5 ms·

In this imaginary timeline where initial investments keep increasing this way, how long before we see a leak shutter a company? Once the model is out, no one w

by jayd16 1y ago

In this imaginary timeline where initial investments keep increasing this way, how long before we see a leak shutter a company? Once the model is out, no one would pay for it, right?

marcosdumay 1y ago
In this imaginary reality where LLMs just keep getting better and better, all that a leak means is that you will eat-up your capital until you release your next generation. And you will want to release it very quickly either way, and should have a problem for a few months at most. And if LLMs don't keep getting qualitatively more capable every few months, that means that all this investment won't pay off and people will soon just use some open weights for everything.
jsheard 1y ago
Whatever happens if/when a flagship model leaks, the legal fallout would be very funny to watch. Lawyers desperately trying to thread the needle such that training on libgen is fair use, but training on leaked weights warrants the death penalty.
wmf 1y ago
You can't run Claude on your PC; you need servers. Companies that have that kind of hardware are not going to touch a pirated model. And the next model will be out in a few months anyway.
- jayd16 1y ago
  If it was worth it, you'd see some easy self hostable package, no? And by definition, its profitable to self host or these AI companies are in trouble.
  - quotemstr 1y ago
    Does your "self hostable package" come with its own electric substation?
    - jayd16 1y ago
      You're saying that's needed for inference?
  - serf 1y ago
    I think this misunderstands the scale of these models. And honestly I don't think a lot of these companies would turn a profit on pure utility -- the electric and water company doesn't advertise like these groups do; I think that probably means something.
    - jayd16 1y ago
      What's the scale for inference? Is it truly that immense? Can you ballpark what you think would make such a thing impossible? > the electric and water company doesn't advertise like these groups do I'm trying to understand what you mean here. In the US these utilities usually operate in a monopoly so there's no point in advertising. Cell service has plenty of advertising though.
  - tick_tock_tick 1y ago
    You need a 100+gigs ram and a top of the line GPU to run legacy models at home. Maybe if you push it that setup will let you handle 2 people maybe 3 people. You think anyone is going to make money on that vs $20 a month to anthropic?
    - deleted 1y ago
      [deleted]
    - jayd16 1y ago
      Can you explain to me where Anthropic (or it's investors) expect to be making money if that's what it actually costs to run this stuff?
      - lelanthran 1y ago
        > Can you explain to me where Anthropic (or it's investors) expect to be making money if that's what it actually costs to run this stuff? Not the GP (in fact I just replied to GP, disagreeing with them), but I think that economies of scale kick in when you are provisioning M GPUs for N users and both M and N are large. When you are provisioning for N=1 (a single user), then M=1 is the minimum you need, which makes it very expensive per user. When N=5 and M is still 1, then the cost per user is roughly a fifth of the original single-user cost.
    - lelanthran 1y ago
      > You need a 100+gigs ram and a top of the line GPU to run legacy models at home. Maybe if you push it that setup will let you handle 2 people maybe 3 people. This doesn't seem correct. I run legacy models with only slightly reduced performance on 32GB RAM with a 12GB VRAM GPU right now. BTW, that's not an expensive setup. > You think anyone is going to make money on that vs $20 a month to anthropic? Why does it have to be run as a profit-making machine for other users? It can run as a useful service for the entire household, when running at home. After all, we're not talking about specialised coding agents using this[1], just normal user requests. ==================================== [1] For an outlay of $1k for a new GPU I can run a reduced-performance coding LLM. Once again, when it's only myself using it, the economics work out. I don't need the agent to be fully autonomous because I'm not vibe coding - I can take the reduced-performance output, fix it and use it.
fredoliveira 1y ago
> Once the model is out, no one would pay for it, right? Well who does the inference at the scale we're talking about here? That's (a key part of) the moat.
paganel 1y ago
There’s the opportunity cost here of those resources (and not talking only about the money) not being spent on power generating that actually benefits the individual consumer.
petesergeant 1y ago
gpt-oss-120b has cost OpenAI virtually all of my revenue, because I can pay Cerebras and Groq a fraction of what I was paying for o4-mini and get dramatically faster inference, for a model that passes my eval suite. This is to say, I think high-quality "open" models that are _good enough_ are a much bigger threat. Even more so since OpenRouter has essentially commoditized generation. Each new commercial model needs to not just be better than the previous version, it needs to be significantly better than the SOTA open models for the bread-and-butter generation that I'm willing to pay the developer a premium to use their resources for generation.

