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Every major AI lab is spending billions on compute, and virtually all of it flows through Nvidia. The Blackwell architecture is sold out through 2027, margins are above 75%, and the data center segment alone is growing faster than most entire companies. I keep hearing that $NVDA is "priced... show more

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Wait. $NVDA CEO Jensen Huang is talking about $3T in annual revenue. 60% margins = $1.8T profit. Nvidia’s market cap = ~$5T. That’s less than 3x earnings. Nvidia is either absurdly cheap today. Or the entire AI thesis is wrong. Which is it?

Wait. $NVDA CEO Jensen Huang is talking about $3T in annual revenue. 60% margins = $1.8T profit. Nvidia’s market cap = ~$5T. That’s less than 3x earnings. Nvidia is either absurdly cheap today. Or the entire AI thesis is wrong. Which is it?

Noah

73,772 Aufrufe • vor 3 Monaten

$NVDA networking is now running at a $60B+ annualized pace, growing ~200% YoY and nearly the size of $AVGO total 2025 revenue. As AI clusters scale, the bottleneck becomes how fast GPUs, CPUs, memory and storage move data together because even the best chips underperform if the network cannot keep up. This is why Nvidia is selling the full AI factory stack.

$NVDA networking is now running at a $60B+ annualized pace, growing ~200% YoY and nearly the size of $AVGO total 2025 revenue. As AI clusters scale, the bottleneck becomes how fast GPUs, CPUs, memory and storage move data together because even the best chips underperform if the network cannot keep up. This is why Nvidia is selling the full AI factory stack.

Shay Boloor

61,104 Aufrufe • vor 3 Monaten

Sergey Brin said compute is dessert. The companies winning the AI race right now are not the ones with the most chips. They are the ones with the best algorithms. Every headline you read about AI is about data centers, Megawatts, and Nvidia orders. Billions in infrastructure and more. The entire investment thesis of the last three years has been built on compute scaling as the primary moat. Sergey thinks that framing is wrong. He pulled out an example from physics. The N-body problem. Scientists have been running those simulations since the fifties. Over the decades, raw compute improved on Moore's law. But the algorithms to solve the problem improved faster. Not slightly faster. Far faster. The algorithmic gains made the compute gains look small. He says the same thing has happened in AI over the last decade. Compute is not the meal. It is the dessert. You still want it. Nobody is turning down frontier compute. But the companies that figured out the algorithms first are the ones actually ahead. The market is pricing AI winners by who has the most chips. Sergey Brin just said that is the wrong scorecard. The ones who win this are not building the biggest data center. They are solving the harder math problem.

Sergey Brin said compute is dessert. The companies winning the AI race right now are not the ones with the most chips. They are the ones with the best algorithms. Every headline you read about AI is about data centers, Megawatts, and Nvidia orders. Billions in infrastructure and more. The entire investment thesis of the last three years has been built on compute scaling as the primary moat. Sergey thinks that framing is wrong. He pulled out an example from physics. The N-body problem. Scientists have been running those simulations since the fifties. Over the decades, raw compute improved on Moore's law. But the algorithms to solve the problem improved faster. Not slightly faster. Far faster. The algorithmic gains made the compute gains look small. He says the same thing has happened in AI over the last decade. Compute is not the meal. It is the dessert. You still want it. Nobody is turning down frontier compute. But the companies that figured out the algorithms first are the ones actually ahead. The market is pricing AI winners by who has the most chips. Sergey Brin just said that is the wrong scorecard. The ones who win this are not building the biggest data center. They are solving the harder math problem.

Ihtesham Ali

130,330 Aufrufe • vor 3 Monaten

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

103,768 Aufrufe • vor 21 Tagen

$NVDA This is what you are buying when you buy a share of Nvidia... I heard this today and could not stop thinking about it. Jensen describes the sophistication that is required in designing chips, creating them, delivering them to customers, installing them in datacenters, and more. He argues that there has not been a company since $IBM that was faced with this much technology and investment in order to push the entire world forward with demand that is spanning throughout the globe in EVERY single industry. The stock trades at 27 times forward earnings. Costco and Walmart, amazing companies, are both more expensive than the name that is fueling the AI revolution and brings home 55 cents on every dollar of revenue as net income. This has been my main Mag 7 pick for the year in terms of establishing exposure to big tech and it's just getting harder to imagine a world in which AI matters but $NVDA is not more valuable than it is today.

