materials science

“In material science, I think one of the issues is the experimental data is actually quite noisy. So, you know, this is something that you might hear often that simulations and DFT isn't very accurate, and that's true, but maybe one thing that People don't noti…”

“And I think now, maybe because now machine learning really needs this high precision, large data set, there are these bigger efforts trying to create a CAASPP-like database, but it's not there yet.”

“The more training data you put into LLMs, the better results you get, and how much better your results are actually predictable. It's kind of like a power law. This comes back from, you know, a paper from Baidu Research from back in 2016, I think, and it seems…”

“So I think, I can't imagine a future where we completely eliminate lab work. Because, first of all, we don't know if quantum mechanical simulations will ever become good enough to correctly predict experiments, you know, all the time.”

“The better you know a system, The more you can continue optimizing the system, but it doesn't necessarily mean that knowledge will help you discover something different. And I think this is probably why a lot of important discoveries are serendipitous, because…”