LLMs/transformers are a breakthrough on the level of convolutional neural networks — significant, and one that opens up lots of new interesting applications as well as invites lots more R&D — but like the neural net it’s not gonna fundamentally transform society or industry.
(And as far as I can tell this current craze is entirely predicated on LLMs/transformers.)
Autonomous cars alone will be transformative. And LLMs are not in their end-state, we went from GPT-1 to 4 in 5 years over that timespan it gained lots of new capabilities. Extrapolate, don't just look at what they can do today.
Atoms are more difficult than bits, so physical applications (e.g. in factories, robotics) will lag. I also expect specialist models like AlphaFold slowly finding their niches over time.
> significant, and one that opens up lots of new interesting applications as well as invites lots more R&D — but like the neural net it’s not gonna fundamentally transform society or industry.
Yeah, and semiconductor electronics that grad-students built from of germanium by painstakingly pressing them together are very interesting and worth additional R&D but won't transform society either.
I guess where both you and the GP are correct is that you can't make an autonomous car by applying transformers exclusively.
LLMs are "language I/O interfaces", and as such there isn't a lot of value they can create alone (even most of the currently proposed uses are bullshit). But it's quite likely that they'll be there on a lot of advanced technology helping it do what you meant.
Still even though both will be there in the transformative technology, and even though the technology may not even be useful without them, they are not central pieces on most of it.
llm companies raise lots of money on crazy evaluation, the question is if they will be able to build enough revenue stream to justify further money injections.
