2 ms·

Blog post: https://www.etched.com/announcing-etched https://www.etched.com/announcing-etched I don't see a lot of detail on the actual architecture. Hard to ev

Blog post: https://www.etched.com/announcing-etched https://www.etched.com/announcing-etched I don't see a lot of detail on the actual architecture. Hard to evaluate if it makes sense. The idea of specializing in transformers has merit I think. It seems like this is only for inference, not training. Although inference accelerators are definitely important and potentially lucrative, I find it hard to get excited about them. To me the exciting thing is accelerating progress in capabilities, which means training. The title of the blog post is "Etched is Making the Biggest Bet in AI", and it is a pretty big bet to make an ASIC only for transformers. Even something like 1.5-bit transformers could come along and make their hardware blocks obsolete in six months. Actually I would love to see an ASIC implementation of 1.5 bit transformers, it could probably be far more efficient than even this chip.

airstrike 2y ago
I know very little about hardware, but could they presumably take whatever they learn from this chip and transfer some of that knowledge into a 1.5bit implementation?
- wmf 2y ago
  Of course, but designing the next chip takes two years or more. If you're always two years behind, you're dead.
  - airstrike 2y ago
    Yeah, but 1.5 bit isn't here, so they're not really late
bilater 2y ago
I actually think its a huge deal if this works as it unlocks use cases like real time AI video, instant natural voice agents, as well as probably a bump in reasoning (either one shot or for multi step processes) by techniques like generating 100s of answers and picking one. yes - ultimately the big W is smarter models but this is a huge step up on this (local or global?) optima.