And it is an ad hominem - it's nothing more than an allegation impugning the character of libertarians in order to dismiss their arguments. The allegation alone does neither prove anything about the actual character of these people, nor what their view on reality and empathy actually is, nor if that view is actually wrong, nor who is doing the actual projecting here.

So, how is trusting politicians and bureaucrats to be selfless and focused on their duty to society working out for you?

Mind you, not different, or "better" intervention, but less, or even none at all. One could argue the point about libertarianism is that you can't trust the government to do a good job because it is based on force, and not voluntary market interactions, and hence lacks the proper incentives. It's just a bunch of guys on a spending spree with other peoples money, and their incentive is to make as much of it as humanly possible land in their own pockets.

I'm so lucky such a thing never happened to me. The closest thing was a math teacher in middle school asking me about a problem solution of mine in a test, that he had marked "mysterious" (I had to come up with my own solution path during the test because I hadn't memorized the canonical one we were taught). He asked me to explain my reasoning, and when he was satisfied that it was sound he gave me full marks for the question.

Attention e.g. was developed by Dzmitry Bahdanau et al. (those being Kyunghyun Cho and Yoshua Bengio) in 2014 while interning at the University of Montreal.

The insight of the paper you point to was that with attention you could dispense of the RNN that attention was initially developed to support.

https://openreview.net/forum?id=tO3ASKZlok

Edit: But as a comment somewhere else in the tree noted ,,And if it could tell you that then a third party could force you to reveal that you voted "right" as agreed before.`` - I guess everything's trade-offs.

I was reacting to "We're moving to a world where the mechanical part of grinding the code is not worth much". I have the impression that in the past just mechanically grinding the code was less of a thing than it apparently is today. Guidance, sure, but not as much as seems to be common (often necessarily so) today. But I'm sure that varies with a lot of factors, not just the calendar year.

Maybe a bit, but unfortunately sometimes not so much. I recently had an LLM write a couple of transforms on a tree in Python. The node class just had "kind" and "children" defined, nothing else. The LLM added new attributes to use in the new node kinds (Python allows to just do "foo.bar=baz" to add one). Apparently it saw a lot of code doing that during training.

I corrected the code by hand and modified the Node class to raise an error when new attributes are added, with an emphatic source code comment to not add new attributes.

A couple of sessions later it did it again, even adding it's own comment about circumventing the restriction! X-|

Anyways, I think I mostly agree with your assessment. I might be dating myself here, but I'm not even sure what happened that made "coding" grunt work. It used to be every "coder" was an "architect" as well, and did their own legwork as needed. Maybe labor shortages changed that.

LLM code is still mostly absurdly bad, unless you tell it in painstaking detail what to do and what to avoid, and never ask it to do a bigger job at a time than a single function or very small class.

Edit: I'll admit though that the detailed explanation is often still much less work than typing everything yourself. But it is a showstopper for autonomous "agentic coding".