331–340 of 538 posts
Who is going to fund it? Training is unfathomably expensive. You have either VC funded models looking for a return on investment, or CCP funded models looking to solidify authoritarian "model Chinese society". Maybe there are some university 4B models, but I doubt those will carry far.
Earlier quoted context omitted.
I guess this was more related to syncing GPUs. If you were to take 500 computers with older 1080 GPUs, you might have enough compute/ram equivalent to an H200 GPU for training such a model. Maybe take 10000. But if those machines are spread over 10000 homes, wired with residential internet service, training a large model will not get anywhere. You go from "data in the same HBM memory chip" at 4.8TB/s or "data in adja…
You need to train independently and merge rarely. The problem is the merge step. Weights are too entangled, you are not going to get an improvement commensurate to the effort. Otherwise, everyone would do it. It is an open research problem.
From what I could tell from the very little time that I had to interact with it, it's instruction following seemed more consistent
The other thing that comes to mind is a lot of people commented on how driven it was, so I'm wondering whether figuring out how to keep existing models looping on task might actually be quite a big shift in capability
Turned out both assumptions were wrong. You couldn't trust sama to turn this into open source, the Chinese did. Elon never.
And we couldn't see demis take over as expected, probably blocked by Google buerocracy.
If you take AI risk seriously then Open Source AI should not and must not win. Both by evil actors (biological weapons research) and the danger of unaligned AGI itself. There are some people who would never work for the military or Anduril (automatic weapon systems), but an OS AI „without asking permission“ would be the same.
If closed-source AGI wins, it is not going to be much different from a safety perspective anyway, because AI capability research is advancing faster than safety research.
Edit: relevant Scott Alexander article from today
https://www.astralcodexten.com/p/my-ai-opinions
> In terms of bioweapons, I expect that closed-source AIs will be heavily optimized against helping with these, and open-source AI will be banned after the first warning shot (or become economically prohibitive even before then).
Earlier quoted context omitted.
As I replied to a child comment - this is a nice idea that just isn't tenable in reality. AI hardware isn't just hilariously faster than consumer GPUs, it's also hilariously more power-efficient and has hilariously better connectivity. Every one of these dimensions kills the idea. The far, FAR superior power efficiency means that even if you did harness every public GPU or GPU-like device on earth, you'd end up consu…
AI hardware is for inference, not training. Training uses normal HPC crap. Superpods aren't really power efficient, it's kind of a meme, and it stems from limiting the power draw of other components by having less of them. It's more of a rounding error. > you'd end up consuming so much excess electricity it would be cheaper on net to simply take the money that would have gone to the power bill and spend it on your ow…
And it will, but be patient. I took linux 25 years to conquer the world. One day an open source model reaches "good enough" level. Maybe around the level the current frontier has and most people will use that