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I think the $ORCL earnings has two truths at the same time. The first truth is that Oracle’s AI demand is real, massive and still accelerating but the second truth is that Oracle’s AI demand is expensive to deliver which meansthe stock now comes down to capex, financing, margins... show more

Shay Boloor

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134,760 Aufrufe • vor 4 Monaten •via X (Twitter)

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$ORCL is early to one of the largest AI infrastructure buildouts in the world. If OCI keeps growing near these rates, cloud growth accelerates above 50% and customer prepayments reduce the funding burden then this selloff may eventually look like the painful funding phase before the harvest phase. Oracle now has to prove that massive AI demand can become massive shareholder value without too much dilution.

$ORCL is early to one of the largest AI infrastructure buildouts in the world. If OCI keeps growing near these rates, cloud growth accelerates above 50% and customer prepayments reduce the funding burden then this selloff may eventually look like the painful funding phase before the harvest phase. Oracle now has to prove that massive AI demand can become massive shareholder value without too much dilution.

Shay Boloor

69,765 Aufrufe • vor 4 Monaten

The AI bubble argument has the causality backwards. Cerebras CEO Andrew Feldman was in the 1990s fiber optic wave. He knows what a bubble looks like. In fiber, supply was built ahead of demand - companies bet on a future that hadn't arrived. AI infrastructure is the opposite: data centers can't be built fast enough to meet demand that is already here. Cerebras has $25B in backlog. NVIDIA has a backlog. AMD has a backlog. That is not a bubble. That is a queue. If you are short AI infrastructure on bubble thesis, Feldman's framing is the counter-argument you need to engage with. Feldman's full structural argument - including the fiber optic and railroad comparisons:

The AI bubble argument has the causality backwards. Cerebras CEO Andrew Feldman was in the 1990s fiber optic wave. He knows what a bubble looks like. In fiber, supply was built ahead of demand - companies bet on a future that hadn't arrived. AI infrastructure is the opposite: data centers can't be built fast enough to meet demand that is already here. Cerebras has $25B in backlog. NVIDIA has a backlog. AMD has a backlog. That is not a bubble. That is a queue. If you are short AI infrastructure on bubble thesis, Feldman's framing is the counter-argument you need to engage with. Feldman's full structural argument - including the fiber optic and railroad comparisons:

Podcast Alpha

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CEO of AWS, Matt Garman, on Amazon's CapEx spend: "The capex expense needed to deploy all of the compute everyone needs right now is massive. Our capex is $220 billion for 26. It's the largest expense we've ever had, maybe any company has ever had in a single year. We don't anticipate slowing down anytime soon because the demand is massive." Via a16z $GOOGL $MSFT $META $ORCL $AMZN

CEO of AWS, Matt Garman, on Amazon's CapEx spend: "The capex expense needed to deploy all of the compute everyone needs right now is massive. Our capex is $220 billion for 26. It's the largest expense we've ever had, maybe any company has ever had in a single year. We don't anticipate slowing down anytime soon because the demand is massive." Via a16z $GOOGL $MSFT $META $ORCL $AMZN

P Equity Research 📰

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$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.

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AI is evolving FAST. From agentic AI to physical AI, one thing remains the same: it needs data to grow. Nodepay is building the infrastructure that feeds AI with the intelligence it needs. The demand is massive—the opportunity is even bigger. 🎥👇

AI is evolving FAST. From agentic AI to physical AI, one thing remains the same: it needs data to grow. Nodepay is building the infrastructure that feeds AI with the intelligence it needs. The demand is massive—the opportunity is even bigger. 🎥👇

Nodepay

78,835 Aufrufe • vor 1 Jahr

$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.

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261,814 Aufrufe • vor 4 Monaten

Jon says the Venice daily token chart is the best chart in crypto, and I can see why. - Token demand is the foundation of AI - Venice's daily token demand growth is accelerating - $VVV is the only asset in crypto that provides exposure to AI token demand The entire AI boom rides on the back of increasing demand for tokens. So long as this curve is accelerating up, I remain irrationally bullish on $VVV

Jon says the Venice daily token chart is the best chart in crypto, and I can see why. - Token demand is the foundation of AI - Venice's daily token demand growth is accelerating - $VVV is the only asset in crypto that provides exposure to AI token demand The entire AI boom rides on the back of increasing demand for tokens. So long as this curve is accelerating up, I remain irrationally bullish on $VVV

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Jensen Huang says $NVDA has “the largest supply chain in the world” but AI demand is still outstripping global capacity. The bottleneck is memory, compute, power and the physical buildout required to turn AI demand into usable capacity.

Jensen Huang says $NVDA has “the largest supply chain in the world” but AI demand is still outstripping global capacity. The bottleneck is memory, compute, power and the physical buildout required to turn AI demand into usable capacity.

