3 ms·
Yeah looks very promising. Naively, it multiplies computation time by a factor of 20x though? If they are taking 5x samples per step, and multiple steps per pro
by sdwr 3y ago
Yeah looks very promising. Naively, it multiplies computation time by a factor of 20x though? If they are taking 5x samples per step, and multiple steps per problem.
https://imgur.com/a/VbpQZRm https://imgur.com/a/VbpQZRm
As this gets explored further, I believe we will start finding out why human minds are constructed the way they are, from the practical/necessity direction. Seems like the next step is farming out subtasks to smaller models, and adding an orthogonal dimension of emotionality to help keep track of state.
- GreedClarifies 3y agoI’m sympathetic to the idea of new types of specialized models to assist in this effort. We’re using our one hammer for all problems. In particular, it jumps out that a “ranking model” (different, I think from current ranking models) to judge which paths to take and which nodes to trim would make some level of sense.
- joshka 3y agoNot sure if it's relevant, but the OpenAI APIs generally support taking multiple responses in a single API call. I'm unsure what the generalized effect on processing time of that is however. From what I've read, this is sub-linear, so could reasonably be more effective than 20x, and I'd bet there are probably speedups to be had on the model side of this that make the extra time cost negligible.