Comment by combobyte
7 hours ago
Yep, I agree. The only 'frontier' any of the big labs are racing towards is the frontier of financial ruin.
7 hours ago
Yep, I agree. The only 'frontier' any of the big labs are racing towards is the frontier of financial ruin.
I think we're going to suddenly see them greatly scale back training and try to sell inference-only, but they all know when they do that someone can jump up and outstrip them.
But only as long as training actually improves models significantly. As soon as those improvements stay below a certain threshold, the better move is to invest your R&D money into other things like harnesses or new tricks one can play with existing models and the immense cost of training is just not worth it to be 0.5% ahead.
I'm absolutely certain that we will reach that point, just not when. Could come sooner than we think though.
Don't get me wrong I still want the models intelligence to improve, but for all practical purposes we are already there this is why many people are already moving to cheaper/open source. There is still a case though for the 1% of queries that demand SOTA
At that point they would lose all advantage stemming from their ability to boil the ocean though.
> I think we're going to suddenly see them greatly scale back training and try to sell inference-only
Remember a few weeks ago when all the AI labs said "we need to slow down, to uh, prevent destroying the world"?
Ding!
In this version of conspiracy theory, all the labs secretly understood that training wasn't economically feasible anymore so they all jointly made it look like they were stopping for safety reasons.
Is there no end to this kind of lazy conspiracy theory
3 replies →
Well there certainly is at least some kind of viable business running large AI models for a fee.
These are useful and too big to run locally.
The ultimate size of that business in terms of revenues and profits may not match current expectations, but it's also not 0
> Well there certainly is at least some kind of viable business running large AI models for a fee.
ok, where are:
- The economies of scale?
- The network effects?
- The switching costs?
- The intangible assets (e.g. brand?)
Running AI models for a fee has none of these. At best, there are some economies of scale for running a datacenter, but OpenAI and Anthropic have none.
There are not as many network effects, intangible assets, or switching costs as other businesses. I believe there are economies of scale in terms of power and cooling and network bandwidth and the people who plug in cables and other such things.
The business logic is similar to the general transition to cloud. Corporations and individuals are better off paying someone else to manage physical hardware that they just access over the network. That is even more true of large, expensive, fancy AI GPUs than regular web servers.
OpenAI and Anthropic may both fail, or may not, I don't know. But I'm sure there is some kind of viable business running some kind of AI in the cloud.
2 replies →
Amazon will be able to run large models for a fee, and make money on it. It's not a trillion dollar business, it may not even be a good business, but they'll be able to do it.
1 reply →