Shay Boloor

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CHARLES SCHWAB DIRECTOR OF EQUITY RESEARCH ON WHY BITCOIN IS LAGGING RIGHT NOW: "Bitcoin is a hedge against uncertainty. And I think the market right now is very certain about one thing: AI will absorb the next decade of capital, earnings growth, power demand, semiconductor demand, everything. And so the attention is shifting there." That is the whole explanation in two sentences. Bitcoin thrives when the future is unclear. Right now the market thinks it knows exactly what the next decade looks like. AI wins. Everything else waits. The moment that certainty cracks, Bitcoin is the first place uncertain capital runs. Uncertainty is not gone. It is just temporarily overshadowed.

CHARLES SCHWAB DIRECTOR OF EQUITY RESEARCH ON WHY BITCOIN IS LAGGING RIGHT NOW: "Bitcoin is a hedge against uncertainty. And I think the market right now is very certain about one thing: AI will absorb the next decade of capital, earnings growth, power demand, semiconductor demand, everything. And so the attention is shifting there." That is the whole explanation in two sentences. Bitcoin thrives when the future is unclear. Right now the market thinks it knows exactly what the next decade looks like. AI wins. Everything else waits. The moment that certainty cracks, Bitcoin is the first place uncertain capital runs. Uncertainty is not gone. It is just temporarily overshadowed.

WOLF Bitcoin

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Since the dawn of time, voice has been our most natural way to communicate. For decades, our interaction with tech went analog - screens, keyboards, clicks. That era is ending. The future is voice-first, again. The opportunity is massive and Silencio is powering AI & robotics to talk & listen as naturally as humans do.

Since the dawn of time, voice has been our most natural way to communicate. For decades, our interaction with tech went analog - screens, keyboards, clicks. That era is ending. The future is voice-first, again. The opportunity is massive and Silencio is powering AI & robotics to talk & listen as naturally as humans do.

Silencio | Voice Data for AI

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Enterprise AI has moved beyond choosing the right model or GPU. The challenge is operationalizing it across the organization. Oracle’s Karan joined David Nicholson and Matthew Kimball at The Six Five Summit to explore the infrastructure required to move AI into production. Watch on demand:

Enterprise AI has moved beyond choosing the right model or GPU. The challenge is operationalizing it across the organization. Oracle’s Karan joined David Nicholson and Matthew Kimball at The Six Five Summit to explore the infrastructure required to move AI into production. Watch on demand:

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The reason $PLTR has pulled back this year is that it has gone from being viewed as THE AI application winner to AN AI application winner which is a one-letter shift that has completely changed how the market values the stock. At its peak, investors paid nearly 200x earnings because Palantir appeared to be the only public software company clearly converting AI demand into accelerating fundamentals. That multiple has since compressed toward 80x as $SNOW, $DDOG, $MSFT and Databricks prove enterprise AI will have multiple winners.

The reason $PLTR has pulled back this year is that it has gone from being viewed as THE AI application winner to AN AI application winner which is a one-letter shift that has completely changed how the market values the stock. At its peak, investors paid nearly 200x earnings because Palantir appeared to be the only public software company clearly converting AI demand into accelerating fundamentals. That multiple has since compressed toward 80x as $SNOW, $DDOG, $MSFT and Databricks prove enterprise AI will have multiple winners.

Shay Boloor

75,400 Aufrufe • vor 2 Monaten

Lisa Su just dropped a massive reality check on the state of the AI hardware scramble, and the sheer scale of what is coming is wild. If you asked her six months ago, demand was just "strong." But now? The entire landscape has shifted into absolute overdrive. She specifically noted that in the last 60 to 90 days, there has been a massive acceleration, especially when looking at the forecasts and demand patterns for 2026. The most insane takeaway is her blunt assessment that "there's not enough compute out there for everything that wants to be done." It is a complete bottleneck of global ambition versus available silicon. What is really flying under the radar here is that this isn't exclusively a GPU story anymore. The desire to ramp compute quickly for heavy AI enterprise workloads is actively pulling massive CPU content right along with it. The demand is practically insatiable across the entire board. The heavyweights are scrambling, the trenches are fighting for allocation, and the hardware supercycle is officially accelerating to a whole new level.

Lisa Su just dropped a massive reality check on the state of the AI hardware scramble, and the sheer scale of what is coming is wild. If you asked her six months ago, demand was just "strong." But now? The entire landscape has shifted into absolute overdrive. She specifically noted that in the last 60 to 90 days, there has been a massive acceleration, especially when looking at the forecasts and demand patterns for 2026. The most insane takeaway is her blunt assessment that "there's not enough compute out there for everything that wants to be done." It is a complete bottleneck of global ambition versus available silicon. What is really flying under the radar here is that this isn't exclusively a GPU story anymore. The desire to ramp compute quickly for heavy AI enterprise workloads is actively pulling massive CPU content right along with it. The demand is practically insatiable across the entire board. The heavyweights are scrambling, the trenches are fighting for allocation, and the hardware supercycle is officially accelerating to a whole new level.

