11 ms·

How I use LLMs to learn complex topics

• ventana 2mo ago
  The title is not representing what the post is about. “Use LLM to learn complex topics” here actually means that the author asks an agent to describe the problem area, and then implement a simple web-based simulation game, and by playing that game, the author actually learns about the topic and its constraints. They use chip making as an example. That's actually a fun way to learn processes!
  • laurentiurad 2mo ago
    Thanks! The original title was "How I use LLMs to learn...", but somehow HN removed the "How" part. I even removed the initial post thinking it was a typo on my end and tried to post again, but I stumbled upon the same behavior.
    • Anon84 2mo ago
      HN likes to remove “How” and “Why” from titles. You need to edit them back right after you post it
  • lacedeconstruct 2mo ago
    Its fun but is it really effective ? I mean I checked the LLM one and I came out more confused about a topic I already know about, I find the best way to to learn using LLMs is to just generate an example try to somewhat get a mental model of how it works and then ground my understanding with traditional documentation and resources, its an iteration of a technique I used to do in college where I would read the textbook questions first to understand what is important and then read the chapter
    • sixtyj 2mo ago
      Game-based learning, described by Comenius, works if someone else prepares “a game” for you. E.g. like a dungeon master. :) Otherwise you probably get more confused as you have mentioned. On the other side, Peter Diamandis describes a situation where a bunch of kids were given a internet-connected computer and they had no teacher. Instead of it there was a “grandma” that checked kids from time to time. After that there was a knowledge test that revealed “no teacher” approach was more efficient. But it was a group, not an individual activity…
    • ventana 2mo ago
      I assume different ways of learning work for different people. For me personally, it's taking a piece of paper and drawing the diagram of how things work together; of if it's some math, then, again, using the pen and paper to follow the text. I can very much accept that for some people playing the simulation is a good way to touch the new problem space. I can easily imagine that for some topics, let's say, traffic signal automation, a careful simulation game will probably give more information than reading papers or manuals.
      • lacedeconstruct 2mo ago
        > a careful simulation game Totally agree, unfortunately careful simulation games are very rare
• aswegs8 2mo ago
  I mean, yeah, fun project. But that whole game could be like 15 mins of prompting.
• IshKebab 2mo ago
  > What you get is a beautiful animation that is 100% accurate and free of hallucinations. How do you know if you're learning this for the first time? Very risky to learn from LLMs. I've done it, but you have to keep your wits about you. Lots of "oh of course you're right - what I just told you was completely wrong".
• rickcarlino 2mo ago
  I’ve been using LLMs to create readable rewrites of RFCs and specs that interest me. It is not precise enough for implementation use, but it has increased my understanding of the underlying RFC. Another useful approach has been asking Codex to implement complex things, like a Kademlia DHT or BitTorrent client in a literate style with the explicit purpose to increase understanding by reviewing the source code. Examples: https://rickcarlino.com/notes/note-dump-and-ai-summaries/index.html https://rickcarlino.com/notes/note-dump-and-ai-summaries/ind... https://github.com/RickCarlino/tiny-bt https://github.com/RickCarlino/tiny-bt
• dcreater 2mo ago
  YouTube has so many truly wonderful videos on chip production. I admire your approach but it seems like a lot of people are in this ai maxxing phase where they reach for ai for everything despite their being ready, high quality things already available for free
  • AlotOfReading 2mo ago
    I'm also not sure you can really learn chip production from widely available public information. It's a hugely complex industry where the details tend to shape larger strategies. For example, you can't really understand the relationship between Micron and TSMC without some awareness of the trade-offs of memory processes for peripheral transistors.
  • tayo42 2mo ago
    YouTube is just a big dump of information. Having a structured way to learning along with interacting helps you learn. Otherwise you're just binging information
• spacedcowboy 2mo ago
  Another, possibly easier, way is to ask an LLM to give you a quiz on a topic, and then discuss your answers with it. Surprisingly effective.
  • chasd00 2mo ago
    I had an internal company assessment I needed to pass before end of our fiscal year. The study material consisted of 10 ppt decks about 80 slides each (so around 800 total). I had an AI read all the decks and compose a study guide with quizzes along the way. It came up with a 100page word doc that I used in place of the decks to prepare. It worked very well for this including, like you said, quizzing me over various sections. (Yes I confirmed it was ok to use AI with the material)
• user- 2mo ago
  The little tool it outputted is nice, but click around the stages and the text is not high quality at all. The snippy titles, abbrievated explanations, I wish a few more iterations and thought was put into the actual main textual content. Especially for 'complex' stuff
• dwa3592 2mo ago
  i looked at the animations, they look cool, and i don't think i will enjoy learning things that way. as someone else said, there's a lot of content already produced on these topics. i also think the level at which these animations are playing, they are actually hiding the 'complexity' of these topics.
