[WhitneyLand]

Use ChatGpt.

Screenshot the math, crop it down to the equation, paste into the chat window.

It can explain everything about it, what each symbol means, and how it applies to the subject.

It’s an amazing accelerator for learning math. There’s no more getting stuck.

I think it’s underrated because people hear “LLM’s aren’t good at math”. They are not good at certain kinds of problem solving (yet), but GPT4 is a fantastic conversational tutor.

[godelski]

Don't suggest this. While I agree it can be helpful, the problem is if you're a novice you won't be able to distinguish hallucinations. Which in my experience are fairly common, especially as you do advance topice. If you got good math rigor then it's extremely helpful, because often things are hard to exactly search, but it's a potential trap for novices. But if you have no better resource, then I can't blame anyone, just give a warning to take care.

[WhitneyLand]

That’s kind of like telling people not to go online because you can’t believe everything you read on the Internet.

What proportion of the problems you’ve encountered were with the free version vs premium? It’s a huge difference and the topic here is GPT4.

Also since it is fairly common for you are there any real world examples you can share?

[godelski]

> That’s kind of like telling people not to go online because you can’t believe everything you read on the Internet.

Uhhh... it's like telling people to trust SO over reddit, especially a subreddit known to lie.

> What proportion of the problems you’ve encountered were with the free version vs premium? It’s a huge difference and the topic here is GPT4.

Both. Can we stop doing this? This is a fairly well established principle with tons of papers written about it, especially around math. Just search arxiv, there's a new one at least every week

[WhitneyLand]

I’ll take that as it happens so infrequently with GPT4 you have no illustrative prompts that can be shared.

There have not been tons of papers written about this.

You seem to be conflating papers about GPT4 as a solver with it as a math tutor. It’s a completely different problem space.

[godelski]

Or you can check the front page:

https://news.ycombinator.com/item?id=38845878

(older but similar) https://news.ycombinator.com/item?id=37904047

[WhitneyLand]

I don’t get the relevance those seem to be security related?

My main point consistently has been that GPT4 can be an invaluable resource specifically for learning math subjects.

I am not aware of any papers, studying people using it as a conversational tutor for learning math and having problems with hallucinations.

[CamperBob2]

It works better than you think, as long as you use GPT 4. See my answer to the other person (https://news.ycombinator.com/item?id=38837646).

A lot of negativity comes from people who goofed around with 3.X for a while, came away unimpressed, muttered something under their breath about stochastic parrots or Markov chains that sounded profound (at least to them), and never bothered to look any further. 4 is different. 4 is starting to get a bit scary.

The real pedagogical value comes when you try to reconcile what it tells you about the equations with the equations themselves. Ask for clarification when something seems wrong, and there is an excellent chance it will catch its own mistakes.

[godelski]

That answer isn't very compelling as it is one of the most well known equations in ML. There are some very minor errors but nothing that changes the overall meaning. But you even seem to agree with me in your followup: don't rely on it, but use it. I'm only slightly stronger than you.

And stop all this 3.5 vs 4 nonesense. We all know 4 is much better. But there's plenty of literature that shows its limits, especially around memorization. You also don't understand stochastic parrots, but in fairness, seems like most people don't. LLMs start from compression algorithms and they are that at their core. But this doesn't mean it is a copy machine despite the NYT article but it also doesn't mean it is a thinking machine like the baby AGI people. Truth is in between but we can't have a real conversation because hype primed us to just bundle people into two camps and make us all true believers. Just please stop gaslighting people when they say they have run into issues. The machine is sensitive to prompts, so that can be a key difference or sometimes they might just see mistakes you don't. It's not an oracle so don't treat it like one. And don't confuse this criticism as saying LLMs suck, because I use them almost every day and love them. I just don't get why we can't be realistic about their limits and can only believe they are a golden goose or pile of shit. It's, again, neither.

[CamperBob2]

You also don't understand stochastic parrots

You have a parrot that can paint original pictures, compose original songs and essays, and translate math into both English and program code?

I would like to buy your parrot. I'll keep it in my Chinese room. There used to be a guy in there, but he ran away screaming something about a basilisk.

[godelski]

> You have a parrot that can paint original pictures, compose original songs and essays, and translate math into both English and program code?

Kinda, kinda, yes, and yes.

I think there's far less originality than most people think. But it's not surprising when your job isn't leading you to look at thousands of pictures a day. I have yet to see a generative model that isn't pulling heavily towards the training data and you might be noticing the memorization rates are getting higher. But yes, a stochastic parrot doesn't mean memorization, it is about generalization and the stability around the p-norm ball around the training data.

Btw, what's wrong with a stochastic parrot? They are absolutely fucking useful. I use them every day. Hell, I even use things that are complete memorizations and all compression every day. What's with everyone equating powerful statistical systems with uselessness. Anyone saying that they aren't extremely useful is pulling wool over their eyes (but the same is true for anyone claiming baby AGI).

I'd also appreciate it if you discussed in good faith. The snarkiness is not appreciated.

[CamperBob2]

I'm not being snarky! I genuinely feel I'm the one being gaslighted, by people telling me I shouldn't be utterly blown away by answers like the earlier example, or the one I just received:

https://i.imgur.com/JSWLFOi.png

I regularly get downvoted and criticized for suggesting this tool to other students, in defiance of what I can clearly see happening with my own eyes. I see a tool that, if developed further, will answer much deeper questions, including original ones, just as accurately and effectively. One that appears capable of taking humanity to the next level so fast it will make the monolith in 2001 look like an abacus by comparison.

Meanwhile, you tell me, "Don't suggest this to other students, it might hallucinate." Other people say, "Shut this down at once (or nerf it beyond any possibile utility), it might hurt somebody's feelings." Another contingent warns, "Shut this down at once, it might start a nuclear war." Still other people say, "Shut this down at once, it violates copyright law." The objections just get dumber from there, yet gain traction by the day.

There's never been a time when standing in the way of something like this was right. Why should I think it's time to do so now? (And yes, I acknowledge that you're not personally 'standing in the way', but it really bugs me when people who claim they aren't 'standing in the way' of the technology tell other people not to use it.)

I have yet to see a generative model that isn't pulling heavily towards the training data

When's the last time you saw a human mind that didn't work that way? (Or, for that matter, a parrot's mind.) The real truth behind the stochastic-parrot metaphor is that parrots, stochastic or otherwise, are nothing all that special, and neither are we. We're just better at using tools than the birds are, that's all.

Or at least we were up until now. But muh COPYRITE!!!11! ...