Feynman: Knowing versus Understanding

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Strong rec dframe · 2015-09 · on “Visions of Future Physics”

You and the person's comment above you are missing the point. First watch : [LINK] (A.I and physics) are quite related and workable ^I reference the above video not because I watched it and thought (hey that makes sense). I reference it because I already felt the same in my work on A.I and felt (wow someone else gets it) Also : [this video] It's good to keep all sorts of working ideas/knowledge in your head when you're working towards solving a problem. All the physics experiments in the world aren't going to give you insight into problems unless you have workable ideas for how to integrate the findings into understanding/knowledge. What people often error in is that you can keep hacking away at

Cites pvillano · 2016-05 · on “The brain is not a computer”

I think you're missing some key points - Good models are important While the traditional computer model is good at explaining behavior, it doesn't help us ask new questions. And no matter how well what we currently know brain fits the traditional computer model, if it can't be used to inspire new questions then we need to explore new models. Feynman explains this better [ [this video] ]. Even though our finite non-magic brains could fit in a computer, a computer isn't the best metaphor. - Computers don't act like brains by themselves. In any FUZZY LOGIC compiled and ran on a computer, all your code is translated into functions and data. LOSSY COMPRESSION is actually the application of experiments

Cites comment_ran · 2020-04 · on “The Wolfram Physics Project”

This reminds me what Feynman talk to us: [this video] > If you can find any other view of the world which agrees over the entire range where things have already been observed, but disagrees somewhere else, you have made a great discovery. It is very nearly impossible, but not quite, to find any theory which agrees with experiments over the entire range in which all theories have been checked, and yet gives different consequences in some other range, even a theory whose different consequences do not turn out to agree with nature. A new idea is extremely difficult to think of. It takes a fantastic imagination.

Cites RichardCA · 2022-08 · on “Dark Matter Doesn't Exist”

There is always a tension in Physics between physical proof and observability on the one hand, and having the right idea, the right intuition on the other. Going back to my Einstein example, there were other Physicists who contributed to Relativity (Lorentz, Minkowski, Poincaré, Fitzgerald) but we give Einstein the most credit because he had the right idea, that it's not enough to treat the speed of light as a constant in your math, you actually have to believe the Universe works that way. One of the stories that gets told is the reason Einstein never got a Nobel prize for Relativity is because the Nobel committee just wasn't ready to give it up and credit Einstein with discovering a new, fu

Cites gloomyday · 2025-03 · on “Learning Theory from First Principles [pdf]”

The pursuit of knowledge is not a linear path. The reason you benefit from deep learning now is because a few people in the past believed neural networks had a future despite not working as well as other techniques such as SVMs. Discovering knowledge and using the knowledge that works best are very different. Your argument remind me from this lecture from Feynman. Quoting him: "...and every theoretical physicist that is any good knows 6 or 7 different theoretical representations for exactly the same physics and knows that they are equivalent... but he keeps them in his head hoping that they'll give him different ideas for guessing." [this video]