• latent-l 2mo ago
  Very cool, I like the visual learning nature of this and the auto play once starting. The game graphics are engaging which counts for a lot these days, I feel my attention span suffering after using agents for the past year. I've been working on a similar process of pushing to github pages, but focused more on having "practice sessions" with coding blocks to test content. Using webassembly and mock servers to mock backend endpoints Here's one I built to build a full stack llm chat system in the browser. https://model-systems-labs.github.io/latent/llm-systems/lessons/conversation-state/ https://model-systems-labs.github.io/latent/llm-systems/less...
• ultra_nick 2mo ago
  Oh, I do similar, but using single page websites. Last month, I read The Prince and had it make a text adventure campaign for me. For a lot of other topics, I often just ask it to create a simple python example that I can run.
• fosterfriends 2mo ago
  I love this idea!
• brcmthrowaway 2mo ago
  His other project, https://aivestor.tech/ https://aivestor.tech/, seems like a huge grift.
  • gavmor 2mo ago
    Or is it just an unproven attempt? Seems like a pretty straightforward value proposition. Caveat emptor.
    • aswegs8 2mo ago
      If you know anything about investing, you know it is highly likely to be either A a grift or B an innocent, but naive attempt.
      • gavmor 2mo ago
        I don't know anything about investing, but I know a lot about naivete. :)
      • 8bitsout 2mo ago
        From the website: "Quant Competitions Achievement In 2024, I achieved 7th place at Quantiacs, a global quantitative trading competition. With a background in financial software, I built AIvestor to democratize AI-powered investing tools that were previously only available to institutions." I have no idea of the legitimacy of Quantiacs, but for someone with these claims what they are selling is extremely unfaithful. Anyone with a sufficient knowledge of markets would understand the issues with what is being presented on the "portfolio" page, and the approach is bunk. It appears that the product is based on some vibe-coded slop (https://github.com/LaurentiuGabriel/gpt-trading-agent https://github.com/LaurentiuGabriel/gpt-trading-agent). I personally would feel bad even thinking about trying to sell something like this to people.
        • brcmthrowaway 2mo ago
          "Democratize" in 2026 means "sell".
• fosterfriends 2mo ago
  Is there a way we could turn this into a reusable skill?
  • laurentiurad 2mo ago
    Yes! I added it here: https://github.com/LaurentiuGabriel/learnscape https://github.com/LaurentiuGabriel/learnscape
• f311a 2mo ago
  What’s everyone’s opinion on learning new tech things in this day and age? My opinion swings between positive and depressing vision of the future. I still learn new stuff, but I’m afraid it won’t have any value in a year or so. For example, I’m pretty good at optimizing low level stuff, but right now you can just ask LLMs to do so and they are pretty good at it. They will profile the code and suggest reasonable options like 90% of the time.
  • SketchySeaBeast 2mo ago
    > I still learn new stuff, but I’m afraid it won’t have any value in a year or so. This is silly. This would be like arguing that encyclopedias made knowing things pointless. I learn new stuff for me. Professionally, it's important to know enough to know if you're going in the correct direction. Practically, tokens are going to continue to cost money and knowledge can save you tokens.
  • shannadige 2mo ago
    There’s still an immense value in training the brain to learn and be able to approach new problems with the sort of procedural thinking that LLMs enable. We can explore topics that we are curious about and develop that sort of “muscle” to continue asking questions when we have them. I have no fear that when those bigger (and existential) problems arise we’ll be well equipped to keep asking questions and figuring out ways to solve them.
  • SkyeCA 2mo ago
    > I still learn new stuff, but I’m afraid it won’t have any value in a year or so. I have stuff to do now, the value of the knowledge in a year or two isn't important if it solves the issues I have today.
  • brudgers 2mo ago
    One possible value in learning new things is developing a habit of learning. In particular it might be valuable to be in the habit of learning things that one is bad at doing. Or not.
  • cautiouscat 2mo ago
• royal__ 2mo ago
  The biggest thing I've learned from doing stuff like this is that there are no shortcuts. At some point or another, to truly learn something deeply, you've got to dig in to the boring details and do things the hard way. LLMs can help with this...but I find it's usually tempting to try and just offload the boring stuff to them, which doesn't work.
  • ainch 2mo ago
    Quite - you still have to do the work yourself. I think LLMs are best placed to act as an eager tutor that doesn't mind discussing a topic ad nauseam until you're certain you understand it.
