> cannot do precise things like coding software since humans will never be able to use natural language to specify their requirements.

To your point, this example. The issue expressed here is with humans, not AI. We are still pretty terrible at writing specs. TBF, the AIs are too but that wasn’t being voted on.

Well, I can answer this one: https://stoppels.ch/goalposts/?c=40662140

jerf, 2024: "If it could be solved with a Math Overflow-post level of effort, even from Terence Tao, it isn't what I was talking about as "high level math".

"I also am not surprised by "Consider a generation function" coming out of an LLM. I am talking about a system that could solve that problem, entirely, as doing high level math. A system that can emit "have you considered using wood?" is not a system that can build a house autonomously.

"It especially won't seem all that useful next to the generation of AIs I anticipate to be coming which use LLMs as a component to understand the world but are not just big LLMs."

The voting gloss: "An AI fully solves a research-level math problem on its own, not just suggesting an approach."

Yes, I'm satisfied. I don't even feel bad in hindsight. Coding assistants had a nice, gradual rise up the utility curve. Math went from "lol, can't add two six-digit numbers" to research-math level almost overnight in comparison.

Right - people on HN are generally reasonable about objective things. The vast majority of comments (outside those chosen for this website) are not "AI will never ..." but rather, "AI does not currently ...". Of course the further you go back (I'm seeing a lot of comments from ten years ago!) the more skeptical they get, obviously. That's a funny thing to go back and see with modern context, but it doesn't really call for snideness/mockery (something I think is sadly increasing on HN).

Alternatively, you can bet on your predictions. If you're wrong, you lose money.

I'm not always precise with my language, but business tasks can be pretty broad, I think "arbitrary new tasks" is not an unreasonable rephrasing on my part?

Consider I was replying to this:

> So are we all going to be out of a job?

While your boss now has the capacity to ask Claude to train a new AI model to auto-balance a tower defence game's mob, cost, and tower parameters (I know because I've done it), this only matters if you and your boss are working in a video games company.

If your boss is actually a florist, you care if your boss can get Claude to automate a rose pruning, dead-heading, and fertilising robot.

People are trying, but I don't think they'd be happy with 91.5% success rate: https://www.emerald.com/ir/article-abstract/doi/10.1108/IR-0...

> An LLM today sure can do many many many business-speak conversion tasks

Not reliably, and not without supervision. That's the main point. I'm trying really hard to figure out a workflow that doesn't require me to review the code and I just don't see how it's possible (yet)

You either need a comprehensive test suite (which requires understanding the code in order to create) or you need to review the actual implementation code to make sure it does the right thing

You can't ignore the rest of the sentence. "every other task their business does" "everyone will be out of a job"

This means it has to handle basically all business tasks, so "arbitrary". I'm not sure what percent you have in mind by "many many many" but I would say it can't code half the things you need in an efficient and minimally buggy way.

The relevant condition was met; my misjudgement was that meeting it would require ML to be advanced enough to be able to train on arbitraty tasks from realistic (ie small) numbers of examples.