6 ms·
We don't know what they do. We shape them, but our understanding of how they get to their result is comparatively minimal.
by Philpax 12d ago
We don't know what they do. We shape them, but our understanding of how they get to their result is comparatively minimal.
- mikmoila 12d agoI think you're referring to the fact that the sheer amount of computations is something too time consuming for us to follow? But still it is not "magical" - in theory we could follow all the steps, there's no hidden information.
- Philpax 12d agoNo, I mean we just don't know what's going on in the circuits of the model at any substantial level. We set their architecture (hyperparameters), we pump them full of data (pretraining), and we shape how they behave through examples (SFT) and reward (RL), but we can't say with any certainty what the resulting model does internally. You can scroll through https://transformer-circuits.pub/ https://transformer-circuits.pub/ to see the ~extent of our current understanding.
- mikmoila 12d agoYes "at any substancial level" . But still, its all about deterministic processes and still it obeys the law that the same input gives the same output. Or do you mean that the fluctuations like computing environment might ruin the determinism?
- johnsmith1840 12d ago100% not deterministic at the scale they run.