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Comment by Loquebantur | Hacker News Reader

You cannot use mathematics without understanding it.

It doesn't help you that AI understands it, when you don't. You are the one getting screwed over by others who understand statistics better than you do.

When you're rich enough, you can pay others (or AI) to protect you. But then you're dependent upon them.

So, under a transactional model of social relationships, you are in an arms race over raw intelligence and competency/data. With only one winner, who takes all in the end.

Logically, most people have already lost in that game, so why keep playing that nonsense?

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You can't use mathematics without understanding it?

Let's say GPT-23 Astra grinds away for a full month one day and out pops a warp drive. Our best physicists ask it to explain. The resulting stream of text is essentially incomprehensible. But, they build a scale model at its direction to test and sure enough it does the Kessel run in 12 parsecs.

Are you saying we shouldn't hop aboard the USS Enterprise and check out Alpha Centauri because we don't understand the math?

I think what's really happening here is that there's an ivory-tower academic class that feels entitled to make their living at public expense thinking about and writing about their topic of interest, and along comes a new tool that's changing that dynamic up. Meanwhile, in the real world, the value remains with people who can take whatever the tool of the day is and do useful things with it. Which, I think, is why despite all the talk the only professional job losses blamed on AI appear to largely be companies that had a failed strategy of some sort or another and used AI as a boogeyman to do the layoff that they needed to do anyway. To people living in the private sector this isn't seen as a dangerous invader, LLM's are productivity multipliers.

> LLM's are productivity multipliers.

For automated AI shilling ...

>Let's say GPT-23 Astra grinds away for a full month one day and out pops a warp drive.

In the real world, the frontier labs are still hiring lots of humans for business and software roles (https://openai.com/careers/search/) despite being better positioned than anyone to automate them away with their world-beating models and save a bunch of salaries.

That seems wrong unless you have an unusual definition of "understanding":

* Lots of people use math for calculations without having proven any theorems.

* You can understand a mathematical statement without understanding or even having a proof. There are proofs built on the axiom of choice and conjectured results.

I think you can understand* math in general. I think not understanding something it's a matter of presentation. Also I think the presentation can be improved. A good-quality AI can do both, hence it can get a presentation that you can understand.

Yet this has zero utility (other than your own satisfaction). Once you understand something, you will likely not even do a better job at explaining it to someone else, so the utility is strictly limited to yourself.

So even ignoring ability to understand the problem is the cost/efficiency of understanding (and applying it).

I agree with your other statements, but I feel you're suggesting the non-sense is scoped to just math. It's not it's almost everything that we do (exceptions are social interactions including care taking, etc.)

So in this frame your "nonsense" is (almost) everything that we do. Personally I'd like to keep doing things.

"in mathematics you don't understand things, you just get used to them"

John von Neumann

then, I think we can get used to math in general

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