Ask HN: How has AI changed your learning methods?

Yes... AI helps transform learning content to make it more possible to consume in ways that are effective for learning. But it can't help you with things up Blooms hierarchy (like synthesis) and indeed using ChatGPT might harm you doing that - it prevents you feeling the severe pain of bad/inconsistent writing.

Having learned before and after ChatGPT, the workload of students has remained the same, but some can obviously be done with AI, and most students do this, or have tried it.

I believe as a result, the efficacy boost has been offset by the lower amount of time people spend studying - just like most historical studying technologies. For every 1 student who uses AI to learn, there is 2-3 who prefer just to use it to cheat. But it works brilliantly for every type of student for basic explanations, run downs of historic authors or positions, etc. But this is pretty much just wikipedia stuff re-arranged to your learning level. It's helpful, but not augmenting.

The ChatGPT app lets you just take photos of everything. I take photos of labels and ask it to explain all the chemicals in my food, shampoo, toothpaste, etc. Which one are the preservatives? How long do those preservatives last? What's the chemical that makes my teeth hurt when I eat ice cream? What happens if a toothpaste doesn't have that chemical?

Also lately I've been taking photos of stuff like coffee grinders and making it guess what it is. It's surprisingly very accurate and you can use it to explore the thought processes of why someone might pick a particular set.

I used to ask questions on various /r/Ask subreddits. For example, AskHistorians and AskPhilosophy.

Just as ChatGPT became more available, these subreddits decided to make their posting policies unnecessarily strict. The "answering culture" has also become more hostile, with people downvoting questions that don't fit into the monoculture of Reddit's hivemind.

And so I have found ChatGPT to be very useful for asking about philosophical and historical questions, specifically asking for resources on a particular topic/problem. E.g., "Has any philosopher written about XYZ topic?" It will sometimes give me imaginary resources, but usually it'll recommend actual books written on the subject.

I use it a ton to generate example sentences I can then import into Anki to practice vocabulary in a foreign language, specifically Finnish.

I've even been working on a tiny open source wrapper around the OpenAI API specifically to speed this process up, based on what I've learned works from experience: https://github.com/hiAndrewQuinn/wordmeat

For university, it hasn't changed by a lot. Ideally I would want a tool where I could input all slides, worksheets and scripts for a module and then get a nice summary, mock exams, ... nothing can do this which is why I wrote my own tool for this, it works alright, but it isn't 100% accurate and misses bits of information. So I am mostly back to compiling my own summaries and learning based on old exams.

As a side project I am currently building a drone myself on a really tight budget. While I am pretty good on the coding side, my understanding of electronics is basically non-existent. So when I am asking basic questions it's quite helpful; as soon as I am giving it specifications ("Will this brushless motor and this ECS work with a 4S lipo?") it breaks down completely - so it's helpful, but far from perfect.

AI really speeds up the “I am so new to this topic I don’t even know what questions to ask” phase of learning. When approaching a new topic, it gives me a general overview which I can pick apart into deeper queries that I research the old fashioned way.

It's the first thing I go to when I have a "stupid" question. I also just use it to learn languages and math, and get clarification when something in my area of expertise is confusing. It's dramatically reduced my search engine use. It also enabled me to write an anki clone that I just wouldn't have bothered with otherwise.

That said, it is actively harmful when discussing components of Chinese characters - it hallucinates so much it's essentially unusable. I stick to traditional resources for that. I'm also reading as many scientific papers as before, there's really no substitute for that yet, and I haven't found it very good at literature searches.

Not much. It's too inaccurate for my research and is a bad writer.

Day to day I write Lean, and I use moogle.ai to find theorems. It's... fine as a first pass. The website constantly gets confused about similar-looking theorems, it can't pattern match, and it can't really introspect typeclasses (which can be hiding the theorems I want). However it usually can usually help me go from a vague description of what I want to some relevant doc pages, so credit where it's due for that.

As someone focused on grad school, I find myself much less frequently getting stumped by problems and rage-quitting. I also use some prompts which help to speed up my learning in general while making sure any LLM doesn’t give me the answer.

One of my research interests is on how humans use expert systems (akin to how Go players’ ELO ramped significantly after the release of AlphaGo).

I can’t speak for “traditional” learning methods, since I’ve long been out of school. But I find chat gpt is about as good at first pass research as google was circa 2003. Google is no longer good for research. Used to be I didn’t know much on a topic and I could start googling and page 3 or so would start to have key words necessary to blow open the topic. google no longer even populates page 3.

So I start with basic questions in chat gpt. I know it’s lying to me. But it uses words and phrases that seem interesting. I can iterate over that, and in a short time I know a phrase I can actually search for in google to find authoritative content.