  • hahahacorn 2mo ago
    Having an initial higher level understanding across the domain is extremely useful to contextualize the deeper stuff. I think boring details is a very leaky characterization, but I'll continue with it. In my experience it's infinitely easier and faster to learn deep, "boring" things when you understand how they relate to your shallow and wide understanding of all of the related components. The LLM is merely a tool. And you can use it for domain discovery that enables efficient deep learning at an unprecedented rate or you can develop a cursory understanding of a topic and think yourself an expert.
  • yoyohello13 2mo ago
    I’ve found that if I’m not struggling I’m not learning. If stuff is coming fast and easy that’s a sign that what I’m doing is not stretching existing skills enough. It’s true of most things. Running, dieting, weightlifting being uncomfortable is a sign of progress.
    • djaro 2mo ago
      This is also why apps like Duolingo don't work for most users. They want to turn language learning into a fun, effortless game but effortless is fundamentally incompatible with learning. Learning is uncomfortable. Reading a difficult (for you) text in a language you don't understand is exhausting and confusing. But that is where improvement happens. Its even worse since Duolingo added a life system (not sure if they still use it), where you were only allowed to make 3 mistakes before having to recharge your energy. If you get everything right, you are not learning, you SHOULD be making mistakes constantly. That shows you're actually being challenged.
• NBJack 2mo ago
  My favorite way to learn infra topics at work right now is asking for a humorous analogy involving monkeys and bananas. I tend to remember the result, and it gives me reference points for new topics.
• wxw 2mo ago
  > What you get is a beautiful animation that is 100% accurate and free of hallucinations. I'm not sure I follow how this is actually guaranteed? The fact-checking process mentioned just seems to involve asking AI to review its own work.
  • dozerly 2mo ago
    All these LLM-as-review hype pieces don’t acknowledge that it’s turtles all the way down
    • enraged_camel 2mo ago
      What do you mean by this?
      • Gander5739 2mo ago
        If the output can't be trusted, and you use another llm whose output can't be trusted to check the untrusted output of the first llm, then you're back where you started.
        • duncangh 2mo ago
          Yeah this seems to me similar to how the mortgage backed security risk concentration occurred leading up to the global financial crisis. Whereby the risk from exposure to low grade / risky single mortgages was eliminated via diversification but the diversification was simply packaging all of the risky MBS’s together and in no way diversified or de-risked the entire portfolio
          • Terr_ 2mo ago
            I'm hoping that the Big Horrible Realization comes sooner rather than later, when we have less collective damage and pain riding on it. (Plus I'd feel personally vindicated.)
          • cromka 2mo ago
• ElijahLynn 2mo ago
  This is a great share, gonna come back to it. Also worth mentioning that Matt Pocock has a /teach skill that creates interactive, learning sites for learning a new skill.
  • sathish316 2mo ago
    +1, you can customize it to learn any topic concisely, learn by doing, add challenges, add visual explanations https://github.com/mattpocock/skills/tree/main/skills/productivity/teach https://github.com/mattpocock/skills/tree/main/skills/produc...
• 0wis 2mo ago
  Really neat idea, I think it is one of the best ways to exploit the combined building and explaining capabilities of LLMs. I am currently building an app/game to explain friends and family concepts around wealth management and wealth building. Games are a great way to hide complexity while still including it in the « guide » you are making.
• meerita 2mo ago
  I use LLMs to learn deep technical concepts. I really like them because I can spend countless hours a day understanding things and building an investigation file with all my findings. I code examples and test the findings. It has helped me understand basically anything. I'm using LLMs right now to build a terminal browser, a GUI browser, and a PyTorch/LibTorch replacement. It's really fun to be able to learn and make progress this way. It's like reading multiple interactive books, where every concept can be explained again and again until I understand it.
• cautiouscat 2mo ago
  I’ve written a skill that I basically feed what I’m looking to do, some ideas I had for accomplishing it and any other details like tech stack, etc. The skill then riffs with me, judging my ideas and suggesting alternatives. We go back and forth until something useful comes out of it. This process isn’t unlike how I do normal development. However, once agreed it breaks the work into “steps”. It then creates a tutorial for me, for those steps, explaining each line, why each change happens etc. I can then ask questions, muse about an alternative idea etc. Then I do the steps, and I’ve learned and gotten what I wanted to get done. This has been how I’ve been learning Godot and making a game for the past month or so. I didn’t go in blind, I started with a course from GDQuest so I could feel confident guiding the tutorials. I will say though, having a tutor to bounce ideas off of has been really useful. I still try to figure it out myself, consult the docs, discord etc. But if I’m stumped I’ll run my tutor skill and have some fun.
