I remember reading about a startup that is basically using LLMs to let you navigate through websites quicker. I'll edit this comment if I remember what it is.
I know you're joking, but I'd like to clarify that Jesus actually said "Let he who is without sin cast the first stone," in case some future archeologist who doesn't know anything about 21st century religions uncovers this article. Nukes didn't exist in the first century A.D.
With Obsidian, I think you can get the Excalidraw plugin to draw images, though it's not inline (it opens a new pane).
You can also use Numba to speed up loops. It's still slower than C, but it's much better than plain Python code, and it's really easy to implement (just import numba and put a @numba.njit() before your function).
Why did you decide to only use rotation matrices instead of any invertible matrix? If you're trying to find a new basis to work in, wouldn't any invertible matrix work just as well?
I agree with your fundamental claim that there are lots of top tier students going to non-top schools, but I think you focused too much on SAT scores and GPA. Right now, there are so many kids getting top scores (about 5,500 students every year get a 36 on the ACT, and about 4500 students get a at least a 1570 on the SAT), test scores just aren't enough to determine who gets in. Instead, admissions officers use a "holistic" approach, which seems rather noisy, but does factor in other real accomplishments, like getting to the IMO or starting a million dollar business.
My opinion is that we need harder standardized tests. (Maybe we on LessWrong could create one!) Until that occurs, though, I don't think SAT scores are enough to decide that "The 25th percentile of students at University of Maryland, College Park are as good as the 75th percentile of students at Harvard".
I'm not sure how you concluded that James 5:12 says you should not lie under any circumstances. I've always interpreted it as condemning giving oaths, especially oaths on things you have no control over.
But above all things, my brethren, swear not, neither by heaven, neither by the earth, neither by any other oath: but let your yea be yea; and your nay, nay; lest ye fall into condemnation. (James 5:12)
Did you mean to quote somewhere else?
(To Policymakers and Machine Learning Researchers)
Building a nuclear weapon is hard. Even if one manages to steal the government's top secret plans, one still need to find a way to get uranium out of the ground, find a way to enrich it, and attach it to a missile. On the other hand, building an AI is easy. With scientific papers and open source tools, researchers are doing their utmost to disseminate their work.
It's pretty hard to hide a uranium mine. Downloading TensorFlow takes one line of code. As AI becomes more powerful and more dangerous, greater efforts need to be taken to ensure malicious actors don't blow up the world.
Imagine playing your first ever chess game against a grandmaster. That's what fighting against a malicious AGI would be like.
Donald Knuth said, "Premature optimization is the root of all evil." AIs are built to be hardline optimizers.
Source: Structured Programming with go to Statements by Donald Knuth