LLMs are sycophants, and in long conversations, their sycophancy produces a positive feedback loop: the context window contains affirmations of incorrect interpretations / analogies, so the chatbot continues down that path because, well, that's the most likely completion of previous text. And before you know it, you're discovering the hidden fabric of the universe, which is always some Minkowski fractal spacetime tensor lattice manifold with subharmonic DNA nanotubes.
That is to say, unless you have a robust way to evaluate what you're learning, and to confirm that you're actually learning, I'd tread carefully.
That is my point: an LLM can be great if you know the field and can spot errors. Or, to a lesser extent, if you have some automatic feedback loop that the model can't easily game ("does this code pass unit tests?"). It's a lot less great if there's a risk that you won't detect the early drift.
However, your perspective on how LLMs are used might be too narrow. While no one is suggesting using an AI to find a one-shot cure for Alzheimer's, LLMs are incredibly effective tools when paired with textbooks to master subjects like undergraduate physics.
I agree that they can be helpful for explaining things if you're stuck. But since you used the example of physics, the majority of hard won physics knowledge comes from working lots of problems yourself.
Too many people are already used to LLMs circumventing the laborious aspects of things, so it takes a certain person to withhold from just having the LLM solve the problem for you when you're stuck.
Until we can figure out to teach people to fight against their instincts, then I don't think LLMs will lead to better long term outcomes.
You aren't learning anything. Learning involves doing.
We've known this for ages: simply reading a maths book without drilling on the problems will not get a student to pass.
Best case scenario, you're reading stuff. For users of coding agents, they're not even doing that.
You can have it write a program that generates drills for you.
I wanted to become better at reading sheet music so I generated a sheet music reading program. You can have it generate maths drills, then ask questions about it if you get stuck or whatever. If you genuinely want to get better at something then AI will help you learn it faster. Obviously its going to hamper more people's cognitive ability that it will enhance but that is a separate problem.
I actually did have an LLM ingest some material and generate drills. It worked well. It's rare that happens, though.
The difference between humans and other animals on the planet had always been the ability to reason. If we, as a species, lose that ability, we're looking at an extinction-level event.
For example: AI has helped me get into restoring retro tech, specifically resoldering leaky caps on retro Macintosh logic boards. Before AI, I didn't know how to use a multimeter (I knew theoretically how it worked), I didn't know how to use flux, solder wick, heat gun. I also didn't understand how bromine radicals yellowed plastic and how to reverse it by using blue light similar to what they use for indoor aquariums.
So AI unlocked doing for me.
You're happy using AI instead of other material because it will constantly tell you how brilliant you are, or how quick you're learning.
Just because you can't use a tool doesn't mean the tool isnt useful.
Your bias on display here is frankly silly. Im not saying LLMs are ALWAYS the best way of learning something just like they aren't always the best at anything. They are a valuable tool though. Yes so is youtube and textbooks, and professsors, and peer review literature, and pen and paper, and block training etc.
I also use AI to take in-progress pictures as I desolder to help me check for traces that need to be repaired or help identifying specific chips. I probably could try and find a video where the same chip is featured and someone explains it, and/or retrieve the schematic for the specific logic board, but that's very painful and does slow the process. Think of AI, in this specific case, as enabling skill development for me in a field I wouldn't have necessarily have gotten into, because of being short on time and AI helps me consolidate that information quickly.
I don't quite follow how AI unlocked any of that?
The best way to learn these things (well, second to a human coach who has the expertise and has time to guide you) is from youtube videos, not AI.
In addition, I literally had AI build a complete list of parts to order from Amazon down to the caps for each system I wanted to rebuild -- it was close to 20 different items, I would have probably given up if I had to try and assemble this list from different YouTube videos.
You seem to believe LLMs cannot even produce simple exams and rubrics is that right?
Students cannot grade their own answers for more complex problems, they make mistakes but say they are correct since they don't understand the material, or they are correct but since it doesn't say the exact same thing as the example answer they say they are wrong and correct it even though it was already correct. And an LLM would be even worse than that at correcting tests.
