> don't really teach you anything
Dunno, I've been learning a lot of Rust in the past few days. Just dove right into a project and asked AI to teach me stuff on a need to know basis. I'm actually getting used to Rust by now.
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Learning programming languages is quite trivial. Many years ago I counted 16 that I had used professionally, now they are more.
It takes way more time to master and be very comfortable with a language due to its ecosystem, though. Some languages are more likely to click with a person, yet underneath they are all the same (minus the functional languages that form their own group), e.g. some performance issues may require looking at the generate assembly code.
A programming language is a skill with an accessible source of irrefutable feedback. If the program doesn't work, then you did something wrong. What happens if you try to learn something less concrete or less testable, like quantum mechanics, as the GP suggested?
I agree with you. I'm also using AI to help me learn electronics so I can finally make some real stuff I can hold in my hands. Lots of hard engineering involved so I'm a lot less confident in my ability to spot the AI's own mistakes.
However, saying you can't learn "anything" is just too strong. I'm definitely managing to distill the AI's weights into my own brain.
It's true in a very real sense, though. Without calibration, how can you tell whether you're learning something real or something fictitious? Imagine trying to learn a language from a single teacher, without ever talking to or corresponding with a native speaker. How could you tell whether you're actually learning the language, or the teacher's unique dialect? Yes, you indeed "learned" something, it's just something that might not bear much resemblance to the real thing.
This made me realize all those benchmarks which unlike loosely acts as a person being awarded with a certificate after his doctorate is rather worthless, for you never know when it bullshit-ted.
Yep. This is the key. You need some kind of knowledge of what the end result should look like to really learn something from LLMs. Otherwise it's a deep dark forest with no way out.
Same. I setup a practice skill that has a curriculum/list of topics, teaching methodology, approach to drills, progress tracking and spaced repetition.
Additionally I asked it to also give me problems relevant in my business domain so that I learn how to directly apply the knowledge in a realistic scenario.
I am getting much more comfortable writing rust than I was barely two weeks ago. More than I was just reading tutorials.
AI is a super polarising topic. Even now there are people who are like “it’s all AI slop so it’s all useless” along with the “OMG AI!!! OMG we will have AGI soon!!!” people.
The truth, as always, is in between. There’s loads of people using it for useful things, learning, automation and getting good results. But it’s also wrong enough that you need to deploy it carefully sometimes.
Don’t worry about either group. Keep objective and use AI where it helps and do it yourself where you are better. That’s all.
yep, I think its even worth considering that some folks are internally conflicted, I am certainly an enthusiastic consumer of AI (or what I can mooch anyways) yet nothing prevents me from considering the downsides, with the usual bleeding heart guilt that comes with a perceived complicity in unfortunate happenings and I'd also probably be a nimby if I were the sort of titled landowner that anyone would listen to.