$NVDA This is what you are buying when you buy a share of Nvidia... I heard this today and could not stop thinking about it. Jensen describes the sophistication that is required in designing chips, creating them, delivering them to customers, installing them in datacenters, and more. He argues that there has not been a company since $IBM that was faced with this much technology and investment in order to push the entire world forward with demand that is spanning throughout the globe in EVERY single industry. The stock trades at 27 times forward earnings. Costco and Walmart, amazing companies, are both more expensive than the name that is fueling the AI revolution and brings home 55 cents on every dollar of revenue as net income. This has been my main Mag 7 pick for the year in terms of establishing exposure to big tech and it's just getting harder to imagine a world in which AI matters but $NVDA is not more valuable than it is today.

amit

277,134 Aufrufe • vor 1 Jahr

Earnings this week isn't important for just $NVDA … but the entire market. 🚨 $NVDA is in a macro bull cycle and my long‑term model is targeting $220 in the next 90 days. In this video I break down the setup, my profit targets, and the exact conditions that flip me bearish.

Earnings this week isn't important for just $NVDA … but the entire market. 🚨 $NVDA is in a macro bull cycle and my long‑term model is targeting $220 in the next 90 days. In this video I break down the setup, my profit targets, and the exact conditions that flip me bearish.

Peter DiCarlo

54,640 Aufrufe • vor 6 Monaten

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud

John Furrier

47,663 Aufrufe • vor 1 Monat

Peter Diamandis: SpaceX has the potential to become the world’s first $10 trillion company “Well, if anybody can do it, Elon can. I think this has the potential to really be the first $10 trillion company out there and growing. He’s building civilizational-level infrastructure. The challenge is, I don’t think the market knows how to value this company. It’s not a company, it’s really four different businesses wrapped into one vertical, and you have to look at each individually. “The first business is global communications with Starlink. Starlink is going to deliver global gigabit connectivity to the entire planet, billions of individuals. They’re just making a dent right now. Then they’re going direct satellite-to-cell phone. As Gwynne said on the earnings call yesterday, that’s a $600 billion level of revenue potential, and they expect to take a chunk of that. “The second business is delivering AI compute. They’ve already signed up $20 billion in annualized revenue, and they’re building faster than anybody else. They announced two gigawatts of compute by the end of this year and are shooting for upwards of 10 gigawatts next year… Elon said they’re launching their first AI satellites in partnership with Nvidia in 2027, much faster than anybody thought.”

Peter Diamandis: SpaceX has the potential to become the world’s first $10 trillion company “Well, if anybody can do it, Elon can. I think this has the potential to really be the first $10 trillion company out there and growing. He’s building civilizational-level infrastructure. The challenge is, I don’t think the market knows how to value this company. It’s not a company, it’s really four different businesses wrapped into one vertical, and you have to look at each individually. “The first business is global communications with Starlink. Starlink is going to deliver global gigabit connectivity to the entire planet, billions of individuals. They’re just making a dent right now. Then they’re going direct satellite-to-cell phone. As Gwynne said on the earnings call yesterday, that’s a $600 billion level of revenue potential, and they expect to take a chunk of that. “The second business is delivering AI compute. They’ve already signed up $20 billion in annualized revenue, and they’re building faster than anybody else. They announced two gigawatts of compute by the end of this year and are shooting for upwards of 10 gigawatts next year… Elon said they’re launching their first AI satellites in partnership with Nvidia in 2027, much faster than anybody thought.”

DogeDesigner

47,675 Aufrufe • vor 1 Monat

$AMD CEO Lisa Su said at CES 2026 that the world may need 100x more compute over the next five years as AI workloads scale across industries. This earnings cycle is proving the point: • $AMZN AWS reaccelerated to 28% (fastest growth in 15 quarters) while Bedrock customer spend grew 170% QoQ & processed more tokens in Q1 than all prior years combined • $MSFT AI business is now at a $37B run-rate growing 123% YoY • $GOOGL Cloud grew 63% (now nearly half the size of AWS) & has a $243B backlog while GenAI products grew 800% YoY • $MU & $SNDK margins show memory demand is still compounding WAY faster than supply with margins now higher than many software companies The 100x compute framework looks less crazy after this earnings cycle.

