Using LLMs for everything is going to be seen as a big fad in a few years. First we try them for everything, then we find what use cases actually make sense, then we scale back. Woe betide our 401(k)s when it happens, though.
drBonkers 13 minutes ago [-]
This is a concise statement of what I've tried to articulate by analogizing it to railroad infra buildout.
What applications do you think make the most sense so far?
simianwords 6 minutes ago [-]
The paper did not compare against LLMs though.
z3c0 36 minutes ago [-]
Ha! To think that we're finally back to asking ourselves why we are using generative models for categorization and extraction. I wonder how much money has collectively been wasted by companies wittling away at square pegs.
3 hours ago [-]
Rendered at 16:15:48 GMT+0000 (Coordinated Universal Time) with Vercel.
What applications do you think make the most sense so far?