I wouldn’t quite call it a game changer yet, as all it’s done is give me back what I once had. But it is a bonus in that it can do an ok job synthesizing new examples from content that already had lots of disperate examples on the web. It can also give some clues when you find conflicting information as to why the information is conflicting. It’s making stuff up a lot, but there are always good clues in the output.

Massively changed my learning in the development. Before I sat in front of my pc and did not know where to start. Also understanding the innerhalb working is much easier. I learned next.js in just a few weeks

My son used the "custom GPT" in ChatGPT a lot e.g., for Organic Chemistry and Advanced Biology. He said they saved him a ton of time as it explained basic concepts when he had trouble understanding the textbook (which is written in the most Orwellian manner possible). Before, he googled Libretext and Khan Academy etc., but the custom GPTs summarizes that information nicely.

Yolo pumping out code for a programming language or tooling I'm unfamiliar with, either to use as boilerplate or learn from as an example.

Now that AI has crapped all over the internet, I use books more.

I've tried to use ChatGPT to answer programming questions where I need either a library reference and/or an example. I find that ChatGPT isn't better than looking up the library reference, but that sometimes it's faster for it to generate the example that I'd otherwise have to look on several pages before I find.

I also spend too long clarifying what I mean.

For example, I wanted for a Rust program to detach into the background, and ChatGPT (with my stupid prompting) kept suggesting I just run `std::process::Command::new("program")`, but I want a single executable to detach! Eventually, once I struck the right chord, it suggested the `daemonize` crate. But it wasn't until after I'd found that by conventional search.

I sometimes use the Kagi !fgpt pattern if I know that what I'm searching for has a good average answer. It'll give that answer and skip the blinking ads, cookie pop-ups, newsletter popups, and autonomously scrolling on my behalf.

I'm looking forward to having an offline AI assistant that'll search and accumulate, rather than hallucinate answers from a bunch of stolen code snippets that akin to "copy-pasting from StackOverflow, but with hallucinations."

To be honest, I've never felt like I needed additional tooling to make learning faster or easier. You're inherently rate-limited by the bandwidth of your own brain, so it mostly comes down to finding information in the first place. It sounds like others haven't known where to start in the past, but I guess I'm lucky not to have ever had that problem. I'm drowning in more information than I can take in already. My bookshelves have always been and will always be full of books I intend to get to eventually. All the other things taking up mental time and energy, spending time with my wife, trying to have a family, making and eating food, sleep, exercise, software can't help me with. The only time-consuming activity I can potentially offload is paid work if I can find some other way to pay the bills.

I've gone back to reading paper books.

This is something I found useful doing but not sure if it applies to learning in general, but here goes:

- I regularly read technical texts, some related to math, some related to programming/software engineering

- I ask Chatgpt4 (now Claude Sonnet 3.5) to quiz me on the nuances of topics X, Y, Z

My prompt template looks like so:

"I'd like to test my understanding of {topic}. I'd like you to quiz me one question at a time. Ask nuanced questions. Answers need to be multiple choice that I can pick from. Avoid congratulatory tone in responses. If I pick the right choice for a question, move on to next one without asking. Provide detailed explanations in case I answer something incorrectly."

I've found this surprisingly effective at pointing out gaps in my understanding. Ymmv.

I still use StackOverflow 99% of the time for my code issues. #micDrop

Between the hallucinations and over the top agreeableness I have a hard time finding LLMs useful as a reliable learning aid. First you have to disentangle what output is factual from what it's just making up and then you have to be careful not to feed it loaded questions lest you unwittingly lead it on such that it's just agreeing with whatever you say. The amount of work required to get satisfactory results might be better spent doing research in more traditional ways.

All that said I'm very excited for the future and look forward to these problems being solved as I believe they eventually will.

I use OpenAI and Anthropic tools for brainstorming/rubber ducking/sanity checks.

I know that the LLM provided specifics are almost never good enough for a final answer. However, LLMs can get me to think out of my own personal box.

Basically, this has replaced what I once used to get out of being surrounded by human peers. However, I was reticent to bother humans, and I have no such reservations about asking a chatbot a dumb question.

Since the advent of AI, when I am doing research I have to scroll down a little further after making a search before I can see the results, because now there is some AI stuff in the way at the top of the page.

I have to do a double take on Google, Duck, Brave because even the search results and content farms are spitting out AI hallucinated nonsense.

Thanks to ChatGPT, I'm much less hesitant to delve (haha) into unfamiliar topics. "Hi! I'm a beginner programmer. I'm interested in learning Idris but I know next to nothing about dependent types. Could you explain them in a couple of sentences?"

Then, after the answer, I ask follow-up questions. I also try to check the answers against other sources, e.g. docs or Wikipedia in order to spot hallucinations.

Last year, when I was studying for an AWS Certification, I used a lot of chatGPT to explain me services and concepts with useful analogies and practical use cases.