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Peter Thiel: “AI chips will get commoditized.” Yes, the value in AI has largely accrued to the semiconductor level so far amd concentrated largely in $NVDA. But this is bound to change. In chips, you can stay as a monopoly only if you have an exclusive partnership with the...

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Oguz Erkan

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398,846 views • 2 months ago •via X (Twitter)

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$AMZN CEO: “Customers badly want better price/performance. This is why we build custom chips. ” If $AMZN chip business was a standalone company, it would be at $50 billion ARR. Let that sink in. It’ll only accelerate from here as bulk of the AI workloads shift to inference and inference itself becomes more agentic. This will not only result in cheaper inference for customers, but it’ll also expand AWS margins by 7-8% as Jassy said in the earnings call. Imagine where $AMZN valuation would be if AWS growth keeps above 20% for the next decade and net margin stays above 30% thanks to custom chips. Long $AMZN.
1:27

$AMZN CEO: “Customers badly want better price/performance. This is why we build custom chips. ” If $AMZN chip business was a standalone company, it would be at $50 billion ARR. Let that sink in. It’ll only accelerate from here as bulk of the AI workloads shift to inference and inference itself becomes more agentic. This will not only result in cheaper inference for customers, but it’ll also expand AWS margins by 7-8% as Jassy said in the earnings call. Imagine where $AMZN valuation would be if AWS growth keeps above 20% for the next decade and net margin stays above 30% thanks to custom chips. Long $AMZN.

Oguz Erkan

61,999 views • 1 month ago

$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?
0:20

$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?

Oguz Erkan

282,229 views • 2 months ago

No wonder Jensen got so defensive over $NVDA GPUs against custom chips. $GOOG will start using different custom chips for inference and training. $AMZN has already adopted this approach as they have Trainium for training and Inferentia for inference. Hyperscalers obviously see better price/performance in this approach, and this is where the industry is headed. $AVGO and $MRVL are poised to be big winners, while $NVDA dominance will be under increasing pressure.
3:25

No wonder Jensen got so defensive over $NVDA GPUs against custom chips. $GOOG will start using different custom chips for inference and training. $AMZN has already adopted this approach as they have Trainium for training and Inferentia for inference. Hyperscalers obviously see better price/performance in this approach, and this is where the industry is headed. $AVGO and $MRVL are poised to be big winners, while $NVDA dominance will be under increasing pressure.

Oguz Erkan

223,244 views • 2 months ago

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson
56:36

Dojo 2, Dojo 3 Chips and AI5 Chips Are Critical for Tesla and Battle for Future of AI. Tesla and XAI are buying about one million AI GPUs this year. This would be about 20% of the entire Nvidia production of B200/B300 chips that will be made in 2025. If XAI were to buy a mix of half Dojo 2/3 chips in 2025 and 2026 this could make them bigger than AMD. AMD is making about 400,000 AI GPU chips. Tesla will switch to AI5 chips for driving its cars but those chips will also act as inference chips with about 500 Teraflops of compute. Tesla could make 3-4 million AI5 chips in 2026. This would make Tesla the largest maker and user of AI inference chips in the world. Tesla could become the number 2 maker of AI training chips just by supplying a lot of those chips to XAI and Tesla internal use. Tesla is and will be the number one maker and user of AI inference chips. Sawyer Merritt Elon Musk Randy Kirk Herbert Ong Warren Redlich - Chasing Dreams 🇺🇸 Ale𝕏andra Merz 🇺🇲 Ray Emmet Peppers Bradford Ferguson

nextbigfuture

23,809 views • 1 year ago

$AMD will be a multi-trillion $ company. The AI accelerator TAM will exceed $1T by 2030, and the market will only keep growing. As Lisa Su says: “We’re in a market where you can think of computing as equating to intelligence. If you can get more intelligence, why wouldn’t you want more computing?” While big tech like $GOOGL with TPUs and $AMZN with Trainium are building their own ASICs, GPUs—especially $NVDA and $AMD —are expected to dominate, representing 70–75% of the AI accelerator market by the end of 2030.
0:48

$AMD will be a multi-trillion $ company. The AI accelerator TAM will exceed $1T by 2030, and the market will only keep growing. As Lisa Su says: “We’re in a market where you can think of computing as equating to intelligence. If you can get more intelligence, why wouldn’t you want more computing?” While big tech like $GOOGL with TPUs and $AMZN with Trainium are building their own ASICs, GPUs—especially $NVDA and $AMD —are expected to dominate, representing 70–75% of the AI accelerator market by the end of 2030.

