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OpenAI just minted a brand new Mag 7 in under 10 years. Almost every other AI company is collecting scraps. Sora is one of the fastest growing apps in history.

OpenAI just minted a brand new Mag 7 in under 10 years. Almost every other AI company is collecting scraps. Sora is one of the fastest growing apps in history. When they add ads to ChatGPT, they'll make bank. I use ChatGPT way more than I use Google now.

prescriptivist 1y ago
OpenAI's (and other superscalers) revenue isn't really up for debate, nor is the long term value of their mission/product. The issue (somewhat articulated in this article) is that the superscalers (both public and private) have generated such a massive, unprecedented amount of speculative investment as well as capital expenditure that has left the rest of the economy in the dust (aka minting a mag 7 in less than a decade) that we have a distorted view of the world. The fear of an AI bubble isn't that AI companies will fail, it's that a downturn in the AI "bubble" will lay bare the underlying bear market that their growth is occluding. What happens then? Nobody knows. Probably nothing good. Personally I think much of the stock market growth in the last few years that seems disconnected with previous trends (see parallel growth betwen gold and equities) is based on retail volume and unorthodox retail patterns (Robinhood, WSB, et. al) that I think conventional historical market analysis is completely unprepared for. At this point everything may go to the moon forever, or it may collapse completely. Either way, we live in a time of little precedence.
- beeflet 1y ago
  >OpenAI's (and other superscalers) revenue isn't really up for debate It isn't? What is stopping companies from building on GPT-OSS or other local models for cheaper? The AI services have no moat. I agree with your second paragraph. The boom in the AI market is occluding a general bear market.
  - prescriptivist 1y ago
    > It isn't? What is stopping companies from building on GPT-OSS or other local models for cheaper? The AI services have no moat. Right now there is an efficiency/hardware moat. That's why the Stargate in Abilene and corresponding build outs in Louisiana and elsewhere are some of the most intense capex projects from the private sector ever. Hardware and electric production is the name of the game right now. This Odd Lots podcast is really fresh and relevant to this conversation: https://www.youtube.com/watch?v=xsqn2XJDcwM https://www.youtube.com/watch?v=xsqn2XJDcwM Local models, local agents, local everything and the commodification of LLMs, at least for software eng is inevitable IMO, but there is a lot of tooling that hasn't yet been built for that commodified experience yet. For companies rapidly looking to pivot to AI force multiplication, the superscalers are the answer for now. I think it's a highly inefficient approach for technical orgs, but time will create efficiency. For your joe on the street feeding data into an LLM, then I don't think any of those orgs (think your local city hall, or state DMV) are going to run local models. So there is a captured market to some degree for the the current superscalars.
beeflet 1y ago
I don't use LLMs for finding products, just general topics. It doesn't give good recommendations because the training set is so out of date, and I find it unusual that that anyone would use it for product recommendation. Lastly, "fastest growing" in the short term does not amount to much in the long term.
- echelon 1y ago
  > I find it unusual that that anyone would use it for product recommendation. I would say the exact same for Google. What isn't SEO'd to hell is crowded out by half a page of paid search ads. I'm not a typical consumer though. I don't think I've ever bought anything via an ad. The only search ads I click are the ones where Google FOMO-extorted the brand into buying ads for their own trademark. (That shit ought to be illegal given the monopoly levels of search capture Google has. Everyone having to buy up search clicks for their own brands and company names is comical. A protection racket.)
  - beeflet 1y ago
    An example of a purchase I made recently is this $15 bimetal heat break: https://www.amazon.com/dp/B0C5VSK1V8 https://www.amazon.com/dp/B0C5VSK1V8 it's basically a part that allows you to 3D print at higher temperatures. To figure out that this was the right product I wanted, it took a couple minutes of research, looking at diagrams, searching recent reddit and youtube posts, etc. If I would have asked an LLM, it would have told me to buy an all-metal hotend that costs $70 or more, based on outdated advice. I don't trust LLMs for out of the box thinking because they have no idea what is going on in the real world. They are fine for discussing general aspects of well-documented and often-discussed things like taxes, cooking, or gardening.
827a 1y ago
ChatGPT was at 700M weekly actives when their head of product went on Lenny's Podcast on Aug 9th. This week Sam announced at dev day they'd hit 800M weekly actives. They gained 100M users in two months. Not monthly active; weekly active. Polymarket has the market for "1B monthly actives in 2025" at 78%, but to be frank; if they're at 800M WAUs, they've probably already blown past 1B MAUs. We probably won't hear them announce 1B WAUs in 2025; but I'd bet every dollar I own that we'll hear it before the end of 2026-Q1. Here's something I implore readers think about, just to help ground your reality in the numbers we're talking: The super bowl gets ~120M viewers. During the four hour event, this year, they turned ~$800M in advertising revenue. What you're thinking is "I see where you're going with this, but that's higher value advertising, its not the same on..." and I'll stop you right there and ask: How much revenue do you think Meta makes every day? The answer: ~$450M. Not far off. OpenAI will make so much money if they figure out advertising. Incomprehensible, eye-watering amounts of money. They will spend all of it and more building data centers. If your mental model on these companies is still based in some religious belief that they need to achieve AGI to be profitable, and AGI isn't possible/feasible: you need to update your model. AGI doesn't matter. People want to stop thinking and sext their chatgpt robot therapist. You can hate it, but get with the program and stop crystalizing that legitimate hate for what the future looks like as some weird fantasy that OpenAI is unsuccessful and going to implode.

