A minimax chess engine in regular expressions
I wrote a (list of) regular expressions that will play a (not very good) chess game by running a 2-ply minimax search.
Nicholas Carlini is a research scientist at Anthropic working at the intersection of machine learning and computer security.
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I wrote a (list of) regular expressions that will play a (not very good) chess game by running a 2-ply minimax search.
A fun experiment where I back-port all the improvements we've made to chess engines over the last 30 years and run it on a 1996 Pentium Pro to see what we could have done if only we knew more at the time.
[What follows are my thoughts on some recent research in machine learning privacy. These are my thoughts, and do not represent those of others.]
I don't think that AI models (by which I mean: large language models) are over-hyped. In this post I will list 50 ways I've used them.
This program is a dependency-free implementation of GPT-2, including byte-pair encoding and transformer inference, in ~3000 bytes of C. I then use this to create something like Chat GPT.
An opinionated perspective on how to do important research that makes a difference (and sometimes win awards).
Figure from our paper: given any waveform, we can modify it slightly to produce another (similar) waveform that transcribes as any different target phrase.