This is not a bias against you, its just a general thing that applies to all students and people. Nobody is good at correcting their own work, even the most esteemed professor gets his work checked by other people. And an LLM is not another person here, they aren't good enough to check your work.
Note its much harder to accurately grade an answer than to answer a question.
But it's not the only way to learn and not even the only way to do a lot of forced recall.
It's downright crazy to say you aren't learning anything by reading. You likely won't retain that high a % of the content without repeated drilling, but it's not like nonfiction exists for no reason!
How much of a nonfiction book can you recall a few months after reading it? Probably very little.
However, I haven't taken a calculus class in nearly a decade and I still know how to solve derivatives and integrals.
Point being: there's levels to this, and reading is not nearly as effective as drilling exercises.
Without doing you may as well read some fiction. The result is mostly the same.
Learning requires a huge time investment. Using an LLM doesn't shorten that.
An LLM absolutely shortens the research part of learning. If I had a human of who had a moderate level of skill who would endlessly answer all my questions, the result would be the same.
You might have a point when it comes to software development because the AI can tell you things but it also just do them for you, at which point, you've learned a lot less. But for non-software things I have to learn things so I can then go and do them.
But even for software development, I've learned a lot of esoteric crap to get interop working on projects that I will probably quickly forget just the same as when I had to spend hours skimming through stackoverflow.
No, it doesn't. Because in any scenario where you are using AI in a potentially appropriate manner, you are verifying every single source it spits out and cross referencing everything it says. If you do not do this you are failing the process entirely.
LLMs are not even close to that unreliable.
If we're talking about research as in actually attempting to learn and get to the heart of a matter then yes. You should be cross referencing everything.
I've build a lot of "houses" recently that I wouldn't have attempted if I didn't have a friend/LLM to ask.
So did you build a house, or did you build a house?
When you ask 'who knows' that's the point of research which was my original comment here. The same goes true for some random asshole telling you to drink bleach as it does an LLM, except people seemingly have hyped themselves into believing the LLM is more right somehow instead of being trained on every random asshole ever.
But it's not going to do that. It's literally designed to give the best and most accurate answer that it can. It's not perfect and I don't expect it to be perfect. According to my personal experience it's definitely good enough for a lot of things like recipes, coding, hobby stuff, and home repairs.
You're expecting me not to trust my own personal learned experience using AI as if somehow all my continued successes are worth nothing because you can invent some wild hypothetical. The more I use it, the more I understand its limitations and avoid them.
No, no, no and no. This is the biggest mistake I see people consistently make with LLMs. It is not designed to give you the most accurate answer, it is designed to give you the most likely series of words following your prompt.
If an LLM is trained on 10 jackasses thinking bleach is a medicinal drink and 1 doctor who disagrees, it will by virtue of probability tell you to drink bleach. Companies add additional safeguards or system prompts to try and keep it 'on rails' but it's all probability based on what you prompt it. It is by the literal functionality of how it works to do so. A function depending on what said company ingests during training, many of which include the entire corpus of the internet.
If you do not understand how LLMs work under the hood then yes, you shouldn't trust your own personal learned experience because you've already demonstrated that you're wrong.
That's not specifically true either; training is more complex than that. ChatGPT had to be trained, for example, to answer questions in a chat format.
> If an LLM is trained on 10 jackasses thinking bleach is a medicinal drink..
Again with the hypotheticals! You literally cannot discuss this subject without hallucinating things that don't exist. LLMs are trained on huge corpus of information from books to videos to reddit posts. Ultimately, statistically, it's going to predict the most common answer to something. Yes, that might be wrong but the vast majority of the time it's going to be right. And you know what, in the real non-hypothetical world, it works great. As much you don't want it to. You can hypothetically hallucinate as many weird unlikely scenarios as you want but that doesn't make it true.
The people least willing to understand how the system works are also the most willing to blindly believe it.
AI companies are trying to build a system that gives the best and most accurate answers possible -- that's the whole point of it all.