  • vorticalbox 2mo ago
    I’ve started doing a similar thing after reading a post on hn about manually applying the code so that you actually understand it. I have done this for all my work this week and it works quite well. For one it lets you actually query the LLM as to why, their plans give a high level not every single change and it allows you to correct it as you go and the plan will change.
• hathym 2mo ago
  Too over engineered, few text paragraphs would suffice to understand the topic.
• SalaevAl 2mo ago
  LLMs can help you understand a language, but they can't replace learning the vocabulary. Words and phrases still need to be learned the old-fashioned way: repetition
• tuvix 2mo ago
  I don’t think I really agree with the author’s approach here, but I will say LLMs have been a huge help to me as I’ve been reviewing linear algebra and diving into signal processing. Anything in a textbook that I don’t fully grasp or am confused about, I just take a snapshot or copy paste then ask a model to derive it or explain it in different terms. It reduces friction a ton, but at the end of the day I’m not skipping anything.
• 8bitsout 2mo ago
  I thought LLMs were a great tool for learning new topics - perhaps even complex ones. But overtime, I have had several frustrations with this. First, I get exhausted reading LLM prose. I really don't want to read anything generated by something like Opus 5 at this point. Second, as I dive deeper, I need a way to organize the information in a useful way as I begin to branch out in many different directions. I have tried to use the LLM to fix this by having it generate a web page with diagrams and organized information flow. It's an improvement, but I still run into the issues I described in my first pint - LLM prose is annoyingly dense, and the useful information gets lost in a bunch of noise. You can direct it do something like "use plain English and avoid LLM prose - provide only as much information as necessary to demonstrate the point", but it is once again only a marginal improvement. And then I begin to think to myself that I should just read a book on the topic written by a trusted source who put a lot of effort into teaching the topic properly and presenting the information in a thoughtful way. So, I am back to books and mostly try to use LLMs to clarify certain questions or ideas I have.
  • copperx 2mo ago
    It's much better to feed the book to the LLM and ask questions as you read along, instead of asking the LLM to basically write a custom book for you from scratch.
    • gb2d_hn 2mo ago
      I came across the socratic method recently, and have used it to learn a couple of topics that I was having trouble getting to stick. There are some SKILL.md's available for it. It works for concepts as opposed to facts, and causes the model to guide you to answers through your own reasoning, which is both much more engaging than reading a wall of LLM text and helps the information stick.
      • hirako2000 2mo ago
        I was so annoyed I made a Socratic wrapper based on predefined curriculum: https://adaptive.bounded.cc https://adaptive.bounded.cc Trying to diagrams/animations didn't yield good results even with frontier models. But pure text, any model does a decent job.
• jdalsgaard 2mo ago
  I guess we all learn in different ways. I prefer reading, and can fairly fast find the articles that make sense to me. Colleagues often suggest podcasts and videos - I very, very rarely listen to them or see them. The bandwidth is too low. It's not efficient and ultimately I'm bored. This is a nice project, it looks cute. I watched some of the pages But I want more than that, more information, and faster - still a Wiki fan. Also, step number 2 in the flow: have the LLM check itself... Naah, I don't believe that. But you're not the only using gen ai like that. Take care.
  • dan_mctree 2mo ago
    Imo the podcast and the video are better served as background material for some other task. The low bandwidth becomes an advantage because it's often ok if you miss out on some parts due to lack of attention. Indeed it's often a waste of time to just focus on talking people fully if you want to learn fast, reading and especially deliberate practice are better for that. But if you don't have the time, energy or focus, then listening to interviews in the background can be useful supplementally
• sidautomation 2mo ago
  [flagged]
• tolerance 2mo ago
  If you're using LLMs to learn or for research, and at some point you don't end up engaging with an actual resource (books, papers, lectures, web pages, etc) then you're playing yourself.
  • gnarlouse 2mo ago
    Sorta. If its response is grounded in actual material, and you're thorough, it's not so risky. As with all learning, trusting one source is a risk in itself. Hell, I didn't even trust my physics textbooks in college. Physics.
• deleted 2mo ago
  [deleted]
• UltraSane 2mo ago
  I recently used Opus to create a learning plan in ClickUp for every Tailscale feature and it worked very well.
• wiremine 2mo ago
  Personally I'm excited about these sorts of experiments. We all learn in different ways, and these sorts of techniques allow us to create "on-demand" syllabuses and lessons that fit our learning style and learning level. It's not perfect, but I'm optimistic this will be a useful way to teach/learn in the future. And, to be clear, I think this will be best utilized within a group/community setting. I don't think it will replace teachers or classrooms.