$AMD CEO Lisa Su said at CES 2026 that the world may need 100x more compute over the next five years as AI workloads scale across industries. This earnings cycle is proving the point: • $AMZN AWS reaccelerated to 28% (fastest growth in 15 quarters) while Bedrock customer spend grew 170% QoQ & processed more tokens in Q1 than all prior years combined • $MSFT AI business is now at a $37B run-rate growing 123% YoY • $GOOGL Cloud grew 63% (now nearly half the size of AWS) & has a $243B backlog while GenAI products grew 800% YoY • $MU & $SNDK margins show memory demand is still compounding WAY faster than supply with margins now higher than many software companies The 100x compute framework looks less crazy after this earnings cycle.

Shay Boloor

174,441 Aufrufe • vor 4 Monaten

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.

Milk Road AI

419,755 Aufrufe • vor 4 Monaten

Every AI model needs somewhere to run. Compute. Power. Data centres. That's the bottleneck now, not the software. Canada is putting billions on the table through 2030 to secure sovereign AI capacity. HIVE Digital Technologies is building that infrastructure now, ahead of the funding curve. Why investors are watching: - Sovereign AI compute infrastructure, live in Canada - Data centres, GPU capacity, and power, already in motion - Dual-engine business model generating revenue while expanding AI infrastructure - Sitting at the intersection of AI, energy, and infrastructure - Exposure to one of tech's fastest-growing long-term trends Railroads built the industrial economy. The internet built the information economy. AI infrastructure is building this one. Every company will use AI. Fewer will own what it runs on. Learn More:

Every AI model needs somewhere to run. Compute. Power. Data centres. That's the bottleneck now, not the software. Canada is putting billions on the table through 2030 to secure sovereign AI capacity. HIVE Digital Technologies is building that infrastructure now, ahead of the funding curve. Why investors are watching: - Sovereign AI compute infrastructure, live in Canada - Data centres, GPU capacity, and power, already in motion - Dual-engine business model generating revenue while expanding AI infrastructure - Sitting at the intersection of AI, energy, and infrastructure - Exposure to one of tech's fastest-growing long-term trends Railroads built the industrial economy. The internet built the information economy. AI infrastructure is building this one. Every company will use AI. Fewer will own what it runs on. Learn More:

BTV & CEO Clips

24,998 Aufrufe • vor 1 Monat

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

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

Herbert Ong

24,496 Aufrufe • vor 1 Monat

$NBIS is up nearly 30% because this quarter showed the AI compute shortage is translating into better pricing, faster paybacks, higher margins and better financing. Nebius now earns ~$25M per MW on normal contracts and up to $50M for immediate capacity while Q2 deals pay back in under two years and customers fund roughly half the capex upfront. That pricing power is already showing up in the market with its first capacity auction clearing 15% above prior $NVDA Blackwell pricing, AI cloud margins reaching 50% and management saying it could sell all of 2027 capacity today.

$NBIS is up nearly 30% because this quarter showed the AI compute shortage is translating into better pricing, faster paybacks, higher margins and better financing. Nebius now earns ~$25M per MW on normal contracts and up to $50M for immediate capacity while Q2 deals pay back in under two years and customers fund roughly half the capex upfront. That pricing power is already showing up in the market with its first capacity auction clearing 15% above prior $NVDA Blackwell pricing, AI cloud margins reaching 50% and management saying it could sell all of 2027 capacity today.

Shay Boloor

161,621 Aufrufe • vor 1 Monat

🚨 BREAKING: TECH COMPANIES ARE STRAIGHT FALSIFICATING EARNINGS Microsoft just gave OpenAI $13 BILLION OpenAI invested it back to Azure Microsoft booked it as revenue OpenAI booked it as a revenue too Amazon and Google are running similar loops with Anthropic while marking up huge paper gains from AI valuations Nvidia and Oracle don't even hide this scheme anymore OpenAI is spending over $60 BILLION a year on compute while generating only $25 BILLION in revenue. Ray Dalio, one of the most profitable investors in the world, has warned that late stage bubbles are driven by fake flows, not real economics He saw it before in 2000, 2008 Now he warns the same ponzi is happening at bigger scale That is exactly the definition of top of the market Keep in mind: I’ve called every major market top and bottom for over 10 YEARS I was one of the only people who called the top in October, and I’ll do it again That’s literally my job If you still haven’t followed me, you’ll regret

