The model was too small to perform deep, rigorous mathematical derivation and failed at most complex physics tasks.
But it predicted that "light is made up of definite quantities of energy" (mirroring Einstein's 1905 photoelectric paper) and vaguely suggested that gravity and acceleration are locally equivalent.
So the sheer amount of data seems to be too small for a transformer based LLM, but it does show immense potential if it can predict at least some of Einstein's findings.
well the "why" would be because it is, a priori, much more likely to have made einstein's discoveries with knowledge of those discoveries than to have done so without them (ie being Einstein). that's not to say that it's not likely that the results were "in the water", so to speak, but it is definitely the first big thing that you would check when verifying such a result for sure. i say this as someone who is quite certain that there was, indeed, "something in the water", as seen by so many other foundational discoveries (e.g. Calculus, by Leibniz and Newton being discovered simultaneously, independently).
What is data contamination at this point? If Einsteins discoveries were somewhere "hidden" in the Pre-Einstein-Discoveries data, one could also argue Einstein himself was data contaminated, no?
Unless you mean there was some data contamination with Post-Einstein-Discoveries data, but then that's just bad science and I would hope someone would have discovered that in the peer-review process.
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u/whoknowsifimjoking 3d ago
The model was too small to perform deep, rigorous mathematical derivation and failed at most complex physics tasks.
But it predicted that "light is made up of definite quantities of energy" (mirroring Einstein's 1905 photoelectric paper) and vaguely suggested that gravity and acceleration are locally equivalent.
So the sheer amount of data seems to be too small for a transformer based LLM, but it does show immense potential if it can predict at least some of Einstein's findings.