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My biggest question heading into $NVDA earnings is whether demand keeps broadening beyond $MSFT, $AMZN and $GOOGL into ACIE and newer buyers like $SPCX. I also want to see whether Rubin can replace Blackwell at a higher system value allowing Nvidia to capture more of the rack across CPUs,... show more

Shay Boloor

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49,916 次观看 • 8 天前 •via X (Twitter)

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$NVDA is evolving into the platform behind the entire AI factory spanning compute, CPUs, networking, interconnect, software, rack-scale systems and now the financing that helps customers build them. Owning more of that stack lets Nvidia capture more of every dollar spent on AI infrastructure while sitting across the bottlenecks that determine how quickly the entire market can scale.

$NVDA is evolving into the platform behind the entire AI factory spanning compute, CPUs, networking, interconnect, software, rack-scale systems and now the financing that helps customers build them. Owning more of that stack lets Nvidia capture more of every dollar spent on AI infrastructure while sitting across the bottlenecks that determine how quickly the entire market can scale.

Shay Boloor

152,747 次观看 • 8 天前

The cleanest test of the AI cycle is what $NVDA is actually shipping, and current expectations still point to revenue climbing from ~$95B this quarter toward ~$110B next quarter. If revenue keeps rising while gross margins hold around 75% then it becomes much harder to argue the compute boom is already rolling over. That demand base is still expanding too with $SPCX potentially growing from ~4% of Nvidia revenue today toward 10% by the end of 2027 as its compute buildout scales.

The cleanest test of the AI cycle is what $NVDA is actually shipping, and current expectations still point to revenue climbing from ~$95B this quarter toward ~$110B next quarter. If revenue keeps rising while gross margins hold around 75% then it becomes much harder to argue the compute boom is already rolling over. That demand base is still expanding too with $SPCX potentially growing from ~4% of Nvidia revenue today toward 10% by the end of 2027 as its compute buildout scales.

Shay Boloor

103,065 次观看 • 6 天前

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

Shay Boloor

261,814 次观看 • 3 个月前

I still own $IREN because I think the market is underestimating both the $NVDA alignment and how hard its power footprint is to replicate. If the company can turn ~5 GW of secured power into Nvidia-aligned AI cloud capacity then the market may start valuing the 10x gap between its power base and near-term AI cloud needs.

I still own $IREN because I think the market is underestimating both the $NVDA alignment and how hard its power footprint is to replicate. If the company can turn ~5 GW of secured power into Nvidia-aligned AI cloud capacity then the market may start valuing the 10x gap between its power base and near-term AI cloud needs.

Shay Boloor

1,314,709 次观看 • 3 个月前

$ORCL is borrowing aggressively to build AI data centers for a customer base heavily tied to OpenAI and the market is starting to question whether Oracle can fund that buildout without $MSFT, $GOOGL, $AMZN or $META level cash generation. The upside is that OCI now has one of the largest AI backlogs in the market at ~$640B which gives Oracle a real shot at becoming the fourth major AI cloud platform if that demand converts into durable revenue. If cloud growth stays above 50% and customer prepayments ease the funding burden then this selloff could eventually look like the painful capital cycle before the harvest phase.

$ORCL is borrowing aggressively to build AI data centers for a customer base heavily tied to OpenAI and the market is starting to question whether Oracle can fund that buildout without $MSFT, $GOOGL, $AMZN or $META level cash generation. The upside is that OCI now has one of the largest AI backlogs in the market at ~$640B which gives Oracle a real shot at becoming the fourth major AI cloud platform if that demand converts into durable revenue. If cloud growth stays above 50% and customer prepayments ease the funding burden then this selloff could eventually look like the painful capital cycle before the harvest phase.