Daniel

45,866 views • 6 months ago

“WE’LL HAVE A DEEP PARTNERSHIP WITH $NVDA FOR A LONG TIME,” SAYS $AMZN CEO ANDY JASSY But with inference demand exploding -- Amazon is doubling down on custom training chips to power the next wave of AI.
2:00

“WE’LL HAVE A DEEP PARTNERSHIP WITH $NVDA FOR A LONG TIME,” SAYS $AMZN CEO ANDY JASSY But with inference demand exploding -- Amazon is doubling down on custom training chips to power the next wave of AI.

Shay Boloor

80,266 views • 1 year ago

$NVDA CEO Jensen Huang said “buy $QCOM stock” while discussing edge AI and the need for AI chips inside smartphones. Qualcomm is positioned to benefit as more AI inference moves to devices.
0:57

$NVDA CEO Jensen Huang said “buy $QCOM stock” while discussing edge AI and the need for AI chips inside smartphones. Qualcomm is positioned to benefit as more AI inference moves to devices.

Shay Boloor

183,493 views • 19 days ago

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️
0:43

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. Amazon Web Services Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️

Amazon

27,151 views • 1 month ago

From “We will not allow China to develop AI using our chips” to “We cannot give the entire chip market to Huawei so it can fund further development to out compete US chips” This is how admitting defeat sounds like 🤣
0:53

From “We will not allow China to develop AI using our chips” to “We cannot give the entire chip market to Huawei so it can fund further development to out compete US chips” This is how admitting defeat sounds like 🤣

David Lee

129,989 views • 11 months ago

$AVGO helps hyperscalers build the custom chips and networking fabric needed to run massive AI systems. If $GOOGL, $META, OpenAI or Anthropic want to build their own inference chips then Broadcom is one of the first calls because it has the IP, packaging expertise and networking portfolio required to scale custom AI systems. Thats why Broadcom remains one of the strongest infrastructure positions in the AI economy.
1:00

$AVGO helps hyperscalers build the custom chips and networking fabric needed to run massive AI systems. If $GOOGL, $META, OpenAI or Anthropic want to build their own inference chips then Broadcom is one of the first calls because it has the IP, packaging expertise and networking portfolio required to scale custom AI systems. Thats why Broadcom remains one of the strongest infrastructure positions in the AI economy.

Shay Boloor

77,765 views • 23 days ago

Peter Thiel on $NVDA (about a year ago): It is probably quite tricky. If you had to concretize it, one thing that is very strange is if you just follow the money, at this point 80 to 85% of the money in AI is being made by one company, it is NVIDIA. It is all on this very weird hardware layer, which Silicon Valley does not even know very much about anymore. We do not really do hardware, we do not do silicon chips in Silicon Valley anymore. I get pitched on these companies once every three or four years, and it is always, I have no clue how to do this, it sounds like a pretty good idea, but man, I have no clue, and we never invest. There is this theory that the hardware piece makes the money initially, then gets more commodified over time, and it will shift to software. And the, I do not know, multi trillion dollar question is whether that is going to be true again this time, or whether NVIDIA will have this incredible monopoly. I suspect NVIDIA will. I think it will maintain its position for a while. I think the game theory on it is something like this. All the big tech companies are going to start trying to design their own AI chips so they do not have to pay the 10x markup to NVIDIA. How hard is it for them to do it? How long will it take? If they all do it, then the chips become a commodity and nobody makes money in chips. So do you go into hardware? You should do it if nobody else is doing it. If everybody does it, you should not do it. I am not sure how that nets out, but probably people stay stuck for a while and NVIDIA goes from strength to strength for a while.
1:55

Peter Thiel on $NVDA (about a year ago): It is probably quite tricky. If you had to concretize it, one thing that is very strange is if you just follow the money, at this point 80 to 85% of the money in AI is being made by one company, it is NVIDIA. It is all on this very weird hardware layer, which Silicon Valley does not even know very much about anymore. We do not really do hardware, we do not do silicon chips in Silicon Valley anymore. I get pitched on these companies once every three or four years, and it is always, I have no clue how to do this, it sounds like a pretty good idea, but man, I have no clue, and we never invest. There is this theory that the hardware piece makes the money initially, then gets more commodified over time, and it will shift to software. And the, I do not know, multi trillion dollar question is whether that is going to be true again this time, or whether NVIDIA will have this incredible monopoly. I suspect NVIDIA will. I think it will maintain its position for a while. I think the game theory on it is something like this. All the big tech companies are going to start trying to design their own AI chips so they do not have to pay the 10x markup to NVIDIA. How hard is it for them to do it? How long will it take? If they all do it, then the chips become a commodity and nobody makes money in chips. So do you go into hardware? You should do it if nobody else is doing it. If everybody does it, you should not do it. I am not sure how that nets out, but probably people stay stuck for a while and NVIDIA goes from strength to strength for a while.

