Pre-1900 LLM Relativity Test
Wanted to share one of my personal projects, since similar work has been shared here. TLDR is that I trained an LLM from scratch on pre-1900 text to see if it could come up with quantum mechanics and relativity. The model was too small to do meaningful reasoning, but it has glimpses of intuition. When given observations from past landmark experiments, the model can declare that “light is made up of definite quantities of energy” and even suggest that gravity and acceleration are locally equivalent. I’m releasing the dataset + models and leave this as an open problem. You can play with one of the early instruction tuned models here (not physics post trained): gpt1900.com Blog post: https://michaelhla.com/blog/machina-mirabilis.html GitHub: https://github.com/michaelhla/gpt1900 submitted by
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Unmathematical features of math
Thanks to @Gurkenglas for being so wrong I decided to write this. (Epistemic status: I consider the following quite obvious and self-evident, but decided to post anyways. [1] ) Mathematics is a social activity done by mathematicians. — Paul Erdős, probably There've been a few attempts to create mathematical models of math. The examples that come to my mind are Gödelian Numbering (GN), Logical Induction (LI), and to some extent Solomonoff Induction (SI). Feel free to suggest more in the comments, but I'll use those as my primary reference points. In this post, I want to contrast them with the way human mathematicians do math by noticing a few features of their process, the ones that are hard to describe with the language of math itself. Those features overlap a lot and reinforce each other,
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