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mad

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投稿

Can LLMs model real-world systems in TLA+?

sigops.org
123 ポイント·投稿者 mad·2 か月前·33 コメント

How LLMs and coding agents change the dynamics of adopting Rust

mdwdotla.medium.com
1 ポイント·投稿者 mad·4 か月前·0 コメント

An opinionated take on how to do important research that matters

nicholas.carlini.com
169 ポイント·投稿者 mad·4 か月前·42 コメント

DoubleAI's WarpSpeed: Surpassing Expert-Written Kernels at Scale

doubleai.com
2 ポイント·投稿者 mad·4 か月前·0 コメント

Are large language models worth it?

nicholas.carlini.com
10 ポイント·投稿者 mad·8 か月前·0 コメント

コメント

mad
·4 か月前·議論
> Most of this list is about how to dress for senpai; figuratively speaking. A pretty depressing take on "how to do important research that matters".

How is that the case? The tips seem to aim for impactful research: picking good ideas and executing well on them. There's a tacit assumption that such impactful research will win best paper awards, but that's actually not substantiated and isn't obviously correct, since best paper selection committees can't see the future. For example, many (maybe most?) winners of retrospective awards (test-of-time / influential paper) aren't papers that won a best paper award when originally published.

Most of the author's papers he cites in the post, including the membership inference paper which is one of the papers the author is "most proud of," didn't win best paper awards.