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Terence Tao: Mathematics in the Age of AI [pdf]

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Re: Terence Tao: Mathematics in the Age of AI [pdf]

#41

Post by NitpickLawyer »

megaloblasto wrote: post #5

This is the thought process that I fail to see many people take (both here and other places). AI is changing many fields, ok what does that look like and how do we adapt? What can we do now that we couldn't before? What skills should I learn to adapt to this changing world? I think this is how we move forward. If you can get past the scary aspects of AI (not talking about datacenters or billionaires, that is a differ…

> fail to see many people take (both here and other places)

A lot of very vocal people have already taken a position (as in ideology) on this, and are very reluctant to change it, even when faced with obvious evidence to the contrary. It's like anonymous gary marcus clones. Every time something cool happens, they move the goal posts. Even in this thread there's someone saying that recent math advances are "models just brute forcing until something sticks". shrug

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#42

Post by layer8 »

pyentropy wrote: post #11
doomrobo wrote: post #3

Recording of a talk with the same title. I’m not certain it’s the same content as the linked PDF though https://youtu.be/mS9Lr43cIB4

Note that the SAIR lecture is from 6 months ago, this Beamer presentation is from 2 days ago.

> Beamer

Spotted the German guy. ;)

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#43

Post by andyjohnson0 »

hannofcart wrote: post #27
vouaobrasil wrote: post #22

Earlier quoted context omitted.

Well, that's what AI does. It makes everything about the final product and nothing about the enjoyment of the process. Now a lot of people here will say "you can still read the AI results and enjoy math on your own time", but that is completely at odds with how most people do things: a large part of most people's enjoyment comes from sharing results with others and AI devalues that. People can't help but feel less im…

> The whole point of discovering knowledge is to enjoy the process and share that with the world to create hope an optimisim in it, not to product like a factory. This is the crux of everything you've written and I strongly disagree. The purpose of knowledge is the sheer power it brings, and if there's factory scale churning out of it, I'll gladly take it. As a closer analogy, consider this probability (I'll be steal…

> The purpose of knowledge is the sheer power it brings

A dismal prospect.

When knowledge is acquired at a human scale, and under the influence of a human culture, then extraordinary things can happen. Agriculture, the transistor, Gödel's theorems.

When knowledge is "churned out" at "factory scale" then human flourishing isn't even a by-product.

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#44

Post by andybak »

light_triad wrote: post #18

This is the taste question applied to Mathematics in a similar way it's been applied to code. In an era of AI abundance, the question becomes what the goals are and what gets verified and digested (adopted by users). Goodhart’s law: the goal of producing code is not just about maximizing the number of tokens used, but the productivity gains and economic surplus. This could serve as the template for any field in the a…

> but the productivity gains and economic surplus.

I think you might be missing out vast swathes of human experience here. Some things are about joy, or god help me - fun.

(For the record I think AI has a role to play here as well)

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#45

Post by jdm2212 »

layer8 wrote: post #42
pyentropy wrote: post #11

Earlier quoted context omitted.

Note that the SAIR lecture is from 6 months ago, this Beamer presentation is from 2 days ago.

> Beamer Spotted the German guy. ;)

the software that generated the slides is called Beamer https://en.wikipedia.org/wiki/Beamer_(LaTeX)

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#46

Post by gravypod »

vouaobrasil wrote: post #24
megaloblasto wrote: post #5

This is the thought process that I fail to see many people take (both here and other places). AI is changing many fields, ok what does that look like and how do we adapt? What can we do now that we couldn't before? What skills should I learn to adapt to this changing world? I think this is how we move forward. If you can get past the scary aspects of AI (not talking about datacenters or billionaires, that is a differ…

As a (sort of former) mathematician myself, I can say two things. First, one of the most exciting parts of mathematics is to see what other people can do with it and the results they obtain, and learning from them (and sharing with them in return). And second, I am completely uninterested in what AI has to offer. To me (and most normal people) knowledge pursuit is about inspiring others with discovery and the intelle…

> And second, I am completely uninterested in what AI has to offer. To me (and most normal people) knowledge pursuit is about inspiring others with discovery and the intellectual joy of doing something yourself.