by jayd16 1y ago

In this imaginary timeline where initial investments keep increasing this way, how long before we see a leak shutter a company? Once the model is out, no one would pay for it, right?

marcosdumay 1y ago

In this imaginary reality where LLMs just keep getting better and better, all that a leak means is that you will eat-up your capital until you release your next generation. And you will want to release it very quickly either way, and should have a problem for a few months at most. And if LLMs don't keep getting qualitatively more capable every few months, that means that all this investment won't pay off and people will soon just use some open weights for everything.

jsheard 1y ago

Whatever happens if/when a flagship model leaks, the legal fallout would be very funny to watch. Lawyers desperately trying to thread the needle such that training on libgen is fair use, but training on leaked weights warrants the death penalty.

wmf 1y ago

You can't run Claude on your PC; you need servers. Companies that have that kind of hardware are not going to touch a pirated model. And the next model will be out in a few months anyway.

jayd16 1y ago
If it was worth it, you'd see some easy self hostable package, no? And by definition, its profitable to self host or these AI companies are in trouble.
- quotemstr 1y ago
  Does your "self hostable package" come with its own electric substation?
  - jayd16 1y ago
    You're saying that's needed for inference?
- serf 1y ago
  I think this misunderstands the scale of these models. And honestly I don't think a lot of these companies would turn a profit on pure utility -- the electric and water company doesn't advertise like these groups do; I think that probably means something.
  - jayd16 1y ago
    What's the scale for inference? Is it truly that immense? Can you ballpark what you think would make such a thing impossible? > the electric and water company doesn't advertise like these groups do I'm trying to understand what you mean here. In the US these utilities usually operate in a monopoly so there's no point in advertising. Cell service has plenty of advertising though.
- tick_tock_tick 1y ago
  You need a 100+gigs ram and a top of the line GPU to run legacy models at home. Maybe if you push it that setup will let you handle 2 people maybe 3 people. You think anyone is going to make money on that vs $20 a month to anthropic?
  - deleted 1y ago
    [deleted]
  - jayd16 1y ago
    Can you explain to me where Anthropic (or it's investors) expect to be making money if that's what it actually costs to run this stuff?
    - lelanthran 1y ago
      > Can you explain to me where Anthropic (or it's investors) expect to be making money if that's what it actually costs to run this stuff? Not the GP (in fact I just replied to GP, disagreeing with them), but I think that economies of scale kick in when you are provisioning M GPUs for N users and both M and N are large. When you are provisioning for N=1 (a single user), then M=1 is the minimum you need, which makes it very expensive per user. When N=5 and M is still 1, then the cost per user is roughly a fifth of the original single-user cost.
  - lelanthran 1y ago
    > You need a 100+gigs ram and a top of the line GPU to run legacy models at home. Maybe if you push it that setup will let you handle 2 people maybe 3 people. This doesn't seem correct. I run legacy models with only slightly reduced performance on 32GB RAM with a 12GB VRAM GPU right now. BTW, that's not an expensive setup. > You think anyone is going to make money on that vs $20 a month to anthropic? Why does it have to be run as a profit-making machine for other users? It can run as a useful service for the entire household, when running at home. After all, we're not talking about specialised coding agents using this[1], just normal user requests. ==================================== [1] For an outlay of $1k for a new GPU I can run a reduced-performance coding LLM. Once again, when it's only myself using it, the economics work out. I don't need the agent to be fully autonomous because I'm not vibe coding - I can take the reduced-performance output, fix it and use it.

fredoliveira 1y ago

> Once the model is out, no one would pay for it, right? Well who does the inference at the scale we're talking about here? That's (a key part of) the moat.

paganel 1y ago

There’s the opportunity cost here of those resources (and not talking only about the money) not being spent on power generating that actually benefits the individual consumer.

petesergeant 1y ago

gpt-oss-120b has cost OpenAI virtually all of my revenue, because I can pay Cerebras and Groq a fraction of what I was paying for o4-mini and get dramatically faster inference, for a model that passes my eval suite. This is to say, I think high-quality "open" models that are _good enough_ are a much bigger threat. Even more so since OpenRouter has essentially commoditized generation. Each new commercial model needs to not just be better than the previous version, it needs to be significantly better than the SOTA open models for the bread-and-butter generation that I'm willing to pay the developer a premium to use their resources for generation.