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A quoted post draws an “awesome” reaction · Digg

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A quoted post draws an “awesome” reaction

A user called a post they quoted “awesome” without explaining what they liked about it.

TLDR

A user quoted another post and wrote, “this was awesome.” They offered no further detail about the reaction.

Combined views

67.1K

15 Sources, first seen 20d ago

Combined views

67.1K

15 Sources, first seen 20d ago

773 likes

20d ago

first seen 20d ago

773 likes

50 comments

253 saves

40 reposts

50 comments

253 saves

40 reposts

Featured Source

15 Sources

@GaryMarcusthis was awesome20d

@TaylorLorenzI think you can make a compelling argument that a bunch of tech companies are overvalued based on their underlying biz model and we’re amidst a massive hype cycle, but to call AI technology “fake”… 🤨19d

@ShanuMathew93You can debate whether you believe their forecast on capex, labs, etc. but Coatue always does a nice job framing some of the biggest trends in the market very simply. The size of the compute financing & capex wave relative to the broader economy and prior cycles relative to the incremental revenue is the biggest Q to answer imo.18d

@DKThompSeveral facts regarding the AI bubble question that are all true at the same time, with most points illustrated by graphs 1. AI revenue growth is incredible, and possibly historic. 2. Big public tech companies have relatively low P/E ratios right now, which defies lazy predictions about how they're wildly mis-priced and doomed for a big correction 3. But model competition could compress AI token margins ... 4. ... at the same time that the hyperscalers are going deeper and deeper into debt to build out AI ... 5. ... and the level of future free cash flow anticipated to justify this build-out is absolutely enormous, like genuinely without precedent in corporate history ... 6. ... and any correction in frontier lab valuations will reverberate through public companies, which own huge shares in the labs18d

@davemcclureRT @DKThomp: Several facts regarding the AI bubble question that are all true at the same time, with most points illustrated by graphs 1.…18d

@DanielleFongRT @ShanuMathew93: You can debate whether you believe their forecast on capex, labs, etc. but Coatue always does a nice job framing some of…17d

@menhguinlike yeah, 2021 was basically a parabolic blow off top dead cat bounce 1930-style bear rally bidding up ridiculous nothingburgers. were it not for ChatGPT bringing LLMs to the mainstream, tech investors would be squeezing economic blood from a stone w/ real zero new ideas rn.17d

@firstadopterI will say it again!17d

@SemiAnalysis_"It's like a zombie apocalypse, but you don't know how many waves of zombies are coming." H100 rental prices went up, on a GPU that should be sliding down its depreciation curve. That curve is what lenders underwrite, and there's $7 trillion of debt coming by 2029. @dnishball kicks off our new Compute Capital Markets group with @JordanNanos. Nvidia's backstops, ClusterMAX as a credit signal, whether each token is profitable and more.17d

@gabriel1some napkin math for the "ai bubble" obviously all data created will pass through an llm in the future, which is 100000x more data than now so if model cost goes down 100x, we will only need 1000x more gpus17d

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15 Sources

@GaryMarcusthis was awesome20d

@TaylorLorenzI think you can make a compelling argument that a bunch of tech companies are overvalued based on their underlying biz model and we’re amidst a massive hype cycle, but to call AI technology “fake”… 🤨19d

@ShanuMathew93You can debate whether you believe their forecast on capex, labs, etc. but Coatue always does a nice job framing some of the biggest trends in the market very simply. The size of the compute financing & capex wave relative to the broader economy and prior cycles relative to the incremental revenue is the biggest Q to answer imo.18d

@DKThompSeveral facts regarding the AI bubble question that are all true at the same time, with most points illustrated by graphs 1. AI revenue growth is incredible, and possibly historic. 2. Big public tech companies have relatively low P/E ratios right now, which defies lazy predictions about how they're wildly mis-priced and doomed for a big correction 3. But model competition could compress AI token margins ... 4. ... at the same time that the hyperscalers are going deeper and deeper into debt to build out AI ... 5. ... and the level of future free cash flow anticipated to justify this build-out is absolutely enormous, like genuinely without precedent in corporate history ... 6. ... and any correction in frontier lab valuations will reverberate through public companies, which own huge shares in the labs18d

@davemcclureRT @DKThomp: Several facts regarding the AI bubble question that are all true at the same time, with most points illustrated by graphs 1.…18d

@DanielleFongRT @ShanuMathew93: You can debate whether you believe their forecast on capex, labs, etc. but Coatue always does a nice job framing some of…17d

@menhguinlike yeah, 2021 was basically a parabolic blow off top dead cat bounce 1930-style bear rally bidding up ridiculous nothingburgers. were it not for ChatGPT bringing LLMs to the mainstream, tech investors would be squeezing economic blood from a stone w/ real zero new ideas rn.17d

@firstadopterI will say it again!17d

@SemiAnalysis_"It's like a zombie apocalypse, but you don't know how many waves of zombies are coming." H100 rental prices went up, on a GPU that should be sliding down its depreciation curve. That curve is what lenders underwrite, and there's $7 trillion of debt coming by 2029. @dnishball kicks off our new Compute Capital Markets group with @JordanNanos. Nvidia's backstops, ClusterMAX as a credit signal, whether each token is profitable and more.17d

@gabriel1some napkin math for the "ai bubble" obviously all data created will pass through an llm in the future, which is 100000x more data than now so if model cost goes down 100x, we will only need 1000x more gpus17d

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