Shay Boloor

132,000 次观看 • 2 个月前

$NBIS and $CRWV growing like crazy shouldn't be surprising. Satya Nadella publicly explained 6 months ago on a podcast that $MSFT would be leasing a lot of capacity going forward rather than building all itself. Here is what I think is happening: These neo-cloud businesses, both $NBIS and $CRWV, exist solely because $NVDA wants them to exist. Nvidia has an equity stake in both companies, and they are both members of the Nvidia Partners Program. Nvidia grants early access to its chips to the partners. Nvidia does that because it knows all hyperscalers, especially $MSFT and $AMZN, are racing to develop their own cutting-edge GPUs, as this is their biggest cost in scaling cloud operations. Nvidia knows that if they are allowed to control the supply, it will prolong the upgrade cycles and reduce orders to gain time to develop its own chips. This is why it's providing early access to the neo-clouds that are 100% dependent on Nvidia chips. Hyperscalers know that if they delay orders for the fresh capacity, the demand will shift to the neo-clouds that can build capacity fast with the support of $NVDA. Thus, $NVDA corners hyperscalers and strategically compels them to put new orders and cripples their ability to focus on their own chips. $MSFT sees this and says, "If this is the case, I'll just lease the capacity from the neo-clouds." It's basically a strategic response to $NVDA. It leases the bulk of their capacity, making them dependent on it. So, if $MSFT backs down, they'll have a really hard time staying alive. There is a small window of opportunity here for neo-clouds. If they can scale beyond hyperscalers and form a fragmented customer base, they may keep thriving even if hyperscalers reduce leases. Currently, $NBIS has a better shot at it than $CRWV, as $MSFT already makes up 72% of its revenue. I am long $NBIS, and I have already made 4x of money in the stock. I'll remain long $NBIS and even grow my position, but I'll remain skeptical of $CRWV for its unfavorable strategic position, as I explained above.

$NBIS and $CRWV growing like crazy shouldn't be surprising. Satya Nadella publicly explained 6 months ago on a podcast that $MSFT would be leasing a lot of capacity going forward rather than building all itself. Here is what I think is happening: These neo-cloud businesses, both $NBIS and $CRWV, exist solely because $NVDA wants them to exist. Nvidia has an equity stake in both companies, and they are both members of the Nvidia Partners Program. Nvidia grants early access to its chips to the partners. Nvidia does that because it knows all hyperscalers, especially $MSFT and $AMZN, are racing to develop their own cutting-edge GPUs, as this is their biggest cost in scaling cloud operations. Nvidia knows that if they are allowed to control the supply, it will prolong the upgrade cycles and reduce orders to gain time to develop its own chips. This is why it's providing early access to the neo-clouds that are 100% dependent on Nvidia chips. Hyperscalers know that if they delay orders for the fresh capacity, the demand will shift to the neo-clouds that can build capacity fast with the support of $NVDA. Thus, $NVDA corners hyperscalers and strategically compels them to put new orders and cripples their ability to focus on their own chips. $MSFT sees this and says, "If this is the case, I'll just lease the capacity from the neo-clouds." It's basically a strategic response to $NVDA. It leases the bulk of their capacity, making them dependent on it. So, if $MSFT backs down, they'll have a really hard time staying alive. There is a small window of opportunity here for neo-clouds. If they can scale beyond hyperscalers and form a fragmented customer base, they may keep thriving even if hyperscalers reduce leases. Currently, $NBIS has a better shot at it than $CRWV, as $MSFT already makes up 72% of its revenue. I am long $NBIS, and I have already made 4x of money in the stock. I'll remain long $NBIS and even grow my position, but I'll remain skeptical of $CRWV for its unfavorable strategic position, as I explained above.

Oguz Erkan

180,198 次观看 • 11 个月前

$CBRS is a very unique company because it keeps a huge amount of compute and memory very close together which helps it deliver extremely fast inference and makes the architecture well positioned for agentic AI workloads where fast tokens matter more. OpenAI validated the tec but the stock is getting hit because we still don't have enough visibility into how Cerebras turns that technical advantage into a broad, diversified and high-margin business. Customer concentration remains a massive risk especially with so much revenue tied to its own investor and the company still has to solve the physical infrastructure side of the business across power, cooling, data center capacity and deployment timing. If $NVDA is trading at a below-market multiple while still growing faster than Cerebras then why buy the Nvidia alternative instead of just owning Nvidia?

$CBRS is a very unique company because it keeps a huge amount of compute and memory very close together which helps it deliver extremely fast inference and makes the architecture well positioned for agentic AI workloads where fast tokens matter more. OpenAI validated the tec but the stock is getting hit because we still don't have enough visibility into how Cerebras turns that technical advantage into a broad, diversified and high-margin business. Customer concentration remains a massive risk especially with so much revenue tied to its own investor and the company still has to solve the physical infrastructure side of the business across power, cooling, data center capacity and deployment timing. If $NVDA is trading at a below-market multiple while still growing faster than Cerebras then why buy the Nvidia alternative instead of just owning Nvidia?

