Hi Ramin, On Sun, Jun 13, 2021 at 5:27 PM Ramin Barati <[email protected]> wrote:
> > Right now I am trying to provide for myself a stable job and to set my > foot on a firm ground financially. I think that I am living that part of a > man's life in which one needs to bear the fruits of his first endeavors. > The geopolitical situation in the middle-east and especially Iran is of no > help though. Nevertheless, I am always interested in the discussions in the > mailing list and try to follow them as much as possible. > Food, a place to live, income, savings are vital. Spread the word. Talk to people with political views opposite of your own. Befriend them, even. Talk them over to your side. Gently; don't get shot. Geopolitics should not prevent you from being a good and active citizen. > > On another note, I also have been reading about quantum probability > recently. While the subject is certainly out of my reach right now, I think > that I have found something interesting that I would like to share with you > and Linas and ask if you see any potential there. Before that I would like > to give my thanks to Linas for introducing the reading materials on these > subjects and to tell you that I would surely look them up. On the subject > of Riemannian surfaces, I had a hunch that the subject is important but I > lack the math to read the literature. I figured that I need to get a better > understanding of vector fields and geometric algebra and I am reading a > book called "Geometric Algebra for Computer Science". I would be glad if > you could suggest an introductory book on the subject of Riemannian > surfaces itself. > The more you can read, the better. I would normally recommend "Compact Riemann Surfaces" by Jurgen Jost. It's a Springer textbook. If you look hard enough, you can find a PDF online. My only concern is that it might be a bit too advanced for you. Try it anyway, see how far you can get. Skip the proofs, on first reading. > > The idea is that the output of a classifier is a quantum probability > distribution. So a classifier is something like a Dirichlet process but for > quantum probability distributions. The output of a k-class classifier is a > pure complex antisymmetric k-by-k matrix and using matrix exponential we > can map that matrix to a matrix in SU(k). > Yuck. Stop right there. I know that you don't know the theory of Lie algebras, so down this path you will only find trouble and flawed thinking. In grad school, I had a professor, P.G.O. Freund, and one day, instead of lecturing, he went on a tirade. I did not like it much, it felt like a waste of my time. It took me 2-3 decades to understand what he was saying. I hope it won't take you that long. He drew three symbols on the blackboard: the delta, the nabla and the D'Alembertian (a square). He said: "The people who use a nabla are like that symbol - precariously balanced on its tip, using a tiny amount of knowledge at their base, to reach up into the clouds to explain everything. You don't want to be like that. Stay away from people like that. They are no good. The people who use the delta have a broad base of knowledge, and a sharp pointy tip: they can use their extensive base knowledge to make precise, pointed observations. You want to be like that. The people who use the D'Alembertian are the best: not only do they have a proper foundation on which to build, but they are able to accomplish many things with their knowledge." See what the problem is? I thought to myself "I came to class to hear about this? What a waste of time!" -- but he was right. It took me a few decades to develop a broad base of knowledge. Alas, I am now old, as I mis-spent my youth. If you want to be good at stuff, read widely. But, more importantly, establish a firm foundation. Study the basics. Careful getting tangled in fancy-pants theories before you first have complete mastery of the basics. Once you know the basics, the fancy stuff will then come easily, and quickly, without a struggle. I listened to another famous mathematician proclaim that research should be like paddling a canoe: mostly a leisurely paddle down-stream, with occasional furious paddles upstream. (Maybe this was Raoul Bott? I don't recall.) -- Linas -- Patrick: Are they laughing at us? Sponge Bob: No, Patrick, they are laughing next to us. -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CAHrUA36hZT-NPQ-qFaCMHsOjR_SX-5R3KqMXyNVaD%3DmsG9icNw%40mail.gmail.com.
