Show HN: Simply explain 20k concepts using GPT (platoeducation.ai)
I made a tool that autogenerates simple, high-level explanations of concepts and organizes them in a somewhat university course-like structure so that it's easier to see how things are structured. Currently it has about 20,000 concepts on a range of topics but that's just what I generated so far, it should work with more obscure topics in the future.
I love learning about random topics where I don't have a good background in like history or linguistics, but it's hard to figure out what topics there (you don't know what you don't know) are in certain fields and what they are even about, so this was a way to get the high level idea about random things that I wanted to know about.
It also only uses the information in the GPT model at the moment, so obviously information can't be trusted completely and you should definitely double check any information you read here by Googling. I'm thinking of doing the Bing Chat approach for the next version and adding references, but don't have that yet
Hopefully someone else finds this useful even if it's not perfect!
31 comments
[ 3.3 ms ] story [ 33.1 ms ] threadWhat was the subject and what prompt have you used when asking about the books?
(looks like parent comment has been edited; earlier it mentioned asking GPT for good book recommendations and getting made up results)
Sure, it's possible to "learn" from LLMs in that they might spark some idea that you might not have thought of, but taking the output from LLMs as a source of knowledge is exactly what you shouldn't use an LLM for.
I understand this feeling, but it is important to push back against it, most importantly for the developer's own development. Not all ideas are good. I'd easily wager that most ideas are bad or at least not good, at least going from my own thought process. That is why we have places like HN, to share new ideas and get feedback. It is the best thing for the person with the idea (and also society) when their blatantly bad idea is responded to with generous, kind, informative, and direct criticism.
But when I ask an LLM to tell me something that I am an expert in, I am usually incredibly disappointed by the bullshit it spews.
Might want to remove "on" to make the sentence grammatically correct.
I learn from the 1% of material that is created by humans who are, to some degree, experts in their field.
Sometimes it's also wrong, but it's not because they were just lazily regurgitating rando 'net posts.
I think you're going to see a very rapid pendulum swinging here. With an absurd amount of content being generated and then flooding the various platforms, and in turn platforms are going to try and combat this by creating more centralized sources of information. The return to analog knowledge seems a bit far-fetched. I highly doubt that would be an outcome, if only because convenience trumps it. Look at librarians, you can talk to one and get much better direction of information than asking google, but few people do that. I can't see that changing.
And all of those models have been indiscriminately trained on the sum total of that pure noise. What you are getting from these models is a cleaned-up, grammatically-perfect, auto-editorialized synthesis of that pure noise.
AI algorithms can generate 'noise' at a much faster rate than people can, so it will be even harder to find the hidden gems.