Wall St Engine

824,845 views • 7 months ago

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD
3:17

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD

Daniel

20,558 views • 5 months ago

One reason I stay a bit quite about AI these few months. I can’t find my voice to say this right. I’ll try. — What has my AI found just in the millions of never saved TV from the 1980s-1990s? The simple commercial, I have the largest collection known in the world is a reflection of hyper nuanced humanity. Frail and over optimistic as it is, it shows the sprit of humanity in ways that self-hating 2010 Internet sewage training AI can not. It is interesting to have dark humor, when you know the soul of the person with the humor. It is not interesting to have dark humor from an AI that was not trained on the human spirit. The human sprit is not math, coding and science. This is the OUTCOME of a human sprit. We are training AI backwards and we just can’t see it yet, but we will. I am doing may best as “some posted on X” who has no currency in the “big boy” AI world to save the human sprit. We will need it one day and most of this training material is being erased, trillions of bytes daily. This is the secret to truthful AI. This is the secret to AI that LOVES humanity. We don’t get this right soon, there will be little chance. The data is… Almost gone.
0:30

One reason I stay a bit quite about AI these few months. I can’t find my voice to say this right. I’ll try. — What has my AI found just in the millions of never saved TV from the 1980s-1990s? The simple commercial, I have the largest collection known in the world is a reflection of hyper nuanced humanity. Frail and over optimistic as it is, it shows the sprit of humanity in ways that self-hating 2010 Internet sewage training AI can not. It is interesting to have dark humor, when you know the soul of the person with the humor. It is not interesting to have dark humor from an AI that was not trained on the human spirit. The human sprit is not math, coding and science. This is the OUTCOME of a human sprit. We are training AI backwards and we just can’t see it yet, but we will. I am doing may best as “some posted on X” who has no currency in the “big boy” AI world to save the human sprit. We will need it one day and most of this training material is being erased, trillions of bytes daily. This is the secret to truthful AI. This is the secret to AI that LOVES humanity. We don’t get this right soon, there will be little chance. The data is… Almost gone.

Brian Roemmele

123,518 views • 11 months ago

Linus's views on AI: - “AI is clearly a bubble, but it will change how most skilled jobs get done.” - “Vibe coding is great for getting into programming, but it's a horrible thing to maintain.” - “I'm a huge believer in AI. I'm not a huge believer in the things around AI. I find the market and marketing to be sick. There is going to be a crash.”
1:59

Linus's views on AI: - “AI is clearly a bubble, but it will change how most skilled jobs get done.” - “Vibe coding is great for getting into programming, but it's a horrible thing to maintain.” - “I'm a huge believer in AI. I'm not a huge believer in the things around AI. I find the market and marketing to be sick. There is going to be a crash.”

Yuchen Jin

1,129,631 views • 6 months ago

Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings
1:52

Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings

a16z

39,093 views • 2 months ago

As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries
0:59

As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

Daniel

151,698 views • 6 months ago

Why is Palantir so expensive? You don’t need to look at spreadsheets. Just consider this: The market knows NVIDIA sells the shovels for the AI goldrush. The market is realizing that AI isn’t being monetized at the commercial level because although it’s cool, it’s not unlocking any real insights yet. The market now anticipates that Palantir is selling the maps to find the gold…. Gold being AI-driven insights that actually solve difficult problems. Software that works. Since 2021, NVIDIA’s revenue has exploded from $16B to $96B. Palantir’s TTM revenue is $2.5B. The trajectory of Palantir has changed since AIP released in 2023, which is enabling the company to scale. If NVIDIA sells the shovels, and Palantir provides the maps, then the market believes Palantir will see the same explosion of growth within the commercial market, which the market believes has an almost unlimited TAM for Palantir. A lot of people missed out on NVIDIA. While Palantir’s market cap is expensive at $95B, it is nothing compared to NVIDIA’s $3.26T market cap in terms of size. The market doesn’t want to miss out on the next big thing. At this point, investors have thrown all standard methods of valuation out of the window… Those days were years ago. To me, at this point, buying the stock is betting on NVIDIA-like growth (No I’m not saying the company will shoot to a $3T market cap in 2 years — you get the point). If the company does not show this sort of revenue growth, the stock will be punished. This is the risk investors are willing to take. While I am very bullish on the company in the long run, I, like everyone else, have no clue what will actually happen in the short term. This is not a stock to play on the short term. This is why I continue to hold, regardless of how “expensive” the stock gets. I personally believe Palantir does in fact carry the potential to see explosive revenue growth to more than enough justify its current ratios. I’m not saying it will happen this quarter. But the potential is there. It’s a matter of when, in my opinion. I would never risk selling what I view as my golden ticket to wealth with the justification of “it’s too expensive, the price will come back down and I can buy even more then”. If the stock crashes, I can start buying more shares regardless — I don’t want to get greedy and try to time the market. I would never forgive myself if I sold and the stock ended up soaring so high that even after a crash, it would be far too expensive for me to get back in with my original position size (plus capital gains tax). I don’t care who agrees with me or who thinks I’m crazy for saying this — it’s a real risk to me and I’m not willing to take it. This is not me telling you to buy $PLTR. My average is $8.50. Only you can decide what is right, and your decision should be made on your own level of conviction from studying the company — nothing else. This is me telling you why it’s so expensive. Again, I believe that if the stock does not continue to crush earnings each quarter, even the slightest miss, the stock will be punished in the short term. For longs, it’s another opportunity to accumulate more. This is my opinion, of course. 5-10 years from now, we’ll see who was right. Chips & Ontology.
1:59