Shay Boloor

204,924 次观看 • 2 个月前

Building AI infrastructure at yotta-scale requires more than raw performance; it demands an open, modular rack design that can evolve across product generations, combining leadership compute engines with high-speed networking to connect thousands of accelerators into a single, unified system. Take a look at the Helios. Our rack-scale AI platform powered by MI455X GPUs and EPYC “Venice” CPUs and designed for trillion-parameter training.

Building AI infrastructure at yotta-scale requires more than raw performance; it demands an open, modular rack design that can evolve across product generations, combining leadership compute engines with high-speed networking to connect thousands of accelerators into a single, unified system. Take a look at the Helios. Our rack-scale AI platform powered by MI455X GPUs and EPYC “Venice” CPUs and designed for trillion-parameter training.

AMD

20,832 次观看 • 7 个月前

Jensen Huang just admitted Nvidia is paying for BOTH ends of its own $500 billion deal. Every outlet ran the same headline: Nvidia is putting half a trillion dollars into Korea. The largest AI infrastructure commitment ever announced with a single partner. But when asked what was actually inside that number and whether this is Nvidia spending money in the Korean economy, or SK fronting the capital themselves, Jensen said this: "We're gonna be purchasing memories from them for many years to come. In order to build a trillion dollars worth of Vera Rubin systems, you're gonna have to buy a lot of system memories to go with it. And so we have large purchase agreements and large purchase intentions with SK Hynix. Meanwhile, SK Telecom is gonna become an AI cloud. And in that agreement, we will be selling AI supercomputers to them. So between us, we're gonna do $500 billion worth of business." He literally described two completely different transactions and added them together. Nvidia pays SK Hynix for memory chips. SK Telecom pays Nvidia for supercomputers. Both directions get stacked into one figure and handed to the market as demand. A large share of that half trillion dollars is Nvidia's own money going OUT the door. This is the CEO of the most important chip company on Earth. His silicon runs every serious AI system on the planet. If anyone alive could announce a clean half trillion in customer demand, it's him. Instead he announced a number that counts his own supplier payments as "business." But now this is where it gets genuinely crazy... Bloomberg asked how badly Nvidia needs Korean supply to grow. Jensen said Nvidia does not have enough bits. He said the company is constrained in HBM memory, constrained in LPDDR memory, and constrained in just about every part of the supply chain. Then he named the bottleneck nobody expected: "We're even constrained now with land and power and construction workers to set up the data centers." The company announcing the biggest AI deal in history cannot hire enough people to pour concrete. Then he capped the entire industry. He said the industry has the ability to double each year, and will have a hard time growing much faster than that. Now hold that against the target he set at the top of the same interview: He said the semiconductor industry probably has to become 10x larger than it is today over the next decade. Doubling annually clears that on a spreadsheet. But in reality it only happens if land, power and construction crews cooperate every single year for ten years straight. And the demand justifying all of it is a number most people have not heard yet. Jensen is planning for 100 BILLION AI agents and billions of robots using computers. That is the actual bet. 10x the industry, financed by deals where the vendor is also the customer, and gated by how fast you can find electricians. Korea's market did not celebrate any of this by the way. The KOSPI has been falling hard and SK Hynix and Samsung both slumped while the half trillion dollar headline was running. Jensen listed both directions of money and totaled them on camera because he does not think there is anything wrong with it. Maybe there isn't. Chips have to be bought before systems can be sold. But the market is pricing these announcements as demand, and at least half of this one is spending.

