this post was submitted on 31 Jul 2024
34 points (100.0% liked)
Technology
37634 readers
349 users here now
A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.
Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.
Subcommunities on Beehaw:
This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Ditto on the hate, technical, but important distinction here, they support open-weight ML. They do not release training source code or data sets to actually make your own (granted you'd need millions in video cards to do it, but still). Open-source gets thrown around a lot in AI, presumably virtue signalling, but precious few walk the walk.
Never underestimate the value of getting hordes of unpaid workers to refine your product. (See also React, others)
I understand the distinction, but it's still waaay better than what ~~OpenIAI~~ClosedAI is doing.
Also people are really good at reverse engineering. Open weights models can be fine tuned or adapted. I am trained a Llama 3 Lora not that long ago.
Agreed, and the chance of it backfiring on them is indeed pleasingly high. If the compute moat for initial training gets lower (e.g. trinary/binary models) or distributed training (Hivemind etc) takes off, or both, or something new, all bets are off.
The compute moat for the initial training will never get lower. But as the foundation models get better, the need for from-scratch training will be less frequent.