A relentless low IQ person with broad textbook knowledge and no need to sleep, I guess?

Look cmon, this is pure cope. The problems it has solved in TCS are far from trivial, with plenty of smart people making their careers in trying to solve them. The techniques these LLMs are using are non-trivial, and not just brute force.

You mean techniques like using the prompt of mathematicians in the training set and brute force a solution before they publish?

No, I mean the techniques in the proofs produced by these LLMs.

I'm more interested in the techniques used to generate these proofs, and how they can be improved to be as reliable at solving a broader class of problem than already formalized mathematical conjectures.

These are pretty nice examples, as both SQL and Prolog can only be used well for anything non-trivial when you're aware of how the result you're asking for is going to be figured out.

Releasing the code on GPL was probably notable too.

Notable, true.

But i dont think the outcome is comarable to the TITANIC amount of investment s Valve have been doing in the last 15 years or so.

ah yes, decades of doom running even on toasters... but no, a store and drm daemon is better.

Debian is currently on 3.14.8.

Prove it

Debian repositories are public. You can just look in there.

Then do instead of telling lies.

It's not apt not being smart that can cause troubles when mixing packages from various suites. There's no reason to mix in cases where you can just use backports instead.

The only thing that changes over time is that you need to know more about the topic in order to be able to spot it.

> everyone thinks music peaked when they were in high school

Nah. Music clearly peaked about 10 years before I was born.

Now run LLM inference on it.

butterfly Is this AGI?

this is the sensation I get when I run nested VMs.

I've been using touchscreen laptops for more than a decade now. It's been really useful when working on mobile stuff and occasionally handy in some games or when sketching something, but other than that - it just stays unused.

> But nobody says you have to stop there.

Yeah, but what's more likely to happen is that when you look inside the code you see thousands of lines of code of a handrolled parser and when you ask "why would you write your own rather than use some existing one here?" you only get silence in return.

I don't really generate big chunks of code, but in general I found AI outputs to be quite sensible. It knows what the main modules are and uses them, I've not seen any as egregious as making a JSON parser from scratch without a need.

Maybe not a JSON parser in particular, but I've already seen a fair share of MRs that contained many thousands of lines that no human would have ever written without stopping to ask "do I really need to do it?". LLMs aren't bothered.