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100,831 Aufrufe • vor 6 Monaten

Dan Ives Dan Ives just admitted he was "dead wrong" on $ORCL. Gil Luria called the top. Now Luria is the one saying look again. Oracle ran 200 to 330 on a single OpenAI backlog deal, then round-tripped to 140. The market now values the entire ~$630B compute backlog at zero. But OpenAI raised $122B, the largest raise ever, and narrowed to compute, so those bills are payable. Zero starts to look wrong the other way. Jim Chanos James Chanos, on Risk Reversal back on Jul 17, called the AI-compute backlog a mirage. This is the direct bet against that. The read - at a zero backlog, any conversion at all is upside. The risk sits with OpenAI's commitments, not Oracle's execution. Full exchange:

Dan Ives Dan Ives just admitted he was "dead wrong" on $ORCL. Gil Luria called the top. Now Luria is the one saying look again. Oracle ran 200 to 330 on a single OpenAI backlog deal, then round-tripped to 140. The market now values the entire ~$630B compute backlog at zero. But OpenAI raised $122B, the largest raise ever, and narrowed to compute, so those bills are payable. Zero starts to look wrong the other way. Jim Chanos James Chanos, on Risk Reversal back on Jul 17, called the AI-compute backlog a mirage. This is the direct bet against that. The read - at a zero backlog, any conversion at all is upside. The risk sits with OpenAI's commitments, not Oracle's execution. Full exchange:

Podcast Alpha

99,141 Aufrufe • vor 2 Monaten

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!

Milk Road AI

14,578 Aufrufe • vor 3 Monaten

🎥WATCH: FED MINUTES SHOW AI DEMAND IS NOW AN INFLATION RISK The AI boom is now an official inflation concern for the Fed. "Participants judged that the risks to the inflation outlook were tilted to the upside," with AI demand pushing upward pressure on tech and electricity prices. Some officials also noted AI could eventually reduce costs through productivity gains, but "that effect would likely take time to materialize."

🎥WATCH: FED MINUTES SHOW AI DEMAND IS NOW AN INFLATION RISK The AI boom is now an official inflation concern for the Fed. "Participants judged that the risks to the inflation outlook were tilted to the upside," with AI demand pushing upward pressure on tech and electricity prices. Some officials also noted AI could eventually reduce costs through productivity gains, but "that effect would likely take time to materialize."

Coin Bureau

44,513 Aufrufe • vor 3 Monaten

Some have lost a lot of money betting against Elon and $TSLA. I’m not long a car company, I’m long Elon Musk. The car business is slowing, but the stock is still a bet on the future with robotaxis, AI, and Elon Musk's vision. At ~200x forward earnings, Elon has to make the case to investors. Varney & Co.

Some have lost a lot of money betting against Elon and $TSLA. I’m not long a car company, I’m long Elon Musk. The car business is slowing, but the stock is still a bet on the future with robotaxis, AI, and Elon Musk's vision. At ~200x forward earnings, Elon has to make the case to investors. Varney & Co.

David Nicholas

15,920 Aufrufe • vor 8 Monaten

$MU is the only company right now fully positioned for the memory centric AI cycle. This will, without question, be one of the largest markets over the next 5 years high bandwidth memory, advanced packaging, and AI server demand are structurally exploding. And the market still hasn’t fully priced this in. $DELL is simultaneously capturing the AI infrastructure build out from servers to enterprise deployment with multi year visibility and backlog strength that most investors are still underestimating. I’ll be going down a rabbit hole on both MU and DELL this long weekend.

$MU is the only company right now fully positioned for the memory centric AI cycle. This will, without question, be one of the largest markets over the next 5 years high bandwidth memory, advanced packaging, and AI server demand are structurally exploding. And the market still hasn’t fully priced this in. $DELL is simultaneously capturing the AI infrastructure build out from servers to enterprise deployment with multi year visibility and backlog strength that most investors are still underestimating. I’ll be going down a rabbit hole on both MU and DELL this long weekend.

Bill Brooklyn

23,185 Aufrufe • vor 1 Monat

$NVDA has the “lowest cost per token in the world” which is really a claim about owning the economics of inference. The company that delivers the most tokens per watt, per rack and per dollar is the one that captures the most demand and the best margins as AI scales.

$NVDA has the “lowest cost per token in the world” which is really a claim about owning the economics of inference. The company that delivers the most tokens per watt, per rack and per dollar is the one that captures the most demand and the best margins as AI scales.

Shay Boloor

48,594 Aufrufe • vor 6 Monaten