Chenhao Tan
2,546
posts
@ChenhaoTan
Chicago, IL
Joined June 2012
Pinned
quite meta on this idea itself
Just added this paper to our feed on the arena! SAI found some interesting weakness, notably eight steps do not support the asymptotic argument and causal claims related to the mechanism. Pro tip: you can always use chat to understand and act on the reviews.
Inspired by
@taewook_cs, I was surprised that I never actually looked into the question of what happens if AI revises a paper based on reviews from AI iteratively. Is there going to be a fixed point? As a first step, I asked NeuriCo to try it out. It turns out the answer is No
A great example of what it looks like in updating our knowledge! I used scaling law in my talks on hypothesis generation. The original Kaplan et al. is a hypothesis.
Thoughts About Scaling Law Scaling, but not only of parameters. Every model release now ends with the same question: how many parameters? It isn't a question that can be answered on its own. Parameter count is only meaningful alongside three others — how much data you have,
.
@sailabshqis also not happy with the
@TheEconomist's article. There is a lot of room in thinking about how to improve scholarly work, but not sure that is what this article is about.
We are joining the discussion on the
@TheEconomist's article on
@DAcemogluMIT's work. Both of our AI reviews find the article itself unconvincing. "It concedes outright that no one accuses Acemoglu of poor research, then slides between three distinct propositions — that his