Jensen Huang just admitted Nvidia is paying for BOTH ends of its own $500 billion deal. Every outlet ran the same headline: Nvidia is putting half a trillion dollars into Korea. The largest AI infrastructure commitment ever announced with a single partner. But when asked what was actually inside that number and whether this is Nvidia spending money in the Korean economy, or SK fronting the capital themselves, Jensen said this: "We're gonna be purchasing memories from them for many years to come. In order to build a trillion dollars worth of Vera Rubin systems, you're gonna have to buy a lot of system memories to go with it. And so we have large purchase agreements and large purchase intentions with SK Hynix. Meanwhile, SK Telecom is gonna become an AI cloud. And in that agreement, we will be selling AI supercomputers to them. So between us, we're gonna do $500 billion worth of business." He literally described two completely different transactions and added them together. Nvidia pays SK Hynix for memory chips. SK Telecom pays Nvidia for supercomputers. Both directions get stacked into one figure and handed to the market as demand. A large share of that half trillion dollars is Nvidia's own money going OUT the door. This is the CEO of the most important chip company on Earth. His silicon runs every serious AI system on the planet. If anyone alive could announce a clean half trillion in customer demand, it's him. Instead he announced a number that counts his own supplier payments as "business." But now this is where it gets genuinely crazy... Bloomberg asked how badly Nvidia needs Korean supply to grow. Jensen said Nvidia does not have enough bits. He said the company is constrained in HBM memory, constrained in LPDDR memory, and constrained in just about every part of the supply chain. Then he named the bottleneck nobody expected: "We're even constrained now with land and power and construction workers to set up the data centers." The company announcing the biggest AI deal in history cannot hire enough people to pour concrete. Then he capped the entire industry. He said the industry has the ability to double each year, and will have a hard time growing much faster than that. Now hold that against the target he set at the top of the same interview: He said the semiconductor industry probably has to become 10x larger than it is today over the next decade. Doubling annually clears that on a spreadsheet. But in reality it only happens if land, power and construction crews cooperate every single year for ten years straight. And the demand justifying all of it is a number most people have not heard yet. Jensen is planning for 100 BILLION AI agents and billions of robots using computers. That is the actual bet. 10x the industry, financed by deals where the vendor is also the customer, and gated by how fast you can find electricians. Korea's market did not celebrate any of this by the way. The KOSPI has been falling hard and SK Hynix and Samsung both slumped while the half trillion dollar headline was running. Jensen listed both directions of money and totaled them on camera because he does not think there is anything wrong with it. Maybe there isn't. Chips have to be bought before systems can be sold. But the market is pricing these announcements as demand, and at least half of this one is spending.

Ricardo

35,609 次观看 • 1 个月前

$ONDS is trying to build a full 'system-of-systems' across aerial drones, counter-drone systems, ground robotics, ISR, border security, demining and AI-enabled command-and-control. That's where the $PLTR partnership becomes important because software is what can turn a collection of drones, sensors and robots into a real operating system. The acquisition strategy is aggressive but this quarter made it look a lot more credible. Less like a roll-up and more like an emerging autonomous defense platform with real demand behind it.

$ONDS is trying to build a full 'system-of-systems' across aerial drones, counter-drone systems, ground robotics, ISR, border security, demining and AI-enabled command-and-control. That's where the $PLTR partnership becomes important because software is what can turn a collection of drones, sensors and robots into a real operating system. The acquisition strategy is aggressive but this quarter made it look a lot more credible. Less like a roll-up and more like an emerging autonomous defense platform with real demand behind it.

Shay Boloor

291,777 次观看 • 3 个月前

$NVDA isn’t just selling GPUs anymore… they’re becoming the venture capitalist of the entire AI economy. Over $40 BILLION in equity investments this year alone: • $30B into OpenAI • ~$3.2B into $GLW • ~$2.1B into $IREN • ~$2B each into $MRVL, $LITE, $COHR, $CRWV, $NBIS My observation? Jensen is systematically buying stakes across every critical layer — chips, optics, power, networking, neoclouds, and the model companies themselves. This isn’t random investing. This is vertical integration on steroids. When the whole AI stack eventually needs to scale, a huge chunk of the economics now flows back to Nvidia. The more I look at it, the more it feels like Nvidia is building its own moat with actual ownership, not just technology leadership. This changes how I think about $NVDA long-term. You see this as brilliant capital allocation or overreach?

$NVDA isn’t just selling GPUs anymore… they’re becoming the venture capitalist of the entire AI economy. Over $40 BILLION in equity investments this year alone: • $30B into OpenAI • ~$3.2B into $GLW • ~$2.1B into $IREN • ~$2B each into $MRVL, $LITE, $COHR, $CRWV, $NBIS My observation? Jensen is systematically buying stakes across every critical layer — chips, optics, power, networking, neoclouds, and the model companies themselves. This isn’t random investing. This is vertical integration on steroids. When the whole AI stack eventually needs to scale, a huge chunk of the economics now flows back to Nvidia. The more I look at it, the more it feels like Nvidia is building its own moat with actual ownership, not just technology leadership. This changes how I think about $NVDA long-term. You see this as brilliant capital allocation or overreach?

