alecbz

I have a suspicion that the objective nature of most AI benchmarks is tapering over the kinds of reasoning mistakes LLMs continue to struggle with.

If you give LLMs a clearly defined spec with clear, objective acceptance criteria that the LLM can evaluate itself against, they tend to do well. But I think they struggle with more ambiguity and require a lot of handholding around judgment. That kind of disambiguating work is often baked in to the definition of a benchmark.

> The overwhelming majority of bad driving is caused by alcohol and other drugs, drowsiness, and inattentive driving.

> Sober, well-rested human beings who pay full attention to the road are surprisingly good drivers, to the point where I'm not actually sure that robotaxis can reliably beat them yet.

Including "inattentive" and "pay full attention to the road" feels a little tautological? Like, what's your definition of "inattentive"? More or less by definition, if there's an accident, someone was "inattentive" and didn't do the correct thing. Unless they were actively malicious and trying to hurt someone, which I agree would be a tiny minority of car accidents.

> that's primarily a human concern that's unrelated to the final output.

It's an LLM concern too. LLMs seem to do better with well-organized codebases, just like the humans they were trained on.

In the long-long-term, self-driving will get good enough and people will be relying on it so thoroughly that allowing people to drive on their own, with barely any practice, will probably be more risky than it's worth. In say, idk, 100 years (probably sooner), I doubt people will be able to drive their own cars in the way they do today.

Normalize price discrimination

Though actually I’d suspect a lot of that is just rising costs (rent)?

Knowing to flag down a waiter is probably a big part of the equation. In the US waiters will generally come on their own to take your order fairly quickly and so we’re less used to flagging them down. And in a lot of places in Europe waiters won’t ask to bring the check, it’s on you to ask for it.

At restaurants at least, most people I know just default tip 20% and only adjust up or down in pretty rare circumstances. Maybe it’s different in other parts of the US or for other generations, but I recall studies supporting that people generally have a set percent they always tip.

Software engineering has been getting more efficient for decades and over that time there’s been a massive increase in the number of software engineers.

The Mythical Man-Month describes teams of ten engineers operating before the Internet. Today (pre-LLMs) that’s probably 1-2 people.

> we won't even need programming languages

> just do “natural language” to a programming language

> Germany

The HRE for several hundred years could probably seen as a proto-Germany.

Interesting -- is there any term referring to the executive, legislative, and judicial functions collectively?

> At least the countries in the EU should have separation of powers, and the judicial (the courts) are independent from the government

In the US "government" generally refers to all three branches; is that not the case in Europe?

OOC what's your other income from?

Honestly, either feels like an improvement over now.

If LLMs actually get good enough to really automate the production of good software, it'll be disruptive for the industry and we'll all have to adjust a lot more than we already are, but I think it'd be on-net good for it to be cheaper and easier to produce good software. And, in the past, such changes have only increased the size of the tech industry.

Or, if we finally realize LLMs aren't going to get there, there'll be at least increased demand for actual software engineers to clean up all the LLM mess.

But right now is the worst, where the industry feels like it's lying to itself about what these tools are capable of.