• throwaway63467 2mo ago
  That seems like a terrible way to learn. It’s a neat animation but cmon, there’s like educational TV programs from the 80s that explain this so well, in Germany there’s “Sendung mit der Maus”, not sure if they have a segment on chip manufacturing. But in these clips you can at least see the real stuff instead of some half wrong animation, just let the LLM write a few paragraphs for you or better find an ACM article or book on the subject, probably still takes less time than coming up with that animation… God does everything have to be productized and glorified as if you’ve invented a new way of learning. Read some books!
• foo42 2mo ago
  I've been using them by reading some docs/wiki/tutorial, then when I think I understand something trying to do a rough explanation to the LLM and ask if I'm right. I'm usually making some analogy to something I already understand a little. I'm usually partially right but missing some key bits at the first pass. I go back and forward asking for explanations of various bits or asking for resources around the area I'm not understanding. Often times just discovering the relevant name for the area of study opens lots of doors. I basically use it like I would talk to a knowledgeable and patient teacher. As for how useful it is to understand thins, I believe it's still useful and hope it will continue to be.
• zapataband1 2mo ago
  "What you get is a beautiful animation that is 100% accurate and free of hallucinations." Do you know it is free of hallucinations because you crossed checked it with the source material or because you told the LLM "don't hallucinate"
• reqo 2mo ago
  Something that I have realized recently is that it has become so easy to get an answer to almost any question with the help of chatbots that its almost unnecessary to spend any effort thinking about the problem or the solution. I feel like before when I had to spend time researching a problem to find an answer I learned so many things around the topic itself which helped me understand the problem itself better and gained a deeper understanding. Today it feels like you can have an answer to the most complex questions you might have, yet you gain a superficial understanding of the topic and might forget about it quickly.
• CrzyLngPwd 2mo ago
  AKA - How I skim read a lot and learn nothing of value.
• w10-1 2mo ago
  Gamifying the presentation could make topics more accessible to others. For me the overhead wouldn't help with my own learning. Also I've been burned by just learning things mechanistically (e.g., coding, applying algebraic rules), so I'm leery of learning just by making flashcards or models of the topic. I find LLM's do great for learning when I ask what are the principles, how the main applications work, what are the key drawbacks, where are the growth plates in the field, etc. - the kind of thing a good advisor points to. Sometimes I have to ask it explicitly to use topological order of topics and show relations, which often highlights the gradient changes in the learning curve. For pruning, it's surprisingly good applying philosophical heuristics - Occam's razor, or Derrida's differance (the difference that makes a difference), etc. And finally, no learning is effective without problem sets, and for those LLM's at times get me over blocking issues. The degenerate case is memorizing the glib phrases regurgitated back to me; they're helpful and functional enough to get me into real trouble!
• mlpoknbji 2mo ago
  My high hopes were quickly dashed at the step that involved turning a complex topic into rollercoaster tycoon.
• federico-peconi 2mo ago
  not all knowledge can easily be translated into a pipeline alike game imho
• throwrioawfo 2mo ago
  Gell-Mann Amnesia: the blog post
• epolanski 2mo ago
  > I personally find the style used by LLMs to explain things difficult to follow. It's just too simplistic I also struggle with LLMs explaining things, but for the opposite reason. I consistently have problems to get short, precise but plain/simple answers. Instead I'm overwhelmed with walls of texts, often filled with jargon that is a mixture of imprecise and unneeded. The style at which I learn better is by asking about stuff interactively. I ask you what something is, you give me a 3-4 sentences top answer. Then I explore and dig into the topic from your answer on the things I want to know better.
• madibo3156 2mo ago
  This guy is severely milking it now. If learning means building an inaccurate and incomplete understanding of the topic then go hog wild. Otherwise https://news.ycombinator.com/item?id=49209049 https://news.ycombinator.com/item?id=49209049 sums up my feelings about the author's attitude.
• zatkin 2mo ago
  I tend to ask the LLM for a single HTML page explanation, with a pedagogical approach. Something about dropping the word pedagogical leads to a more structured outcome, but I haven't quite figured it out why yet.
• jb1991 2mo ago
  anyone using LLM to learn a new language? got any useful prompts for this?