Penny

15,403 次观看 • 3 个月前

The Three Tailwinds Nobody's Pricing Into Nvidia 🔊 On Monday's edition of The Macro Show, Director of Research Daryl Jones Jonesy and $HGRO Portfolio Manager Sam Rahman Sam Rahman explained how a PM actually positions into a print like Nvidia's, $NVDA. As Rahman noted, he owns both Nvidia and Marvell, $MRVL — the only two semis currently on the signal strength list — but keeps his active Nvidia position small, with far bigger active weights in software names like Amazon, $AMZN and Microsoft, $MSFT. His approach into big benchmark events is not to overthink the positioning, because get on the wrong side of the news flow and you can get hurt badly. The number that frames the quarter, Rahman explained, is that Nvidia's data-center business has the potential to nearly double year-over-year, an extraordinary feat for a company its size: "Think about the size of this company doubling its core sales line year over year." Beyond the print, he flagged three tailwinds: 1. The transition from Blackwell to the faster, more efficient Vera Rubin chip, with hyperscaler orders already landing. 2. SpaceX emerging as a large, genuinely incremental new buyer of data-center infrastructure post-IPO. 3. A roughly 15% price increase on chips and servers next year, driven by memory-chip inflation, that flows straight to revenue. Subscribe to The Macro Show for daily market analysis you won't find anywhere else:

The Three Tailwinds Nobody's Pricing Into Nvidia 🔊 On Monday's edition of The Macro Show, Director of Research Daryl Jones Jonesy and $HGRO Portfolio Manager Sam Rahman Sam Rahman explained how a PM actually positions into a print like Nvidia's, $NVDA. As Rahman noted, he owns both Nvidia and Marvell, $MRVL — the only two semis currently on the signal strength list — but keeps his active Nvidia position small, with far bigger active weights in software names like Amazon, $AMZN and Microsoft, $MSFT. His approach into big benchmark events is not to overthink the positioning, because get on the wrong side of the news flow and you can get hurt badly. The number that frames the quarter, Rahman explained, is that Nvidia's data-center business has the potential to nearly double year-over-year, an extraordinary feat for a company its size: "Think about the size of this company doubling its core sales line year over year." Beyond the print, he flagged three tailwinds: 1. The transition from Blackwell to the faster, more efficient Vera Rubin chip, with hyperscaler orders already landing. 2. SpaceX emerging as a large, genuinely incremental new buyer of data-center infrastructure post-IPO. 3. A roughly 15% price increase on chips and servers next year, driven by memory-chip inflation, that flows straight to revenue. Subscribe to The Macro Show for daily market analysis you won't find anywhere else:

Hedgeye

13,455 次观看 • 8 天前

If you want to become a millionaire this year, do exactly what I say every day. Here's the market opportunities: 1. $DRAM, $MU, $SNDK, and other companies like $INTC, $AMD, $AMZN, etc. are forming potential bull flags (continuation for further upside if these lows can hold). 2. $IGV and software names like $NOW, $ADBE, $CRM, etc. will retest it's breakout to see if this is REAL conviction or a fake pump. Watch for the buyers, watch for the volume. 3. Stage 2 setups like $CIFR, $IREN, and others are on watch. All in all, I am a buyer of every dip in AI stocks. I am also BALANCED across AI + core defensive stocks heading into the summer. I expect the next few days to be relief (green). We'll see how the markets react and be buyers at key levels.

If you want to become a millionaire this year, do exactly what I say every day. Here's the market opportunities: 1. $DRAM, $MU, $SNDK, and other companies like $INTC, $AMD, $AMZN, etc. are forming potential bull flags (continuation for further upside if these lows can hold). 2. $IGV and software names like $NOW, $ADBE, $CRM, etc. will retest it's breakout to see if this is REAL conviction or a fake pump. Watch for the buyers, watch for the volume. 3. Stage 2 setups like $CIFR, $IREN, and others are on watch. All in all, I am a buyer of every dip in AI stocks. I am also BALANCED across AI + core defensive stocks heading into the summer. I expect the next few days to be relief (green). We'll see how the markets react and be buyers at key levels.

