I have always assumed that Alan Kay compared Lisp to Maxwell's Equations because of the similarity between the interplay of eval and apply in Lisp on the one hand, and the interplay of the electric and magnetic fields in Maxwell's equations on the other.
It's confusing because different people mean different things when using political terms. The political compass (https://www.politicalcompass.org) has two axes: left-right and libertarian-authoritarian. On it, socialists are definitely left wing (and communists far left), regardless of what the left/right wing meant at the time of the French Revolution.
I'm interested in how they work, but building anything like them, given the hardware I have, would be impractical. I've seen others use them, including to answer some questions I had, but the answers they gave were obvious, unhelpful, or wrong.
Even if they become more reliable, I like to understand and work things out for myself, rather than just be given the answer.
The Dartmouth Summer Research Project on Artificial Intelligence was in 1956, before I was born. AI itself is even older than that (e.g. William Grey Walter's robots, Elmer and Elsie in 1948), but it was called cybernetics back then. I've been doing symbolic AI, on and off, since the 1980s.
I assume, though, you mean LLMs. I haven't used them first hand, but I have fairly recently implemented a multi-layer artificial neural network in C, mostly as a learning exercise, but as I had previously built a speech spectrogram in Lisp, I thought I'd try to use it to recognize phonemes, with one hidden layer. The Lisp communicated with the ANN via a Unix pipe. It worked reasonably well for just vowels, but when I added other sounds (e.g. l, r, s, z), its performance deteriorated. I think the C is bug free, but I don't know an easy way to train the ANN. I've tried adding to the training set, adding an extra layer, changing the number of neurons in the hidden layer. The usual debugging skills don't seem to help there.
It's in the name "Hacker News". Hackers are people who enjoy doing the programming themselves, because they get satisfaction from it. Often they program in their spare time, and sometimes what they develop has little to no practical value, and is done as a learning exercise. Using AI would defeat the purpose for them. If they're forced to use AI in their job, it decreases their job satisfaction.
There are others who just want a problem solved, and it doesn't matter to them how the program which solves it gets written, as long as the program (appears to) work and it's done as quickly as possible, so they outsource the development to AI. That is not hacking.
General Relativity. It explained the anomaly in the precession of Mercury's perihelion, and the bending of starlight by the Sun (double the value predicted by Newton's law).
We agree on Algol, Lisp, Forth, APL, and Prolog. For ground-breaking functional language, I have SASL (St Andrews Static Language), which (just) predates ML, and for object oriented language, I have Smalltalk (which predates Self).
I also include Fortran, COBOL, SNOBOL (string processing), and Prograph (visual dataflow), which were similarly ground-breaking in different ways.
Sadly, not part of this course, though Lisp and Prolog are very useful for other things. C's fine for building neural networks from scratch, and you can glue different subsystems together to make anything more complex than that using Python.
Written Chinese stayed the same while the spoken language evolved from the 5th century BC until the 1911 revolution, after which people began writing Chinese the way it's spoken in Beijing. So there's a sharp dividing line just over 100 years ago; Literary Chinese is still taught in school but without that you'd have trouble understanding it.
"But we found that Trump’s so-called “reciprocal” tariff rates weren’t based on tariffs that other countries charged on goods coming from the U.S. Instead, the Office of the U.S. Trade Representative came up with the rates by dividing the size of a country’s trade imbalance with the U.S. in goods by how much America imports in goods from that nation. "
It's well worth a read for anyone who wants to implement their own Lisp. I'd say it's the precursor of Lisp In Small Pieces by Christian Queinnec though. I have copies of both.
Newton wrote, "That one body may act upon another at a distance through a vacuum without the mediation of anything else, by and through which their action and force may be conveyed from one another, is to me so great an absurdity that, I believe, no man who has in philosophic matters a competent faculty of thinking could ever fall into it."
Yes, the principle of relativity was known to Newton, but the other idea, that the speed of light is the same in all reference frames, was new, counterintuitive, and what makes special relativity the way it is.
It isn't an anteceent, it's part of special relativity, discovered by Lorentz. It's well known that special relativity is the work of several people as well as Einstein.