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> For all the desperate founders rushing to train their models to convince their investors for their next $100 million round. I would say Meta has (though not

> For all the desperate founders rushing to train their models to convince their investors for their next $100 million round. I would say Meta has (though not a startup) justified the expenditure. By freely releasing llama they undercut every a huge swath of competition who can get funded during the hype. Then when the hype dies they can pick up what the real size of the market is, with much better margins than if there were a competitive market. Watch as one day they stop releasing free versions and start rent seeking on N+1

mlinhares 2y ago
Given meta hasn’t been able to properly monetize WhatsApp I seriously doubt they can monetize this.
- fragmede 2y ago
  Who says they haven't?
grues-dinner 2y ago
Right, but that is all predicated that, when they get to the end, having spent tons of nuclear fuel, container shiploads of GPUs and whole national GDPs on the project, there will be some juice worth all that squeeze. And even if AI as we know it today is still relevant and useful in that future, and the marginal value per training-dollar stays (becomes?) positive, will they be able to defend that position against lesser, cheaper, but more agile AIs? What will the position even be that Llama2030 or whatever will be worth that much? Like, I know that The Market says the expected payoff is there, but what is it?
- vineyardmike 2y ago
  As the article suggests, the presence of LLAMA is decreasing demand for GPUs. Which are critical to Metas ad recommendation services. Ironically, by supporting the LLM community with free compute-intense models, they’re decreasing demand (and price) for the compute. I suspect they’ll never directly monetize LLAMA as a public service.
  - jorvi 2y ago
    > Ironically, by supporting the LLM community with free compute-intense models, they’re decreasing demand (and price) for the compute. For other people that that sentence didn't make sense for at first glance: "by supporting the LLM community with free compute-intense models [to run on their own hardware] they’re decreasing demand (and price) for the compute [server supply]."
    - fragmede 2y ago
      How fungible is that compute though? Having even a single H100 is different than having a bunch of 4090's, nevermind a properly networked supercomputer of H100s.
      - vineyardmike 2y ago
        That’s the point. You can run inference on a 4090 but training is better on a H100. If you use llama, you don’t need to train on an H100, so you can free that supply up for meta.
        fragmede 2y ago
        I haven't been following llama closely but I thought the latest model was too big for inference on 4090's, and that you can't fine tune on 4090's either, but furthermore, the other question is if the market is there for running inference on 4090s.
        vineyardmike 2y ago
        Well, (1) there are a ton of GPUs out there of various specs, and you can also use an inference provider who can use a H100 or similar to serve multiple inference requests at once. (2) there are a ton of LLAMA sizes, from 1b, 2b, 8b, 70b, and 400b. The smaller ones can even run on phone GPUs.
    - vineyardmike 2y ago
      Sorry, I should have been more clear. They’re decreasing demand for expensive GPUs that would be required to train a model. Fine-tuning and inference are less compute intense, so overall demand for top-end GPU performance is decreased even if inference compute demand is increased. Basically, why train an LLM from scratch, and spend millions on GPUs, when you can fine tune LLAMA and spend hundreds instead.
- scotty79 2y ago
  > there will be some juice worth all that squeeze. Without the squeeze there'd be a risk for some AI company getting enough cash to buy out Facebook just for the user data. If you want to keep status quo it's good to undercut someone in the cradle that could eventually take over your business. So it might cost Meta pretty penny but it's a mitigation for existential risk. If you climbed up to the top of wealth and influence ladder you should spend all you can to kick off the ladder. It's gonna be always worth it. Unless you still fall because it wasn't enough.
- rsynnott 2y ago
  > having spent tons of nuclear fuel It will be primarily gas, maybe some coal. The nuclear thing is largely a fantasy; the lead time on a brand new nuclear plant is realistically a decade, and it is implausible that the bubble will survive that long.
pico_creator 2y ago
Given their rising stock price trend, due to their moves in AI. Definitely worth it for them

mlinhares 2y ago

Given meta hasn’t been able to properly monetize WhatsApp I seriously doubt they can monetize this.

fragmede 2y ago
Who says they haven't?

grues-dinner 2y ago

Right, but that is all predicated that, when they get to the end, having spent tons of nuclear fuel, container shiploads of GPUs and whole national GDPs on the project, there will be some juice worth all that squeeze. And even if AI as we know it today is still relevant and useful in that future, and the marginal value per training-dollar stays (becomes?) positive, will they be able to defend that position against lesser, cheaper, but more agile AIs? What will the position even be that Llama2030 or whatever will be worth that much? Like, I know that The Market says the expected payoff is there, but what is it?

vineyardmike 2y ago
As the article suggests, the presence of LLAMA is decreasing demand for GPUs. Which are critical to Metas ad recommendation services. Ironically, by supporting the LLM community with free compute-intense models, they’re decreasing demand (and price) for the compute. I suspect they’ll never directly monetize LLAMA as a public service.
- jorvi 2y ago
  > Ironically, by supporting the LLM community with free compute-intense models, they’re decreasing demand (and price) for the compute. For other people that that sentence didn't make sense for at first glance: "by supporting the LLM community with free compute-intense models [to run on their own hardware] they’re decreasing demand (and price) for the compute [server supply]."
  - fragmede 2y ago
    How fungible is that compute though? Having even a single H100 is different than having a bunch of 4090's, nevermind a properly networked supercomputer of H100s.
    - vineyardmike 2y ago
      That’s the point. You can run inference on a 4090 but training is better on a H100. If you use llama, you don’t need to train on an H100, so you can free that supply up for meta.
      - fragmede 2y ago
        I haven't been following llama closely but I thought the latest model was too big for inference on 4090's, and that you can't fine tune on 4090's either, but furthermore, the other question is if the market is there for running inference on 4090s.
        vineyardmike 2y ago
        Well, (1) there are a ton of GPUs out there of various specs, and you can also use an inference provider who can use a H100 or similar to serve multiple inference requests at once. (2) there are a ton of LLAMA sizes, from 1b, 2b, 8b, 70b, and 400b. The smaller ones can even run on phone GPUs.
  - vineyardmike 2y ago
    Sorry, I should have been more clear. They’re decreasing demand for expensive GPUs that would be required to train a model. Fine-tuning and inference are less compute intense, so overall demand for top-end GPU performance is decreased even if inference compute demand is increased. Basically, why train an LLM from scratch, and spend millions on GPUs, when you can fine tune LLAMA and spend hundreds instead.
scotty79 2y ago
> there will be some juice worth all that squeeze. Without the squeeze there'd be a risk for some AI company getting enough cash to buy out Facebook just for the user data. If you want to keep status quo it's good to undercut someone in the cradle that could eventually take over your business. So it might cost Meta pretty penny but it's a mitigation for existential risk. If you climbed up to the top of wealth and influence ladder you should spend all you can to kick off the ladder. It's gonna be always worth it. Unless you still fall because it wasn't enough.
rsynnott 2y ago
> having spent tons of nuclear fuel It will be primarily gas, maybe some coal. The nuclear thing is largely a fantasy; the lead time on a brand new nuclear plant is realistically a decade, and it is implausible that the bubble will survive that long.

pico_creator 2y ago

Given their rising stock price trend, due to their moves in AI. Definitely worth it for them