philip_b

Wikitag Contributions

Comments

Sorted by

I think the way to learn any skill is to basically:

  1. Practice it
  2. Sleep
  3. Goto 1

And the time spent in each iteration of item 1 is capped in usefulness or at least has diminishing returns. I think this has nothing to do with frustration. Also, I think reminding yourself of the experience is not that important and I think there is no cap of 1 thing a day.

Ah, ok, I didn't know when exactly Milei has started being the president. I didn't pay attention to the jump. The original post said "1 year" so I counted off one year (right after the jump) and saw that the slope was smaller than before. But you're right, yeah. But I must also point out that this is the official rate and idk of anyone actually uses it.

Through conversations with locals, I understood why. President Milei's initial action was severely devaluing the Argentine Peso, making dollar-denominated goods more expensive.

Not true. A year ago blue dollar rate was approximately the same as now [1], and the official USD-Peso rate has been rising more slowly than before Milei. [2]

m - often used together with n to denote the height and width of a matrix

At first I disbelieved. I thought A > B. Then I wrote code myself and checked, and got that B > A. I believed this result. Then I thought about it and realized why my reason for A > B was wrong. But I still didn't understand (and now I don't understand either) why the described random process is not equivalent to randomly choosing 2, 4, or 6 every roll. I thought some more and now I have some doubts. My first doubt is whether there exists some kind of standard way of describing random processes and conditioning on them, and whether the problem as stated by notfnofn. Perhaps the problem is just underspecified? Anyway, this is very interesting.

If you think you might be in a solipsist simulation, you might try to add some chaotic randomness to your decisions. For example, go outside under some trees and wait till any kind of tree leaf or seed or anything hits your left half of the face, choose one course of action. If it hits the other half of your face, choose another course of action. If you do this multiple times in your life, each of your decisions will depend on the state of the whole earth and on all your previous decisions, since weather is chaotic. And thus the simulators will be unable to get good predictions about you using a solipsist simulation. A potential counterargument is that they analyze your thinking and hardcode this binary random choice, i.e. hardcode the memory of the seed hitting your left side. But then there would need to be an intelligent process analyzing your thinking to try and isolate the randomness. But then you could make the dependence of your strategy on randomness even more complicated.

Nice. I have a suggestion how to improve the article. Put a clearly stated theorem somewhere in the middle, in its own block, like in academic math articles.

Why do you hate earworms? To me, they are mildly pleasant. The only moments when I wish I didn’t have an earworm happening at that moment is when I’m trying to remember another tune and the earworm for musicianship purposes and the earworm prevents me from being able to do that.

Answer by philip_b1-3

Instead of inspecting all programs in the UP, just inspect all programs with length less than n. As n becomes larger and larger, this covers more and more of the total probability mass in the up and the total probability mass covered this way approaches 1. What to do about the non-halting programs? Well, just run all the programs for m steps, I guess. I think this is the approximation of UP that is implied.

Well, now I'm wondering - is neural network training chaotic?

Load More