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What are the considerations around whether to structure the debate to permit the judge to abstain (as Michael et al do, by allowing the judge to end the round with low credence) versus forcing the judge to pick an answer each time? Are there pros/cons to each approach? Any arguments about similarity of one or the other to the real AI debates that might be held in the future?
 

It's possible I'm misremembering/misunderstanding the protocols used for the debate here/in that other paper.

"Follow the right people on twitter" is probably the best option. People will often post twitter threads explaining new papers they put out. There's also stuff like:

I appreciate you transcribing these interviews William!

I've been loving your optimization posts so far; thanks for writing them. I've been feeling confused about this topic for a while and feel like "being able to answer any question about optimization" would be hugely valuable for me.

We're expecting familiarity with PyTorch, unlike MLAB. The level of Python background expected is otherwise similar. The bar will vary somewhat depending on each applicant's other traits, e.g. mathematical and empirical-science backgrounds

Video link in the pdf doesn't work

Confusion:

You write "Only PaLM looks better than Chinchilla here, mostly because it trained on 780B tokens instead of 300B or fewer, plus a small (!) boost from its larger size."

But earlier you write:

"Chinchilla is a model with the same training compute cost as Gopher, allocated more evenly between the two terms in the equation.

It's 70B params, trained on 1.4T tokens of data"

300B vs. 1.4T. Is this an error?

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