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Closed: duplicate Closed: RTFM, dumbass
My favourite moment was when I tried to figure a specific software issue out that had to do with obscure hardware and after hours I found one forum post detailing the solution with zero replies. And it turns out I wrote it myself, years prior and had forgotten about it.
I really do write that stuff for myself, turns out.
I'll personally attest: LLM's have been absolutely incredible to self learn new things post graduation. It used to be that if you got stuck on a concept, you're basically screwed. Unless it was common enough to show up in a well formed question on stack exchange, it was pretty much impossible, and the only thing you can really do is keep paving forward and hope at some point, it'll make sense to you. Now, everyone ba…
No, not really.
> Unless it was common enough to show up in a well formed question on stack exchange, it was pretty much impossible, and the only thing you can really do is keep paving forward and hope at some point, it'll make sense to you.
Your experience isn't universal. Some students learned how to do research in school.
When I ask ChatGPT* questions about things I don’t know much about it sounds like a genius.
When I ask it about things I’m an expert in, at best it sounds like a tech journalist describing how a computer works. At worst it is just flat out wrong.
* yes I’ve tried the latest models and I use them frequently at work
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>Now, everyone basically has a personal TA, ready to go at all hours of the day This simply hasn't been my experience. Its too shallow. The deeper I go, the less it seems to be useful. This happens quick for me. Also, god forbid you're researching a complex and possibly controversial subject and you want it to find reputable sources or particularly academic ones.
My core problem with LLMs is as you say; it's good for some simpler concepts, tasks, etc. but when you need to dive into more complex topics it will oversimplify, give you what you didn't ask for, or straight up lie by omission. History is a great example, if you ask an LLM about a vaguely difficult period in history it will just give you one side and act like the other doesn't exist, or if there is another side, it…
(On the other hand, it's very hard to get them to do it for topics that are currently politically charged. Less so for things that aren't in living memory: I've had success getting it to offer the Carthaginian perspective in the Punic Wars.)
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I've found it excels at some things: 1) The broad overview of a topic 2) When I have a vague idea, it helps me narrow down the correct terminology for it 3) Providing examples of a particular category ("are there any examples of where v1 in the visual cortex develops in a disordered way?") 4) "Tell me the canonical textbooks in field X" 5) Posing math exercises 6) Free form branching--while talking about one topic, I…
These things are moving so quickly, but I teach a 2nd year combinatorics course, and about 3 months ago I tried th latest chatGPT and Deepseek -- they could answer very standard questions, but were wrong for more advanced questions, but often in quite subtle ways. I actually set a piece of homework "marking" chatGPT, which went well and students seemed to enjoy!
I'll personally attest: LLM's have been absolutely incredible to self learn new things post graduation. It used to be that if you got stuck on a concept, you're basically screwed. Unless it was common enough to show up in a well formed question on stack exchange, it was pretty much impossible, and the only thing you can really do is keep paving forward and hope at some point, it'll make sense to you. Now, everyone ba…
how are you checking its correctness if you're learning the topic?
It is hard to verify information that you are unfamiliar with. It would be like learning from a message board. Can you really trust what is being said?
The other chunk of time, to me anyway, seems to be creating a mental model of the subject matter, and when you study something well you have a strong grasp on the forces influencing cause and effect within that matter. It's this part of the process that I would use AI the least, if I am to learn it for myself. Otherwise my mental model will consist of a bunch of "includes" from the AI model and will only be resolvable with access to AI. Personally, I want a coherent "offline" model to be stored in my brain before I consider myself studied up in the area.
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Cliff notes with a near-infinite zoom feature. The criticism of cliff's notes is generally that it's a superficial glance. It can't go deeper, it's basically a summary. The LLM is not that. It can zoom in and out of a topic. I think it's a poor criticism. I don't think it's a silver bullet for learning, but it's a unified, consistent interface across topics and courses.
Except it generally is shallow, for any advanced enough subject, and the scary part is you don't know when it's reached the limit of its knowledge because it'll come up with some hallucination to fill in those blanks. If LLM's got better at just responding with: "I don't know", I'd have less of an issue.
Some topics you learn to beware and double check. Or ask it to cite sources. (For me, that's car repair. It's wrong a lot.)
I wish it had some kind of confidence level assessment or ability to realize it doesn't know, and I think it eventually will have that. Most humans I know are also very bad at that.