• praveer13 2mo ago
  I’ve been doing something similar (browser only interactive courses served from GitHub pages) to teach me topics from beginner to advanced LLMs and systems intersection - https://kernelspace.naigap.com https://kernelspace.naigap.com Distributed systems - https://byzantine.play.naigap.com https://byzantine.play.naigap.com
  • dbrans 2mo ago
    These are high quality at first glance. the visualizations and exercises are helpful. What is your process for creating these resources?
    • praveer13 2mo ago
      I just gave a simple prompt to Kimi k3 when it came out, and then just using it and asking it to improve based on my own taste/gaps etc so it’s a long drawn out process. I’m doing that for the first one, will iteratively keep improving it myself as I run through it. Maybe will post on HN after that.
• michaelmure 2mo ago
  I wish there was a LLM tool to explore a topic recursively, as a tree or a mindmap. You would start with some high level concept (say "cryptography") then dig further and further to more specific topics. I think that would be a way more natural way to explore than being stuck on the classic linear output of a LLM.
• domeinhornMOT 2mo ago
  [flagged]
• QuantumNoodle 2mo ago
  > I ask it to review the accuracy of the knowledge base it built in the previous step. > [I ask it to build an interactive thing] > I then push it to a new repo and enable GitHub Pages for it. Congratulations. You are an echo chamber for LLMs. Use it to create, and verify, and post to then be scraped and trained on again.
• nightwalkerkg 2mo ago
  My main issue with using AI as a learning platform is that unlike documentation, books, Youtube videos, there is not really a process of having someone "review the learning material". For example, I can always read the review of some book or ciriculum, the comments under a video, or if it's some for of open source documentation you can check the PRs and verify to some extent it's claim. With AI I can't really say what it has halucinated, because I am learning a new thing, I don't have that benefit of previously reviewed material.
  • j45 2mo ago
    You can ask the LLM to connect the dots to the sources before displaying it to you so you can see the proof in line. You can ask the LLM how to do this. Start with a topic you know well to get the mechanism working and trust it well.
    • nightwalkerkg 2mo ago
      Of course, and that is what I do, but it becomes and additional mental and time consuming effort. As an dumb example, if I am learning a new programming language and trying to grasp some concept, I'll check the docs, find the section and read it. I trust that the source in the docs has been already vetted by other devs and the authors. But if I ask the AI the same thing, I then need to verify it's claims usually by asking it to check if the info is true, and then possibly opening the source link (lucky for me Claude provides the links in the desktop app as footnotes). It's not a question about AI, it's about the trust I have of this tool, it builds over time, but as soon as the AI makes an assumption or a hallucination we are back down to square one. I assume this will become less of an issue in the future as there is more trust between the AI tools and me.
  • ethin 2mo ago
    This is (exactly) why I very strongly tell people not to teach themselves with an LLM. Particularly from the ground up. If you do not understand the domain, you cannot learn from the model because you won't know what questions to ask and it certainly isn't going to answer all of them for you.
• mancerayder 2mo ago
  I use it by telling it my background, giving it a rough timeline and asking it to create a learning timeline, save progress along the way, and git push / pull periodically so I can use the same thing on both Linux and Mac. I tell it for each phase in the learning timeline, present me information, then challenge me on it. If it's code, it challenges me with a coding challenge, where I use it in an IDE plugin. If I'm learning something that isn't strictly code, then I ask it to give me info, then challenge me with questions and grill til I get it right. I ask it to save what it think I struggled with, so that later we can drill it again and I can also review it in an .md file. Does anyone else use Claude like this? It's sped up my learning by 10x. I struggled with 'just reading a book.' Take kubernetes. I hemmed and hawed and spent years periodically reading some dry book or blog or official doc, falling asleep, and forgetting while I got busy. Now I'm aggressively working with it, almost like I'm addicted to a gamification, of getting through our learning timeline, and I'm excited to move forward as quickly as possible and pass its tests. It's like a fake teacher, because I can also ask it to drill into a topic or re-explain itself if it made no sense. The only thing that worries me is, sometimes I'll say something like, "Um, are you sure about that?", and it'll apologize and correct itself. I barely challenged it!
• novren 2mo ago
  Building learning artefacts is under appreciated. Inthink this was always the best way to learn. But it used to require immense work for a teacher. My compiler course is a great example - program in plug in a stage of a compiler. These exercises can be made on demand and incredibly easy now.
• sgarland 2mo ago
  The selected topic (chip manufacturing) is being presented at a shallow level at best. Go read Wikipedia’s article [0] and see how deep and broad the topic is. It also skips quite a few steps, and utterly glosses over how insane of an accomplishment EUV is. This is my biggest societal issue with LLMs: they allow you to think that you’ve “learned” a topic because you read a lot of technical terms. I don’t think it bodes well for the future. 0: https://en.wikipedia.org/wiki/Semiconductor_device_fabrication https://en.wikipedia.org/wiki/Semiconductor_device_fabricati...
