Ah, I love your optimism.
2,750 karma · joined October 25, 2018
Ah, I love your optimism.
Too optimistic!
> I'd like to fantasize that it will be replaced with its opposite idea, "Good Engineering is Cool" but so far there is no sign that's likely to happen.
Now that's the right amount of pessimism.
a MISERABLE_LITTLE_PILE_OF_BITS
?!? What a claim!
I truly, honestly loathe the way Python handles for symbolic computation, and digging down I traced my disdain all the way to the fundamental object model of Python; so there is no way some surface-level modification will work for me.
On the one hand, it allows the sloppy "integration" of various systems (like you mention). On the other hand, it is not a real integration, just a patchwork of the worst kind. You never know what kind of interface you will face next, there is no coherence among tools, everything is its own world and you need to translate manually between them. Assuming you know the interfaces beforehand. If not... good luck.
Plus, as a non-expert, you will naturally want to understand more about what you are proving together with the expert. LLMs can help there, too, by carving a path from elementary mathematics to the research problem more efficiently and in a more targeted manner than a generic exposition or survey.
That could give birth to a beautiful research-exposition pair that can benefit both academics and interested laypeople, who have (rightfully, but inevitably) felt excluded from the insights of high level research. I have long hoped for something like that. There, however, the academic must watch the LLM like a hawk, because expository interpretation of results is prime ground for hallucinations, and adversarial agents will not have much effect in improving it.
That point had come some time ago. Nowadays the literature is both enormous and littered with false proofs and an unknown, but nonzero, number of false published results.