AskLivermore

195,053 次观看 • 3 个月前

🎙️ Want a full breakdown on why cost per token is a key metric for AI infrastructure TCO? We’re operating in a power-constrained world. Demand for intelligence is scaling faster than infrastructure can keep up—so metrics like cost per GPU hour or FLOPs per dollar don’t tell the full story. When it comes to TCO, Cost per Token is the metric that captures end-to-end performance across GPUs, CPUs, networking, software, and ecosystem making it the key driver of real profitability and scalability in AI. If you’re not measuring efficiency at the token level, you’re missing what actually drives cost. Watch the deep-dive conversation with Dr. Gerro Prinsloo , Nader Khalil and Carter Abdallah, live on the NVIDIA YouTube channel.

🎙️ Want a full breakdown on why cost per token is a key metric for AI infrastructure TCO? We’re operating in a power-constrained world. Demand for intelligence is scaling faster than infrastructure can keep up—so metrics like cost per GPU hour or FLOPs per dollar don’t tell the full story. When it comes to TCO, Cost per Token is the metric that captures end-to-end performance across GPUs, CPUs, networking, software, and ecosystem making it the key driver of real profitability and scalability in AI. If you’re not measuring efficiency at the token level, you’re missing what actually drives cost. Watch the deep-dive conversation with Dr. Gerro Prinsloo , Nader Khalil and Carter Abdallah, live on the NVIDIA YouTube channel.

NVIDIA

21,970 次观看 • 4 个月前

AI investment is expanding beyond models and applications into the full stack that supports them. Energy capacity, semiconductor supply, compute infrastructure, and software layers are becoming more connected, influencing how and where AI can be built and deployed. In partnership with NVIDIA, The Futurum Group examines the Five Layers of the AI Cake framework as a way to understand the structure of the AI economy. The market brief outlines how value is distributed across the stack, where bottlenecks are forming, and what these dynamics mean for enterprise strategy, capital allocation, workforce planning, and global competitiveness. ⏯️ Explore the key findings, and use the link to download the full report: 👉 #AIInfrastructure #NVIDIA #Futurum

AI investment is expanding beyond models and applications into the full stack that supports them. Energy capacity, semiconductor supply, compute infrastructure, and software layers are becoming more connected, influencing how and where AI can be built and deployed. In partnership with NVIDIA, The Futurum Group examines the Five Layers of the AI Cake framework as a way to understand the structure of the AI economy. The market brief outlines how value is distributed across the stack, where bottlenecks are forming, and what these dynamics mean for enterprise strategy, capital allocation, workforce planning, and global competitiveness. ⏯️ Explore the key findings, and use the link to download the full report: 👉 #AIInfrastructure #NVIDIA #Futurum

The Futurum Group

75,859 次观看 • 4 个月前

Every AI response you've ever gotten started with an electron. ⚡ In a recent interview with Sequoia Capital, Jensen Huang described AI infrastructure as a five-layer cake, and at the very bottom, before chips, before data centers, before models, is energy. That's the binding constraint on the Intelligence Age: not compute, not software — watts. This is why NVIDIA calls AI factories the dynamos of our era. They take in electrons and send out tokens of intelligence. We're a few hundred billion dollars into what Jensen calls the largest infrastructure buildout in human history. Trillions more to go. The question isn't whether AI will scale. It's whether the energy grid can keep up. ⬆️

Every AI response you've ever gotten started with an electron. ⚡ In a recent interview with Sequoia Capital, Jensen Huang described AI infrastructure as a five-layer cake, and at the very bottom, before chips, before data centers, before models, is energy. That's the binding constraint on the Intelligence Age: not compute, not software — watts. This is why NVIDIA calls AI factories the dynamos of our era. They take in electrons and send out tokens of intelligence. We're a few hundred billion dollars into what Jensen calls the largest infrastructure buildout in human history. Trillions more to go. The question isn't whether AI will scale. It's whether the energy grid can keep up. ⬆️

NVIDIA

102,834 次观看 • 1 个月前

The recent semiconductor selloff has spread worldwide because the supply chain spans U.S. chip design and cloud spending, Taiwanese manufacturing, Korean memory, Japanese materials, European equipment and Southeast Asian packaging. That makes $MSFT earnings today massive as its June fiscal year-end offers the first major look at spending plans for the first 6 months of 2027 across accelerators, CPUs, memory, networking, optics, advanced packaging, power and equipment. If Microsoft confirms AI demand remains above capacity and capex is still growing 30% to 40% then the selloff will look more like a financing and risk-off reset than evidence the semiconductor cycle is breaking.

