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Fiscal.ai
Nvidia just crushed Q3 estimates
Data Center Revenue +66%
Gaming Revenue +30%
Professional Visualization +56%
Automotive +32%
$NVDA: +4.1% after hours https://t.co/Bis63PgBTz
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Nvidia just crushed Q3 estimates
Data Center Revenue +66%
Gaming Revenue +30%
Professional Visualization +56%
Automotive +32%
$NVDA: +4.1% after hours https://t.co/Bis63PgBTz
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Fiscal.ai
$4B to $110B in operating income in less than 3 years.
Absolutely outrageous growth.
$NVDA https://t.co/LbkHhnBylj
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$4B to $110B in operating income in less than 3 years.
Absolutely outrageous growth.
$NVDA https://t.co/LbkHhnBylj
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Fiscal.ai
RT @StockMKTNewz: Nvidia's $NVDA Data Center Business is now a $204.8 Billion annual run rate segment up from a $4B ARR segment in 2020 https://t.co/EoLokfbb7n
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RT @StockMKTNewz: Nvidia's $NVDA Data Center Business is now a $204.8 Billion annual run rate segment up from a $4B ARR segment in 2020 https://t.co/EoLokfbb7n
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Fiscal.ai
Nvidia v. AMD
Nvidia's Data Center business is now 11x larger than AMD's...
And it's growing 3x faster 🤯
$NVDA $AMD https://t.co/E9YPc26E4E
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Nvidia v. AMD
Nvidia's Data Center business is now 11x larger than AMD's...
And it's growing 3x faster 🤯
$NVDA $AMD https://t.co/E9YPc26E4E
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Fiscal.ai
This is what happens when you're the fastest fundamental data provider in the world. ⚡️⚡️
Soooo many Fiscal AI charts after earnings! https://t.co/TGliCIfcvB
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This is what happens when you're the fastest fundamental data provider in the world. ⚡️⚡️
Soooo many Fiscal AI charts after earnings! https://t.co/TGliCIfcvB
is @fiscal_ai the only platform in the world that already has all of Nvidia's financials? https://t.co/1pRpElwgXn tweet
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Fiscal.ai
Nvidia CFO:
"On our balance sheet, inventory grew 32% QoQ while supply commitments increased 63% sequentially. We are preparing for significant growth ahead"
$NVDA https://t.co/oXLBgXPTII
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Nvidia CFO:
"On our balance sheet, inventory grew 32% QoQ while supply commitments increased 63% sequentially. We are preparing for significant growth ahead"
$NVDA https://t.co/oXLBgXPTII
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Dimitry Nakhla | Babylon Capital®
RT @TheShortBear: $GOOGL first to $5T market cap?
Gemini 3 just dropped and I believe it opened the path for Google to become the most valuable company in the world.
The biggest factor of the release was seeing that Gemini 3 success wasn't based on NVDA chips but on their own TPUs.
Google's development of the Tensor Processing Unit (TPU) is the strategic, long-term weapon designed to dismantle the current, high-cost dominance of general-purpose GPUs and position GOOGL as the indispensable, cost-advantaged infrastructure layer for the global AI revolution.
The core of this thesis is a calculated power play:
Shifting the economic center of gravity from $NVDA high-margin, general-purpose silicon to specialized, high-efficiency, proprietary ASICs.
The $GOOGL Full-Stack Advantage: Cost-Control and Commercialization, as per an ex employee:
The Superior Unit Economics of Inference
The world is shifting from costly AI model training to massive, repetitive, and daily inference (running the models across billions of user queries in Search, Ads, and Gemini).
TPUs, which are purpose-built for the tensor operations that define AI, offer significantly better performance per dollar and energy efficiency, a key metric for a hyperscaler.
For internal use (Gemini, Search, etc.), this drives down $GOOGL's largest and fastest-growing CapEx cost, translating directly into higher operating margins for the Google Services and Cloud segments.
A Commercial Challenge to the Ecosystem
The plan is to move beyond the Google Cloud "walled garden" and begin selling TPU capacity externally to other hosters, essentially following the $NVDA playbook. This means the TPU, currently the "closest alternative" to an $NVDA GPU, will be introduced as a viable competitor.
The recent deal with Anthropic to use up to one million TPUs confirms the enterprise-level maturity and ambition of this strategy, driven by the TPU's compelling cost-performance ratio.
While $NVDA's developer ecosystem (CUDA) remains a strong lock-in, the generational improvements in TPUs are reportedly significantly larger than the jumps seen in new GPUs.
Thesis: Consolidating AI Money
Monetization Synergy
$GOOGL's revenue is currently divided into Ad Money, Cloud Money, and AI Money.