Why is Palantir so expensive? You don’t need to look at spreadsheets. Just consider this: The market knows NVIDIA sells the shovels for the AI goldrush. The market is realizing that AI isn’t being monetized at the commercial level because although it’s cool, it’s not unlocking any real insights yet. The market now anticipates that Palantir is selling the maps to find the gold…. Gold being AI-driven insights that actually solve difficult problems. Software that works. Since 2021, NVIDIA’s revenue has exploded from $16B to $96B. Palantir’s TTM revenue is $2.5B. The trajectory of Palantir has changed since AIP released in 2023, which is enabling the company to scale. If NVIDIA sells the shovels, and Palantir provides the maps, then the market believes Palantir will see the same explosion of growth within the commercial market, which the market believes has an almost unlimited TAM for Palantir. A lot of people missed out on NVIDIA. While Palantir’s market cap is expensive at $95B, it is nothing compared to NVIDIA’s $3.26T market cap in terms of size. The market doesn’t want to miss out on the next big thing. At this point, investors have thrown all standard methods of valuation out of the window… Those days were years ago. To me, at this point, buying the stock is betting on NVIDIA-like growth (No I’m not saying the company will shoot to a $3T market cap in 2 years — you get the point). If the company does not show this sort of revenue growth, the stock will be punished. This is the risk investors are willing to take. While I am very bullish on the company in the long run, I, like everyone else, have no clue what will actually happen in the short term. This is not a stock to play on the short term. This is why I continue to hold, regardless of how “expensive” the stock gets. I personally believe Palantir does in fact carry the potential to see explosive revenue growth to more than enough justify its current ratios. I’m not saying it will happen this quarter. But the potential is there. It’s a matter of when, in my opinion. I would never risk selling what I view as my golden ticket to wealth with the justification of “it’s too expensive, the price will come back down and I can buy even more then”. If the stock crashes, I can start buying more shares regardless — I don’t want to get greedy and try to time the market. I would never forgive myself if I sold and the stock ended up soaring so high that even after a crash, it would be far too expensive for me to get back in with my original position size (plus capital gains tax). I don’t care who agrees with me or who thinks I’m crazy for saying this — it’s a real risk to me and I’m not willing to take it. This is not me telling you to buy $PLTR. My average is $8.50. Only you can decide what is right, and your decision should be made on your own level of conviction from studying the company — nothing else. This is me telling you why it’s so expensive. Again, I believe that if the stock does not continue to crush earnings each quarter, even the slightest miss, the stock will be punished in the short term. For longs, it’s another opportunity to accumulate more. This is my opinion, of course. 5-10 years from now, we’ll see who was right. Chips & Ontology.

Jack Prescott

258,450 views • 1 year ago

This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.
0:35

This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.

Lin

92,571 views • 6 months ago

Friends this is not the time to fear ai 🤖 this is the time to be curious and play with it and understand it … please 🙏 don’t put your head in the sand … there is so much you can’t control when it comes to ai 🤖 and how it will play out … but there is a lot you can control on how you work with it and use it to build something for you and your family !!! Pls If you’re finally ready to not be scared of ai pls leave a 🤖 emoji in the the chat
0:30

Friends this is not the time to fear ai 🤖 this is the time to be curious and play with it and understand it … please 🙏 don’t put your head in the sand … there is so much you can’t control when it comes to ai 🤖 and how it will play out … but there is a lot you can control on how you work with it and use it to build something for you and your family !!! Pls If you’re finally ready to not be scared of ai pls leave a 🤖 emoji in the the chat

Gary Vaynerchuk

15,340 views • 7 months ago

$GOOGL IS HAVING ITS 2022 $NVDA MOMENT The market saw NVIDIA as gaming while it built the AI backbone. Today, Google is seen as just ads & search -- while it quietly owns the full Agentic AI stack: data, chips, distribution & the next-gen AI brain.
5:54

$GOOGL IS HAVING ITS 2022 $NVDA MOMENT The market saw NVIDIA as gaming while it built the AI backbone. Today, Google is seen as just ads & search -- while it quietly owns the full Agentic AI stack: data, chips, distribution & the next-gen AI brain.

Shay Boloor

528,112 views • 11 months ago