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I don't find it convincing that the tech isn't the moat. If the tech wasn't a moat, you'd see Microsoft spinning up its own competitor, you'd see Amazon, Apple,

I don't find it convincing that the tech isn't the moat. If the tech wasn't a moat, you'd see Microsoft spinning up its own competitor, you'd see Amazon, Apple, Meta, Oracle all have SoTA frontier models as well. We don't see that, we see three established players in the frontier model space, and a lot of folks fighting in the second tier category.

aleph_minus_one 1y ago
> If the tech wasn't a moat, you'd see Microsoft spinning up its own competitor, you'd see Amazon, Apple, Meta, Oracle all have SoTA frontier models as well. Rather: these companies consider it to be a really bad business idea to spend lots of billions for building a new state-of-the-art model that will be obsolete half a year later.
- VirusNewbie 1y ago
  Are you under the impression they aren't burning money trying to make their own foundational models?
  - aleph_minus_one 1y ago
    > Are you under the impression they aren't burning money trying to make their own foundational models? Indeed, I think they burn money with that, but not as much as they would if they were putting all of their eggs into one casket, as the "AI companies" like OpenAI and Anthropic do (or do much more). There exist multiple (not mutually exclusive) explanations for that: - Limititing the "money burn rate" on AI is a political compromise that was made at the companies between various decision makers - The companies hope that at the end even a not state-of-the-art AI model might offer business opportunities - Perhaps such a model might give you a better "bang per buck" rate (cost of training, cost of running) - These companies want to get experience with AI, so they currently burn a lot of money of it, but will pivot when their AI models have been out-competed - Such a pivot could be getting from "state-of-the-art models" to "models that are insanely cheaply to run, while still being powerful" - Perhaps the decision makers of the respective companies believe in the (not implausible) scenario that AI could from a technical perspective continue improving a lot, but these models will get disproportionally expensive to run, i.e. in the upcoming future AI models won't improve so much anymore because no one will be able to pay for it. In such a case having a slightly worse model is much less of a disadvantage.
    - VirusNewbie 1y ago
      > but not as much as they would if they were putting all of their eggs into one casket, as the "AI companies" like OpenAI and Anthropic do (or do much more). Microsoft invested over 15 billion in OpenAI. You think they wouldn't have rather spent a fraction of that to have a SoTA model? Limititing the "money burn rate" on AI is a political compromise that was made at the companies between various decision makers Meta has no one to compromise with as Zuck is the majority shareholder (voting wise), Apple has so much cash they don't know what to do with it (cars, VR, etc), This argument doesn't hold up for these cash rich top companies. The companies hope that at the end even a not state-of-the-art AI model might offer business opportunities I find it hard to believe that OpenAI, Anthropic, and Google all aren't optimizing for 'bang for buck' here.

aleph_minus_one 1y ago

> If the tech wasn't a moat, you'd see Microsoft spinning up its own competitor, you'd see Amazon, Apple, Meta, Oracle all have SoTA frontier models as well. Rather: these companies consider it to be a really bad business idea to spend lots of billions for building a new state-of-the-art model that will be obsolete half a year later.

VirusNewbie 1y ago
Are you under the impression they aren't burning money trying to make their own foundational models?
- aleph_minus_one 1y ago
  > Are you under the impression they aren't burning money trying to make their own foundational models? Indeed, I think they burn money with that, but not as much as they would if they were putting all of their eggs into one casket, as the "AI companies" like OpenAI and Anthropic do (or do much more). There exist multiple (not mutually exclusive) explanations for that: - Limititing the "money burn rate" on AI is a political compromise that was made at the companies between various decision makers - The companies hope that at the end even a not state-of-the-art AI model might offer business opportunities - Perhaps such a model might give you a better "bang per buck" rate (cost of training, cost of running) - These companies want to get experience with AI, so they currently burn a lot of money of it, but will pivot when their AI models have been out-competed - Such a pivot could be getting from "state-of-the-art models" to "models that are insanely cheaply to run, while still being powerful" - Perhaps the decision makers of the respective companies believe in the (not implausible) scenario that AI could from a technical perspective continue improving a lot, but these models will get disproportionally expensive to run, i.e. in the upcoming future AI models won't improve so much anymore because no one will be able to pay for it. In such a case having a slightly worse model is much less of a disadvantage.
  - VirusNewbie 1y ago
    > but not as much as they would if they were putting all of their eggs into one casket, as the "AI companies" like OpenAI and Anthropic do (or do much more). Microsoft invested over 15 billion in OpenAI. You think they wouldn't have rather spent a fraction of that to have a SoTA model? Limititing the "money burn rate" on AI is a political compromise that was made at the companies between various decision makers Meta has no one to compromise with as Zuck is the majority shareholder (voting wise), Apple has so much cash they don't know what to do with it (cars, VR, etc), This argument doesn't hold up for these cash rich top companies. The companies hope that at the end even a not state-of-the-art AI model might offer business opportunities I find it hard to believe that OpenAI, Anthropic, and Google all aren't optimizing for 'bang for buck' here.