Chinjut

Yes, and keep in mind also the article author is chair of machine learning at University College London and was a core member of the AlphaGo team at DeepMind.

If only we could all snap our fingers and have our dream jobs.

I don't want to fly planes, be in a traveling circus, or be a chef. There are things I want to do, but the money spigots of our society aren't lining up to pay me to do them. I'm all for obtaining optionality through universal income. But optionality means also the optionality to retire (today, not decades from now).

Retirement doesn't mean you can't work. It means you don't have to. It means you can work for yourself on your own interests instead of for some other boss who tells you what to do.

This is unreadable. What is this?

These are pretty close to each other, to the point where I wouldn't bother strongly distinguishing them.

Suppose we have foldr as in [A] -> B -> ((A, B) -> B) -> B, foldl as in [A] -> B -> ((B, A) -> B) -> B, and reduce as in [A] -> ((A, A) -> A) -> A.

Then we have foldr list value operator = reduce [\b -> operator a b | a <- list] (.), foldl list value operator = foldr (reverse list) value (flip operator), and in the case of a finite non-empty list and associative operator, we have reduce list operator = foldr (tail list) (head list) operator = foldl (init list) (last list) operator.

So these are all basically slight re-parametrizations of each other.

People always bring up the Continuum Hypothesis as though it has something to do with Gödel's incompleteness theorems, but it doesn't really. The Continuum Hypothesis being neither proven nor disproven by some particular axioms is a similar phenomenon as that the group axioms neither prove nor disprove commutativity, the ordered field axioms neither prove nor disprove the existence of a square root of 2, etc. There's no particular reason to expect any particular formal system to be complete, sans some demonstration that is.

Gödelian incompleteness is the specific kind established by Gödel's proof, where theory T can't prove Con(T) without being inconsistent. But the inability of ZFC to consistently decide the Continuum Hypothesis is established in a completely different manner, with the Continuum Hypothesis not consistently decided by ZFC + Con(ZFC) either, or any such thing.

Much though jobs may involve those things, it has been rare for me to be in a position where management has valued those things to an extent where they would discern between me and a frontier reasoning LLM's capabilities on those same decisions.

Yes, on that occasion and now on this one. As a mathematician, my fears have been amped up yet further by this new development.

What is going to become of life for those of us who do not work at AI labs and are unlikely to be hired by AI labs, despite all the years we put into learning math, coding, etc? Those of us who made the mistake of studying anything other than machine learning. How will we make a living? (We don't live in a world that seems likely to distribute gains widely instead of largely to the handful of already mega-rich.)

Why not transition to a time where we do less jobs? Why should we have to carve out extra time in addition to a just plain work job?

This is a repo for a new thing that is not identical to LaTeX, but intended as an improvement upon it. Typst seems apropos to bring up in related conversation.

Perhaps it was childish to listen to advice, sure. I was a child when I made my formative choices; I was a teenager in college and so on. I can't go back in time now.

Yes, these problems are systematic. That is what I am saying. That doesn't make it any nicer.

I am in my forties.

I sympathize with those people too. I have the same concerns for them.

Should I go back in time and know the future?

I'd be happy to not work anymore with a strong welfare system redistributing society's gains to the leisured masses, but absolutely nothing I've seen of the direction of politics in any recent years gives me hope for this kind of situation coming about.

What is going to become of life for those of us who do not work at AI labs and are unlikely to be hired by AI labs, despite all the years we put into learning coding, math, etc, as we were told to do? Those of us who made the mistake of studying anything other than machine learning. How will we make a living? (We don't live in a world that seems likely to distribute gains widely instead of largely to the handful of already mega-rich.)

Why would landlords not seek the highest possible rent without rent control?

Haskell, Lean, and Agda too. But even if Python were the only one, it wouldn't be weird to someone for whom this was their first programming language. It would just seem the way programming languages are. There's nothing intrinsically weird about indentation being significant. It's quite visibly part of the code you write and read.

I hate Python and I'm onboard with putting it down in many ways, but significant whitespace isn't weird in a first programming language. It's only weird if you've absorbed from some other language the convention that whitespace shouldn't be significant.

People love to say the Unix philosophy is "Write programs that do one thing and do it well". But this does not really seem to me to really match Unix practice. And it doesn't match LLMs either, as the article notes.

(So what is this article talking about? I guess it's talking mainly about "Write programs to handle text streams, because that is a universal interface".)

Regulation, antitrust, regulation, antitrust.

iOS allows something similar because this is iOS. iOS allows something exactly the same because this article is about iOS.

Yes. And math too. I think there's lots of beauty remaining in understanding these things, and using that understanding to craft things cleanly rather than as slop, but no one will pay us to do it, so we will never have the opportunity to do it.

I don't understand what you mean by "too good to be true" here. You mistakenly think the women you have good first dates with are fraudulent in some way?

The result in [1] is not progress on the Riemann Hypothesis. It's another fine result, but it's not progress on the Riemann Hypothesis. You could prove 100% of zeros are on the line and it wouldn't show the Riemann Hypothesis. 100% of natural numbers are composite in this same asymptotic density sense, and yet that doesn't prove that all natural numbers are composite.

For 58 years now.

Indeed. Money over everything. It is absurd to complain about decreasing quality of a product that makes increasing money for increasingly rich people (thus, by definition, better).

This article appears to be AI-written slop.