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As a trainer and facilitator who works with nonprofit organizations and staffers, you have to be obsessed with learningtheory to design and deliver effective instruction, have productive meetings, or embark on your own self-directed learning path.
In the graph below, borrowed from the same article, you can see how some of the most cutting-edge algorithms in deep learning have increased in terms of model size over time. To illustrate the energy needed in deep learning, let’s make a comparison.
We link to hundreds of papers and blog posts and offer approximately a hundred different example projects. Motivation: Two lines of recent work have looked for undesirable behaviors in LLMs, approaching the problem from two different angles: Andriushchenko et al. Kumar et al. , Another way could simply be to use low perplexity.
So when youre doing mechanistic interpretability, you have some claim about how the model behaves, and how the model actually behaves might be a bit different than this, but if your understanding is any good, itll be pretty close. Can you tell us: in this case of max of n, roughly, what are you doing to get different kinds of proofs?
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