🚨 BREAKING: TECH COMPANIES ARE STRAIGHT FALSIFICATING EARNINGS Microsoft just gave OpenAI $13 BILLION OpenAI invested it back to Azure Microsoft booked it as revenue OpenAI booked it as a revenue too Amazon and Google are running similar loops with Anthropic while marking up huge paper gains from AI valuations Nvidia and Oracle don't even hide this scheme anymore OpenAI is spending over $60 BILLION a year on compute while generating only $25 BILLION in revenue. Ray Dalio, one of the most profitable investors in the world, has warned that late stage bubbles are driven by fake flows, not real economics He saw it before in 2000, 2008 Now he warns the same ponzi is happening at bigger scale That is exactly the definition of top of the market Keep in mind: I’ve called every major market top and bottom for over 10 YEARS I was one of the only people who called the top in October, and I’ll do it again That’s literally my job If you still haven’t followed me, you’ll regret

Hopper

18,271 Aufrufe • vor 2 Monaten

Nvidia continues to dominate the AI industry with record earnings, explosive data center growth, and massive demand for compute. But the bigger story is what’s happening globally behind the scenes. China is aggressively competing with the United States on AI infrastructure, power generation, and data center expansion and they don’t want to rely on American chips to do it. This is no longer just about stocks it’s a global race for AI dominance.

Nvidia continues to dominate the AI industry with record earnings, explosive data center growth, and massive demand for compute. But the bigger story is what’s happening globally behind the scenes. China is aggressively competing with the United States on AI infrastructure, power generation, and data center expansion and they don’t want to rely on American chips to do it. This is no longer just about stocks it’s a global race for AI dominance.

Kevin O'Leary aka Mr. Wonderful

12,462 Aufrufe • vor 3 Monaten

🚨 THE AI TRADE JUST BROKE. Nasdaq 100 is down 10% from its record. Chips just closed lower four sessions in a row. The moment it turned was July 16. TSMC posted the best quarter in its history. Profit up 77%. Revenue up 33.7%. Then it raised 2026 capex from $56B to $64B and added $100B in Arizona. The stock sold off anyway. Record earnings, and the market sold it. That is the regime change. Good numbers stopped mattering the moment capex started eating the cash flow. Look at what actually changed. The entire AI bull case rested on one assumption: inference gets cheaper. Spend now, scale later, margins explode when compute collapses in price. Here is what happened instead. Memory was 8% of hyperscaler capex in 2023. It is 30% in 2026. Analysts model 48% by 2027. DRAM prices more than doubled this year. LPDDR5 is up over 3x since early 2025. HBM stays short through 2027. Costs are not collapsing. They are compounding. And the market finally noticed the tell. TSMC beat on profit and revenue, then guided capex higher, and the stock sold off. Good earnings are now bearish, because every dollar of capex needs a dollar of return that nobody can show yet. Meanwhile the money still moves in a circle. Anthropic at $965B. OpenAI at $852B. Both funded by the same players buying the same chips. SpaceX down 32% in six weeks, and it is the largest listing in history. This is the same structure as 2000, with better branding. But 2000 did not go straight down either. Nasdaq rallied 40% twice before the real collapse. Both rallies destroyed the shorts who were right too early. That is the phase we are entering now, not the crash. One more squeeze into early 2027. Then the actual dump. I called the $15,768 bottom and the $126,162 top by waiting for exactly this pattern. I am not shorting into the bounce. I am waiting for it to exhaust. Follow and turn notifications on. I post the moment it does.

🚨 THE AI TRADE JUST BROKE. Nasdaq 100 is down 10% from its record. Chips just closed lower four sessions in a row. The moment it turned was July 16. TSMC posted the best quarter in its history. Profit up 77%. Revenue up 33.7%. Then it raised 2026 capex from $56B to $64B and added $100B in Arizona. The stock sold off anyway. Record earnings, and the market sold it. That is the regime change. Good numbers stopped mattering the moment capex started eating the cash flow. Look at what actually changed. The entire AI bull case rested on one assumption: inference gets cheaper. Spend now, scale later, margins explode when compute collapses in price. Here is what happened instead. Memory was 8% of hyperscaler capex in 2023. It is 30% in 2026. Analysts model 48% by 2027. DRAM prices more than doubled this year. LPDDR5 is up over 3x since early 2025. HBM stays short through 2027. Costs are not collapsing. They are compounding. And the market finally noticed the tell. TSMC beat on profit and revenue, then guided capex higher, and the stock sold off. Good earnings are now bearish, because every dollar of capex needs a dollar of return that nobody can show yet. Meanwhile the money still moves in a circle. Anthropic at $965B. OpenAI at $852B. Both funded by the same players buying the same chips. SpaceX down 32% in six weeks, and it is the largest listing in history. This is the same structure as 2000, with better branding. But 2000 did not go straight down either. Nasdaq rallied 40% twice before the real collapse. Both rallies destroyed the shorts who were right too early. That is the phase we are entering now, not the crash. One more squeeze into early 2027. Then the actual dump. I called the $15,768 bottom and the $126,162 top by waiting for exactly this pattern. I am not shorting into the bounce. I am waiting for it to exhaust. Follow and turn notifications on. I post the moment it does.