By controlling the underlying hardware (TPU) that powers all three segments, $GOOGL effectively consolidates the "AI Money" flowing into its system, turning its own immense AI compute consumption from a cost center into a proprietary competitive moat.
$GOOGL can price its cloud AI services more aggressively because its internal cost of goods sold (COGS) for compute is lower than rivals reliant on third-party silicon.
This competitive wedge accelerates Google Cloud's growth and, critically, expands its operating margin, providing structural long-term leverage.
RESULT
Google ends up taking a large chunk of AWS, Azure and NVDA earnings as an all in one platform to develop, train and host the next generation of AI.
Google cloud will become the place to run it all.
On top, the new release of Gemini makes sure they win the Browser market which will run on the superior models.
All of this will be done at a lower cost then the competition, both through the lower cost AI itself but also through the own manufactured TPU and infrastructure.
GOOGL becomes the absolute kind, both for retail as a consumer product but also on the backend where everyone will be building. All of this coming at a massive advantage to Search.
Unreal turn of events after 1-1.5years of doubt by the street. GOOGL kept on telling us that their efforts in AI were strong and rooted in investments made a decade ago...
The market doubted them but it will likely make them the first 5T company.
Perhaps that is what Berkshire saw.
tweet
RT @TheShortBear: $GOOGL first to $5T market cap?
Gemini 3 just dropped and I believe it opened the path for Google to become the most valuable company in the world.
The biggest factor of the release was seeing that Gemini 3 success wasn't based on NVDA chips but on their own TPUs.
Google's development of the Tensor Processing Unit (TPU) is the strategic, long-term weapon designed to dismantle the current, high-cost dominance of general-purpose GPUs and position GOOGL as the indispensable, cost-advantaged infrastructure layer for the global AI revolution.
The core of this thesis is a calculated power play:
Shifting the economic center of gravity from $NVDA high-margin, general-purpose silicon to specialized, high-efficiency, proprietary ASICs.
The $GOOGL Full-Stack Advantage: Cost-Control and Commercialization, as per an ex employee:
The Superior Unit Economics of Inference
The world is shifting from costly AI model training to massive, repetitive, and daily inference (running the models across billions of user queries in Search, Ads, and Gemini).
TPUs, which are purpose-built for the tensor operations that define AI, offer significantly better performance per dollar and energy efficiency, a key metric for a hyperscaler.
For internal use (Gemini, Search, etc.), this drives down $GOOGL's largest and fastest-growing CapEx cost, translating directly into higher operating margins for the Google Services and Cloud segments.
A Commercial Challenge to the Ecosystem
The plan is to move beyond the Google Cloud "walled garden" and begin selling TPU capacity externally to other hosters, essentially following the $NVDA playbook. This means the TPU, currently the "closest alternative" to an $NVDA GPU, will be introduced as a viable competitor.
The recent deal with Anthropic to use up to one million TPUs confirms the enterprise-level maturity and ambition of this strategy, driven by the TPU's compelling cost-performance ratio.
While $NVDA's developer ecosystem (CUDA) remains a strong lock-in, the generational improvements in TPUs are reportedly significantly larger than the jumps seen in new GPUs.
Thesis: Consolidating AI Money
Monetization Synergy
$GOOGL's revenue is currently divided into Ad Money, Cloud Money, and AI Money.
By controlling the underlying hardware (TPU) that powers all three segments, $GOOGL effectively consolidates the "AI Money" flowing into its system, turning its own immense AI compute consumption from a cost center into a proprietary competitive moat.
$GOOGL can price its cloud AI services more aggressively because its internal cost of goods sold (COGS) for compute is lower than rivals reliant on third-party silicon.
This competitive wedge accelerates Google Cloud's growth and, critically, expands its operating margin, providing structural long-term leverage.
RESULT
Google ends up taking a large chunk of AWS, Azure and NVDA earnings as an all in one platform to develop, train and host the next generation of AI.
Google cloud will become the place to run it all.
On top, the new release of Gemini makes sure they win the Browser market which will run on the superior models.
All of this will be done at a lower cost then the competition, both through the lower cost AI itself but also through the own manufactured TPU and infrastructure.
GOOGL becomes the absolute kind, both for retail as a consumer product but also on the backend where everyone will be building. All of this coming at a massive advantage to Search.
Unreal turn of events after 1-1.5years of doubt by the street. GOOGL kept on telling us that their efforts in AI were strong and rooted in investments made a decade ago...
The market doubted them but it will likely make them the first 5T company.
Perhaps that is what Berkshire saw.
tweet