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LLMs are really well understood, what do you mean? You can see the precise activations and token probabilities for every next token. You can abliterate the netw
by xvector 2y ago
LLMs are really well understood, what do you mean? You can see the precise activations and token probabilities for every next token. You can abliterate the network however you'd like to suppress or excite concepts of your choosing.
- ben_w 2y agoThere's various layers of understanding. If you will excuse analogy and anthropomorphism, the human analogy of what we do and don't understand about LLMs is, I think, that we understand quantum mechanics, cell chemistry, and overall connectivity (perceptrons, activation functions, and architecture) and group psychology (general dynamics of the output), but not specifically how some belief is stored (in both humans and LLMs).
- menaerus 2y agoMathematically speaking LLMs have very precise formulation and can be seen as F(context, X0, X1, ..., XP) = next_token. What science behind the LLMs is still lacking is how all these parameters are correlated one to each other and why one set of values is giving a better prediction than the other set of values. Right now, we arrive to these values through experimental approach, that is, through trainings.
- currymj 2y agoi think the younger generation who came up post deep learning, has a very very low bar for “understanding” because they never knew a world where SotA models worked in a way that made sense.