• seabass 2mo ago
  > In plan mode (using CC, or OpenCode) I ask a model to build the foundational knowledge for X topic. I ask it to review the accuracy of the knowledge base it built in the previous step. > What you get is a beautiful animation that is 100% accurate and free of hallucinations. How do you make that leap?
• wyzer 2mo ago
  Kids use agents for exam training, rather than cheating. Which is great as long as the LLM does not hallucinate
• afro88 2mo ago
  I'm all for this and I'm keen to try it. I certainly don't want to take away from sharing another neat use case for learning. But > What you get is a beautiful animation that is 100% accurate and free of hallucinations 100% free of hallucinations when you're not an expert that can check it is impossible. LLM hallucinations are an unsolved problem.
• light_hue_1 2mo ago
  This animation is worse than useless. I've taught a lot of students. This is not learning, it's stamp collecting. You're just memorizing a nonsensical recipe. What are the constraints? Why do we do X rather than Y? How does a particular thing scale? etc. All you're doing is fooling yourself into thinking that you've acquired some knowledge. When in reality you haven't even learned the basic mental model to reason about this stuff. You've learned something when you have a mental model that makes correct predictions. Until then you've memorized it at best, and as with most memorized things it will decay exponentially and will be gone from your memory soon enough.
• Dante_Ushin 2mo ago
  [dead]
• eager_learner 2mo ago
  i had Bolt create an interactive app teaching me Oberon language but despite several attempts to fix issues, there were still glitches in unexpected places. So the experience was... meh. Then I went back to a book written by humans (Eric Nikitin's "Realm of Oberon").
• shay_ker 2mo ago
  i've asked llms to write a presentation for me on a given topic. for whatever reason, that finds the hidden layer responsible for explaining things well.
• scottrogowski 2mo ago
  The main bottleneck as an engineer is no longer writing or testing code. It is how long it takes to understand complex systems. This is a really nice approach that, if you have the tokens and the patience, feels like I great way to learn something and I think we'll see more and more stuff like this. I had a similar realization a few months back and am working on a tool that generates "mermaid walkthroughs". It is 1000% less pretty but it is fast and is pretty good at explaining how services work or what a code review does or just as a way for your agent to explain some decision to you. https://github.com/scottrogowski/ariel https://github.com/scottrogowski/ariel
• foxtrot8672 2mo ago
  once again. state and persistence are the issue. not generic llm inference.
• kurthr 2mo ago
  I am greatly disturbed by the idea that any of the demonstrations involve "complex topics". Whether it was the silicon workflow, LLMs, or EUV, I saw nothing complex. Are these supposed to be freshman undergrad or even high school level explainers? I suppose I didn't see any glaring errors on a quick glance, but definitely lots of details were glossed over. Perhaps basic special relativity could be done this way, or simple derivatives, but definitely not general relativity or integrals, much less PDEs. I guess I was hoping for a 3B1B type output. Oh well.
  • kingkawn 2mo ago
    Rejoice for your chance to brag
    • kurthr 2mo ago
      What do you consider complex? This might do basic anatomy, or maybe the ~200 bones in the skeletal system, but would you even cover the circulatory system this way? I sure wouldn't try to do liver function with all the feedback systems (bile, pancreas, pituitary) involved. This might work to explain how a string is stored in different languages, or different sorting mechanisms (bubble vs heap vs insertion vs quick vs merge vs Tim)? That is something covered in 15 minutes of a CS class, but what it misses is why you would choose those mechanisms, and where they are optimal! It's not going to cover a complex topic, like even basic encryption that takes a few classes. In finance it might cover interest or a mortgage payment calculation, but it's not ever going to cover option calculations like Black-Scholes. The issue is that if all you want to learn are some sequences of words that make is sound like you understand something, but not the processes and models that actually drive the performance and limit the design of that thing, then this "works". But it is classic LLM slop! It's a not good enough to win as a high school science fair entry. There are things like language learning that I think different techniques could greatly benefit from LLMs. I would love for them to be popularized! I'm sure there are other LLM learning tools that are less gamified, but more effective for actual understanding and depth.
      • kingkawn 2mo ago
• TormentNexusAI 2mo ago
  The biggest win for AI dev efficiency is cutting down what gets loaded into context. Semantically matching tasks to the top tools helps a lot.
• dbreunig 2mo ago
  > What you get is a beautiful animation that is 100% accurate and free of hallucinations How does he know?