prescriptivist 1y ago

OpenAI's (and other superscalers) revenue isn't really up for debate, nor is the long term value of their mission/product. The issue (somewhat articulated in this article) is that the superscalers (both public and private) have generated such a massive, unprecedented amount of speculative investment as well as capital expenditure that has left the rest of the economy in the dust (aka minting a mag 7 in less than a decade) that we have a distorted view of the world. The fear of an AI bubble isn't that AI companies will fail, it's that a downturn in the AI "bubble" will lay bare the underlying bear market that their growth is occluding. What happens then? Nobody knows. Probably nothing good. Personally I think much of the stock market growth in the last few years that seems disconnected with previous trends (see parallel growth betwen gold and equities) is based on retail volume and unorthodox retail patterns (Robinhood, WSB, et. al) that I think conventional historical market analysis is completely unprepared for. At this point everything may go to the moon forever, or it may collapse completely. Either way, we live in a time of little precedence.

beeflet 1y ago
>OpenAI's (and other superscalers) revenue isn't really up for debate It isn't? What is stopping companies from building on GPT-OSS or other local models for cheaper? The AI services have no moat. I agree with your second paragraph. The boom in the AI market is occluding a general bear market.
- prescriptivist 1y ago
  > It isn't? What is stopping companies from building on GPT-OSS or other local models for cheaper? The AI services have no moat. Right now there is an efficiency/hardware moat. That's why the Stargate in Abilene and corresponding build outs in Louisiana and elsewhere are some of the most intense capex projects from the private sector ever. Hardware and electric production is the name of the game right now. This Odd Lots podcast is really fresh and relevant to this conversation: https://www.youtube.com/watch?v=xsqn2XJDcwM https://www.youtube.com/watch?v=xsqn2XJDcwM Local models, local agents, local everything and the commodification of LLMs, at least for software eng is inevitable IMO, but there is a lot of tooling that hasn't yet been built for that commodified experience yet. For companies rapidly looking to pivot to AI force multiplication, the superscalers are the answer for now. I think it's a highly inefficient approach for technical orgs, but time will create efficiency. For your joe on the street feeding data into an LLM, then I don't think any of those orgs (think your local city hall, or state DMV) are going to run local models. So there is a captured market to some degree for the the current superscalars.

beeflet 1y ago

I don't use LLMs for finding products, just general topics. It doesn't give good recommendations because the training set is so out of date, and I find it unusual that that anyone would use it for product recommendation. Lastly, "fastest growing" in the short term does not amount to much in the long term.

echelon 1y ago
> I find it unusual that that anyone would use it for product recommendation. I would say the exact same for Google. What isn't SEO'd to hell is crowded out by half a page of paid search ads. I'm not a typical consumer though. I don't think I've ever bought anything via an ad. The only search ads I click are the ones where Google FOMO-extorted the brand into buying ads for their own trademark. (That shit ought to be illegal given the monopoly levels of search capture Google has. Everyone having to buy up search clicks for their own brands and company names is comical. A protection racket.)
- beeflet 1y ago
  An example of a purchase I made recently is this $15 bimetal heat break: https://www.amazon.com/dp/B0C5VSK1V8 https://www.amazon.com/dp/B0C5VSK1V8 it's basically a part that allows you to 3D print at higher temperatures. To figure out that this was the right product I wanted, it took a couple minutes of research, looking at diagrams, searching recent reddit and youtube posts, etc. If I would have asked an LLM, it would have told me to buy an all-metal hotend that costs $70 or more, based on outdated advice. I don't trust LLMs for out of the box thinking because they have no idea what is going on in the real world. They are fine for discussing general aspects of well-documented and often-discussed things like taxes, cooking, or gardening.

827a 1y ago

ChatGPT was at 700M weekly actives when their head of product went on Lenny's Podcast on Aug 9th. This week Sam announced at dev day they'd hit 800M weekly actives. They gained 100M users in two months. Not monthly active; weekly active. Polymarket has the market for "1B monthly actives in 2025" at 78%, but to be frank; if they're at 800M WAUs, they've probably already blown past 1B MAUs. We probably won't hear them announce 1B WAUs in 2025; but I'd bet every dollar I own that we'll hear it before the end of 2026-Q1. Here's something I implore readers think about, just to help ground your reality in the numbers we're talking: The super bowl gets ~120M viewers. During the four hour event, this year, they turned ~$800M in advertising revenue. What you're thinking is "I see where you're going with this, but that's higher value advertising, its not the same on..." and I'll stop you right there and ask: How much revenue do you think Meta makes every day? The answer: ~$450M. Not far off. OpenAI will make so much money if they figure out advertising. Incomprehensible, eye-watering amounts of money. They will spend all of it and more building data centers. If your mental model on these companies is still based in some religious belief that they need to achieve AGI to be profitable, and AGI isn't possible/feasible: you need to update your model. AGI doesn't matter. People want to stop thinking and sext their chatgpt robot therapist. You can hate it, but get with the program and stop crystalizing that legitimate hate for what the future looks like as some weird fantasy that OpenAI is unsuccessful and going to implode.