4 ms·

Maybe it's not the LLMs nor the weights nor the data. But there are a great many things that can make a moat around a company: culture, talent, deals, investors

by dsign 1y ago

Maybe it's not the LLMs nor the weights nor the data. But there are a great many things that can make a moat around a company: culture, talent, deals, investors, brand, press attention, willingness to boil the oceans. For the moment at least, OpenAI seems to have quite many of those.

VirusNewbie 1y ago
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.
cft 1y ago
It looks like Ilya Sutskever wasn't as indispensable as he thought. SSI, Inc. is nowhere near the scale of OpenAI.
- mattnewton 1y ago
  was his goal ever to become the next OpenAI? I figured it was to get a bunch of money to do his own research with friends, and that seems to be working.
paulpauper 1y ago
What is interesting about the AI/LLM hype-cycle/bubble is how it can support so many entrants and players, like Cursor AI, Open AI, Cline, Gemini, Claude, Grok, CoPilot etc., and each carving a niche and a high valuation. THis is is in contrast to social networking, in which Facebook was the overwhelming dominant player, followed a distant second by LinkedIn. (Instagram was bought out.) Or Yahoo vs. Google. But now it's like a dozen companies, and each worth a lot and not as interchangeable, as seen with search engines or social networking. Facebook was the clear and dominant winner and superior platform, and there was little reason to use an alternative, except maybe LinkedIn for job searches.
- lbreakjai 1y ago
  They don't have a network effect, the cost of switching is almost null, and no model seem to have a clear and lasting edge. It made sense to be on Facebook, because everyone was on Facebook. It made sense to use google, because for a long while they were head and shoulders above the rest.

by dsign 1y ago

VirusNewbie 1y ago

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.

cft 1y ago

It looks like Ilya Sutskever wasn't as indispensable as he thought. SSI, Inc. is nowhere near the scale of OpenAI.

mattnewton 1y ago
was his goal ever to become the next OpenAI? I figured it was to get a bunch of money to do his own research with friends, and that seems to be working.

paulpauper 1y ago

What is interesting about the AI/LLM hype-cycle/bubble is how it can support so many entrants and players, like Cursor AI, Open AI, Cline, Gemini, Claude, Grok, CoPilot etc., and each carving a niche and a high valuation. THis is is in contrast to social networking, in which Facebook was the overwhelming dominant player, followed a distant second by LinkedIn. (Instagram was bought out.) Or Yahoo vs. Google. But now it's like a dozen companies, and each worth a lot and not as interchangeable, as seen with search engines or social networking. Facebook was the clear and dominant winner and superior platform, and there was little reason to use an alternative, except maybe LinkedIn for job searches.

lbreakjai 1y ago
They don't have a network effect, the cost of switching is almost null, and no model seem to have a clear and lasting edge. It made sense to be on Facebook, because everyone was on Facebook. It made sense to use google, because for a long while they were head and shoulders above the rest.