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It makes me think about how Einstein was famous for making falsifiable real-world predictions to accompany his theoretical work. And, sometimes it took years fo
by philip1209 2y ago
It makes me think about how Einstein was famous for making falsifiable real-world predictions to accompany his theoretical work. And, sometimes it took years for proper experiments to be run (such as measuring a solar eclipse during the breakout of a world war).
Perhaps the opportunity here is to provide a quicker feedback loop for theory about predictions in the real world. Almost like unit tests.
- HanClinto 2y ago> Perhaps the opportunity here is to provide a quicker feedback loop for theory about predictions in the real world. Almost like unit tests. Or jumping the gap entirely to move towards more self-driven reinforcement learning. Could one structure the training setup to be able to design its own experiments, make predictions, collect data, compare results, and adjust weights...? If that loop could be closed, then it feels like that would be a very powerful jump indeed. In the area of LLMs, the SPAG paper from last week was very interesting on this topic, and I'm very interested in seeing how this can be expanded to other areas: https://github.com/Linear95/SPAG https://github.com/Linear95/SPAG
- goggy_googy 2y agoAgreed. At the very least, models of this nature let us iterate/filter our theories a little bit more quickly.
- jprete 2y agoThe model isn't reality. A theory that disagrees with the model but agrees with reality shouldn't be filtered, but in this process it will be.