Nonzee

17,990 Aufrufe • vor 1 Monat

David Sacks just said what every honest analyst in Silicon Valley is already thinking (Save this). Nobody has ever seen anything like this. Anthropic has grown at 10x per year for three straight years and going into 2026, the conventional wisdom was that the rate of growth had to slow at this level of scale but then the numbers came in. Q1 alone is $10B ARR to $30B, in April, $30B to $44B and that's $96 million in new ARR added every single day. Inference margins are now above 70%, up from 38% last year and the only thing holding them back was compute. That's solved now, the SpaceX deal and others Anthropic has been quietly signing unlocks the supply side. This is exactly why we are bullish on Nebius and AMD. When a single company is adding nearly $100M in ARR per day, the real trade isn't the frontier lab but rather the infrastructure underneath it. Nebius, one of the fastest-growing neoclouds on the planet posted 547% YoY revenue growth in Q4 2025, exited the year with $1.25B ARR, and is guiding for $7–9B ARR by year-end 2026. Their revenue backlog has reached $46B, with projections of $16B in revenue by 2028 and NVIDIA locked in a $2 billion stock buy agreement with them giving Nebius early access to cutting-edge chips while every other cloud scrambles for supply. AMD is the other side of the same coin. Data center revenue hit $5.78B in Q1, up 57% year-over-year with total company revenue at $10.25B, up 38%. Meta has committed to deploying up to 6 gigawatts of AMD Instinct GPUs. Data center GPU revenue is forecast to surge 114% year over year to $15B in 2026. MI400-series chips hit the market in H2 and analysts project segment operating margins climbing to 31% as the next generation ramps. The model is simple, Anthropic is printing revenue and that that revenue pays for compute. That compute flows through companies like Nebius and AMD. This is why Milk Road PRO remains bullish on them and our positions are up massively. Our analysts have broken down the full thesis, the allocations, and the price targets. Go PRO at Milk Road to see everything, link below!

David Sacks just said what every honest analyst in Silicon Valley is already thinking (Save this). Nobody has ever seen anything like this. Anthropic has grown at 10x per year for three straight years and going into 2026, the conventional wisdom was that the rate of growth had to slow at this level of scale but then the numbers came in. Q1 alone is $10B ARR to $30B, in April, $30B to $44B and that's $96 million in new ARR added every single day. Inference margins are now above 70%, up from 38% last year and the only thing holding them back was compute. That's solved now, the SpaceX deal and others Anthropic has been quietly signing unlocks the supply side. This is exactly why we are bullish on Nebius and AMD. When a single company is adding nearly $100M in ARR per day, the real trade isn't the frontier lab but rather the infrastructure underneath it. Nebius, one of the fastest-growing neoclouds on the planet posted 547% YoY revenue growth in Q4 2025, exited the year with $1.25B ARR, and is guiding for $7–9B ARR by year-end 2026. Their revenue backlog has reached $46B, with projections of $16B in revenue by 2028 and NVIDIA locked in a $2 billion stock buy agreement with them giving Nebius early access to cutting-edge chips while every other cloud scrambles for supply. AMD is the other side of the same coin. Data center revenue hit $5.78B in Q1, up 57% year-over-year with total company revenue at $10.25B, up 38%. Meta has committed to deploying up to 6 gigawatts of AMD Instinct GPUs. Data center GPU revenue is forecast to surge 114% year over year to $15B in 2026. MI400-series chips hit the market in H2 and analysts project segment operating margins climbing to 31% as the next generation ramps. The model is simple, Anthropic is printing revenue and that that revenue pays for compute. That compute flows through companies like Nebius and AMD. This is why Milk Road PRO remains bullish on them and our positions are up massively. Our analysts have broken down the full thesis, the allocations, and the price targets. Go PRO at Milk Road to see everything, link below!

Milk Road AI

184,643 Aufrufe • vor 4 Monaten