Beautiful explanations are lovely when they exist, but we shouldn't wait for them if we can also find the truth through an ugly method.

I used to work at an overnight NOC many years ago, and I literally learned bash and python just to save time so I could spend more time watching netflix or whatever instead of working. Instead, my scripts handled so many alerts that they laid off someone and gave me a promotion to being a sys admin :(

I've been chasing the dream of automating my job away and collecting a paycheck for doing nothing for decades now, and I keep getting promoted...

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it's not a great discovery, it's a pretty minor question, that I thought would be easy and it's not -- i've just been poking off and on at it for weeks, and I'm relying on lean to verify everything. It's actually a quite specific CS-adjacent problem that I came up with trying to write code, that just is hard to solve, and nobody in the literature that I could find has looked at directly. The end result of it will have exactly zero consequences other than proving an interesting lower bound for a question that as far as i can tell, nobody has bothered even looking at but me. The reason it touches on multiple fields is that it's sort of both an algebra problem and a CS problem, so i keep having to flip between them to understand what I'm looking at, and there are a lot of sub-fields that span both that have different tools, and it took me a while to find the right one.

I don't want to call anyone out, but I emailed one fairly famous mathemetician, and he literally said: "This is very interesting, I thought about it for a while, couldn't figure it out, but I thought ChatGPT had an interesting response..." and he linked me to his chatgpt transcript... (which, was actually helpful, because he asked it a better question than I was asking).

I have a suspicion that math will quite soon be exactly like programming and fall to the same machinery that coding is.

One thing that I noticed is that a common workflow I had was isolating hard subquestions in a self contained way and then "surveying" multiple different LLMs in a totally clean context. They would often say: "Oh, this is a obvious example of such-and-such" and immediately clear the barrier.

Interestingly, dogs and cows meet many of ted chiang's requirements for consciousness.

It's not so much the people who _operate_ the machines as the people who _build_ the machines.

I think this is directionally right, but I think there might be a scaling/organization problem for companies, and that the more likely outcome is that _small companies_ are going to start punching way over their weight class.

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It's not really racial discrimination per se, but there's a strong parental-educational/economic/class element which is still tied to race in the US unfortunately.. It's not reason not to have high school calculus but it's still something to keep in account.