The recent semiconductor selloff has spread worldwide because the supply chain spans U.S. chip design and cloud spending, Taiwanese manufacturing, Korean memory, Japanese materials, European equipment and Southeast Asian packaging. That makes $MSFT earnings today massive as its June fiscal year-end offers the first major look at spending plans for the first 6 months of 2027 across accelerators, CPUs, memory, networking, optics, advanced packaging, power and equipment. If Microsoft confirms AI demand remains above capacity and capex is still growing 30% to 40% then the selloff will look more like a financing and risk-off reset than evidence the semiconductor cycle is breaking.

Shay Boloor

78,929 次观看 • 1 个月前

Nvidia's Jensen Huang on Fox Business: * Asked for a single word on the rest of the year, Huang says "demand accelerating" * Says the reason is AI does productive work and the tokens labs generate are "profitable tokens," so what's holding it back now is just compute. * Next year is already sold out and supply-constrained at 70% growth. * "Every single [chip] that we can make has already been sold." * Customers commit a year-plus ahead because "you're not buying a computer, you're building a factory," at $50-60 billion each. * With memory prices way up, Nvidia reset margin guidance this quarter to "rip the band-aid off." * Margins fall from 75% to 72 - 73% next year after absorbing memory cost increases and repricing, to clear what he called "a cloud on our stock." * Next year's Vera Rubin will ramp even faster than Blackwell did, which Huang calls "the fastest product launch we've ever had in history." * Bottlenecks "literally everywhere," the biggest buildout in history. * Constraints span TSMC CoWoS packaging, wafers, memory, networking, silicon photonics, power generation, and "high-quality land that's powered," plus a skilled-labor shortage in the US * Says scarcity is not a bad thing. This quarter's 100% growth and next year's 70% are both supply-constrained, which can be healthy because it "causes the best technologies to emerge and rise" and makes everybody sharper. * AWS alone is set to add 2 million GPUs across 2027 and 2028. Half of revenue comes from about six hyperscalers, much of it rented onward to "Nvidia developers all over the world" * Says on hyperscalers, the Nvidia platform is "the most rentable" and "captures the highest pricing" of anything hyperscalers own. * After Bill Gates suggested taxing tokens over AI job losses, Huang says: "I see things very differently than he does." * Argues AI is "a net job creator at a scale that we've never seen" because productive companies hire more people not lay people off Plus, more. See video link in reply. Bookmark & watch: _____ More on why Nvidia needed to "rip the band-aid" due to memory makers:

Nvidia's Jensen Huang on Fox Business: * Asked for a single word on the rest of the year, Huang says "demand accelerating" * Says the reason is AI does productive work and the tokens labs generate are "profitable tokens," so what's holding it back now is just compute. * Next year is already sold out and supply-constrained at 70% growth. * "Every single [chip] that we can make has already been sold." * Customers commit a year-plus ahead because "you're not buying a computer, you're building a factory," at $50-60 billion each. * With memory prices way up, Nvidia reset margin guidance this quarter to "rip the band-aid off." * Margins fall from 75% to 72 - 73% next year after absorbing memory cost increases and repricing, to clear what he called "a cloud on our stock." * Next year's Vera Rubin will ramp even faster than Blackwell did, which Huang calls "the fastest product launch we've ever had in history." * Bottlenecks "literally everywhere," the biggest buildout in history. * Constraints span TSMC CoWoS packaging, wafers, memory, networking, silicon photonics, power generation, and "high-quality land that's powered," plus a skilled-labor shortage in the US * Says scarcity is not a bad thing. This quarter's 100% growth and next year's 70% are both supply-constrained, which can be healthy because it "causes the best technologies to emerge and rise" and makes everybody sharper. * AWS alone is set to add 2 million GPUs across 2027 and 2028. Half of revenue comes from about six hyperscalers, much of it rented onward to "Nvidia developers all over the world" * Says on hyperscalers, the Nvidia platform is "the most rentable" and "captures the highest pricing" of anything hyperscalers own. * After Bill Gates suggested taxing tokens over AI job losses, Huang says: "I see things very differently than he does." * Argues AI is "a net job creator at a scale that we've never seen" because productive companies hire more people not lay people off Plus, more. See video link in reply. Bookmark & watch: _____ More on why Nvidia needed to "rip the band-aid" due to memory makers:

Fireside Alpha

13,018 次观看 • 4 天前