity purposes... A lot of people say, 'Oh, I'm not hearing this stuff anymore. It must be gone.' It's not frickin gone. It's going to come out again as soon as they win, as soon as they feel like they're safe. But right now they're hiding. I think it's hiding everywhere.

Joe Lonsdale: The people in charge of the sociology department at Yale and the education school at Stanford are still god**mn socialists who hate business and are bad for our civilization. But they've learned not to say certain things... A lot of people say, 'Oh, I'm not hearing this stuff anymore. It must be gone.' It's not gone. It's going to come out again as soon as they win. ZUBY: interviews Joe Lonsdale for Real Talk with Zuby Zuby: I feel like there's a change that is happening over the last couple of years with the pendulum starting to swing back. Joe: It's happening in some areas and others. Zuby: How do you see it? Joe: A lot of this, again, is tied to Marxists and socialists who are actively plotting to take over institutions. That's what they've done for the last 60 years. There's the very famous march through the institutions... I thought it was a conspiracy theory when I first heard about it. But it's very clear they've done this very successfully. And you can think of it almost like a virus... In this case, I think the virus has learned to hide itself... A lot of the people who run all of these conquered institutions haven't changed. The people in charge of the sociology department at Yale and the people in charge of the education school at Stanford are still godd*mn socialists who hate businesses and who are bad for our civilization. But they've learned not to say certain things. They've learned not to very publicly and openly say, 'We shouldn't have advanced math anymore,' which is what the education department in general is doing. They're going around getting rid of advanced math for equity purposes... A lot of people say, 'Oh, I'm not hearing this stuff anymore. It must be gone.' It's not frickin gone. It's going to come out again as soon as they win, as soon as they feel like they're safe. But right now they're hiding. I think it's hiding everywhere.

American Optimist

86,820 views • 2 months ago