I often hear that people are "uninterested in what AI has to offer" but I don't really understand it. I understand this is a mix of ethics and engineering that I don't often engage with but I do not understand why someone would explicitly state that they are not interested in improvements to the world based on the source of the improvement.

The comment I am replying to did not say that LLMs cannot create improvements. That would be a different discussion! It instead says that it does not care about fruits born from the LLM tree.

It seems highly likely to me that through a combination of LLMs and traditional optimization software like vizier that manufacturing, industrial processes, scientific research, or even bakeries will see some improved output through the mixing of domain specific expertise and enablement from LLMs.

I think right now, in the extreme hype environment we live in where people say AI will do everything and take over the world and take your job and give you nothing, people are burned out. Once we get past this point through I am hoping people start talking about what LLMs can do that will actually improve our lives and which can actually work. Much of what people tell me LLMs can do, don't actually work reliably. But there are many cases where LLMs have been a step function in capabilities.

Examples: OCR that really works, fuzzy search, fixing scoped bugs in software, building prototypes of software, etc.

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#47

Post by bobmarleybiceps »

I feel like at a certain point, there's is not necessarily a reason to go through the peer review publication process for some AI proofs.

Not because "ai bad," but because at some point AI outputs should probably just be treated like public knowledge. Specifically stuff that's provable by "AI please output lean showing X is true," where anyone could kind of reach the same conclusion by asking ai.

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#48

Post by skybrian »

bobmarleybiceps wrote: post #47

I feel like at a certain point, there's is not necessarily a reason to go through the peer review publication process for some AI proofs. Not because "ai bad," but because at some point AI outputs should probably just be treated like public knowledge. Specifically stuff that's provable by "AI please output lean showing X is true," where anyone could kind of reach the same conclusion by asking ai.

You don't want people to have to rerun the prompt though. Collaborating on a registry for proven results makes sense.

This probably looks like contributing Lean code to an open source project and writing docs.

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#49

Post by 2snakes »

knollimar wrote: post #35
2snakes wrote: post #12

Earlier quoted context omitted.

Open source intellectual power though. The promise of the personal computer.

Whats personal about a datacenter?

You could have said the same thing about mainframes in the past? I am talking about smaller open source models not huge ones that need spaceships to run.

Re: Terence Tao: Mathematics in the Age of AI [pdf]

#50

Post by jpleyden98 »

vouaobrasil wrote: post #24
megaloblasto wrote: post #5

This is the thought process that I fail to see many people take (both here and other places). AI is changing many fields, ok what does that look like and how do we adapt? What can we do now that we couldn't before? What skills should I learn to adapt to this changing world? I think this is how we move forward. If you can get past the scary aspects of AI (not talking about datacenters or billionaires, that is a differ…

As a (sort of former) mathematician myself, I can say two things. First, one of the most exciting parts of mathematics is to see what other people can do with it and the results they obtain, and learning from them (and sharing with them in return). And second, I am completely uninterested in what AI has to offer. To me (and most normal people) knowledge pursuit is about inspiring others with discovery and the intelle…

I don't see how AI in maths stops anyone from pursuing any sort of intellectual learning themselves.

In the same way children still learn their times tables even though calculators can do the job better.

To me (and most normal people) knowledge pursuit is about inspiring others with discovery and the intellectual joy of doing something yourself.

I disagree, for a lot of people knowledge pursuit is about the knowledge and the results of that knowledge. IE the end result is what matters.

As a simple example, Pythagoras's theorum is useful to lots of people all over the world as in the actual equation. I'm not sure most for most people that the knowledge that Pythagoras himself went through an intellectual journey to discover the theorum is more important than the equation itself.

If we use a thought experiment to say that instead of Pythagoras discovering the theorum it was actually discovered by artificial intelligence do you think most people would care? I would say not.

I think a lot of people like the idea of being at the forefront of their field and their intellectual contributions being able to push the frontier foreward. If AI simply gets good enough to largely absorb the frontier they don't find as much fun in rediscovering what AI has already discovered. People forget however, this has already happened to many fields, chess being one example.

Whether AI gets there with maths is an open question but to say AI has no value in maths whatsoever is to say that the practical implications of a better understanding of maths that AI could potentially give us is worth nothing.

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