This is not true. This is not how LLM's work. They have no concept of accuracy or "best".
The system designers (OpenAI, Anthropic, etc.) are absolutely trying to build a system that gives the best and most accurate answers possible.
The model itself does not have goals, intentions, or an internal concept of "best" or "accurate."
If I had to have a complete idea of what I was doing to do it, I wouldn't even have a job. Doing stuff and making mistakes is exactly how you learn.
i could not get through the hurdles of installing an IDE and js/python modules before.
now i am learning basic scripting and data modeling etc.
it is phenomenal for learning languages.
i built a chicken coop and some furniture. the skills and confidence i gained are real. am i failing to learn certain skills in the process? of course. but I'm getting further then i would on my own, and that is truly meaningful.
you can keep dismissing it; but I'm genuinely using it to break down barriers, give me confidence, and highlight my ignorance in very productive ways.
i find it bizarre how unwilling some people are to recognize that.
You want us to believe you couldn't overcome the puddle-deep challenge of installing an IDE and using Pip or Node in the past, but now you're actually learning how to write functions?
Cool for you if true I guess but I'm pretty seriously skeptical
A lot of the most miserable parts of getting started coding have nothing to do with programming and everything to do with like, trying to apt-install the right compiler version or figure out which build headers you need or some other equally trivial bullshit that gets in the way of writing code.
I started learning Monogame with C# literally yesterday after being a chiefly JavaScript dev for over a decade. I'm having a lot of fun learning it from scratch with no AI
I'll concede that before yesterday it had been a while though
> Especially something older that won't hold your hand
Python and JavaScript are two of the most "will hold your hand" languages these days aren't they?
> A lot of the most miserable parts of getting started coding have nothing to do with programming and everything to do with like, trying to apt-install the right compiler version or figure out which build headers you need or some other equally trivial bullshit that gets in the way of writing code.
I agree but absolutely not for these two languages in particular
You can open the developer tools in any major browser and start typing in JavaScript right there if you want
Python you can install it and write it right in any editor
The upfront burden for both languages is absolutely trivial imo
I have been very pleased with the results so far. I was able to tune the tutorial to exactly what I want to learn, and it did a very good job (at least that i have seen so far). It has made learning fun, since I get to learn exactly what I want, and I can ask the AI questions and have it make changes to the tutorial in real time as i am working through it.
Now, will I keep using this at a rate to fully offset all of the thinking i have stopped doing since i started using AI? I am not sure, I guess time will tell.
For example I am following Dirac's book "The Principles of quantum mechanics" to study QM. Pre-AI wouldn't have been able to do so, I am just that dumb. Even with AI its tough. but the thing is I can keep asking questions until I get that concept drilled in. Now I am doing it at a pace that's unfathomable to me.
But now that I am getting to grips with QM, I can get to things that I am really interested to learn like spin resonance and so on. This is something I am so grateful for.
Now it can be questioned that is it making me wise, intelligent or just "giving me answers" that I should strive to discover myself. I dont know the answer to that. But studying what I want, how I want and not getting judged is something i deeply enjoy. Srry the comment might have taken some tangents.
Why exactly wouldn’t you be able to learn pre-AI?
In another case I follow a bodybuilding cutting regimen and it helps me create and track recipes consistent with my diet plan and macro guidelines. It helps me also create tasty recipes that fit my criteria based on the ingredients I have on hand.
Those are just 2 examples.
I also recently built a backyard jib setup with a platform, ramp, PVC jib rail for snowboarding, and it helped me architect the design for it.
Are you learning, or are you simply consuming?
I think we're missing long form studies that show if it's possible to learn deeply from compressed AI generated summaries of topics.
I've wildly increased my breadth of learning. If I'm ever curious about anything, even a passing thought, I can scratch that itch in a way I never could before.
But am I going deep? Acquiring new skills? Eh... I usually go far enough to unblock myself and/or settle a curiosity. I don't think that's good or bad, but it does present a certain set of tradeoffs that are different than going deep.