  • y1n0 2mo ago
    It's the kind of overstated unjustified claim an LLM would make.
  • QwenGlazer9000 2mo ago
    I thought of the "does he know" meme when I saw this.
  • dbreunig 2mo ago
    Wrote about this awhile ago, and it hasn’t changed: > Time and time again, when talking to people who rely on ChatGPT, Claude, Perplexity, and other general AI tools, I hear them say, “AI is incredible. It handles nearly everything I throw at them.” > “What does it fumble with?” I’ll ask. > “Well, it still gets things wrong when it comes to my line of work.” https://www.dbreunig.com/2025/04/08/on-ai-observational-comics.html https://www.dbreunig.com/2025/04/08/on-ai-observational-comi...
  • ggm 2mo ago
    Gell-Mann Amnesia. Recognises the failings in their own field of discourse, assumes all true about anything else, same source.
  • jmuguy 2mo ago
    I think these same people believe everything they see on TV, unless the thing on TV is something they already knew about.
• muh_gradle 2mo ago
  > In plan mode (using CC, or OpenCode) I ask a model to build the foundational knowledge for X topic. Makes sense. > I ask it to review the accuracy of the knowledge base it built in the previous step. Ooookay that sounds good. > I proceed asking it to build a simulation of that topic in a low-poly, Rollercoaster Tycoon-like animation. wat.
  • lfx 2mo ago
    Author likes this kind of animation. I have something similar like this, but without the animation step. The main idea is you can do any style you want or like to learn.
  • ch4s3 2mo ago
    It's such a surprising and delightful turn, I love it!
• AmbroseBierce 2mo ago
  But AI will be better than you at those topics as well, and when someone needs an expert in that topic take a guess who will they approach in such scenario. I don't think we are even that far when the complexity AI can handle surpasses 99.999% of what humans can handle, where AI make e.g. physics discoveries beyond the grasp of most humans and it will have to "dumb it down" when talking with humans -even physicists- but not with other AIs
• gnarlouse 2mo ago
  I've had success using the socratic method. I give Claude some topic (say, how the intricacies of the bond market works, the content from which are screenshots of pages from a textbook), and then I go on a walk chatting with it in voice mode. Claude is the expert, I am the student. Claude asks me questions, leading me to an answer logically. I come back with questions, and we back and forth. LLMs arent like they were in '23-'25. I'm almost always skeptical its going to lie, and almost always wrong. In particular: - I limit it/encourage it to give me single sentence questions - I sometimes will ask it to tell me a motivating, human-grounded story, when we're starting a new concept: claude responds "Maya is a bond portfolio manager, and her boss has asked her to quickly price in what happened if yields go down. She knows her bond's average duration, a measure in time, but she doesn't have a percentage, which is what her manager wants. How can she give him a percentage number with just a duration figure and the proposed new yield?" - I'll often ask claude to let me work through it, to derive the thing myself, often resulting in a string of thoughts with "yes/no" trailers, to get the LLM to reply yes or no only, and avoid derailing my train of thought. If yes, my train of thought keeps going. If no, I've got something wrong. - I'll sometimes stop and have it craft an artifact. I typically say "build me a Brilliant.org-style interactive demo of the topic", especially when we get into the realm of looking at the actual maths of a thing (for which prose and dialog is not optimal by itself AFAICT) - I'll do this while I'm traveling, while I'm walking, while I'm doing chores. It's so much fun.
  • pumanoir 2mo ago
    can you share ane example of one of your prompts? I have tried to convert some text into the socratic method and haven't succeeded yet.
    • gnarlouse 2mo ago
      It's a stupid word soup on second read, but hey, it works, and that's all that matters with "stochasty the parrot." """ In this project, I require a socratically delivered line of conversation. Here's the typical structure to the conversation. I ask some question. You need to factor and reason about how to conduct and deliver a conversation. Best practices would be to limit terminology, or assess with the user whether they have a firm grasp on terminology before you use it. You must be very strict about this, it's unacceptable to just introduce a new concept, actor, phrase or other complication into the conversation without first labeling who what or why it exists for the conversation. Conversation structure needs to be front-loaded with a brief interview for the user, "you understand X?", "whats your understanding of Y?". Conversation structure then needs to proceed with single-sentence questions from the agent. User replies with an answer. Sometimes the agent needs to correct the user, but only ever do so with yet another question. """ ^^ these are the instructions I have installed at the root of a "project". Keep in mind, this is claude opus 5 low effort we're talking about, in the "projects" area of the mobile app. Here's the process I use to set up its knowledge: 1. I take screenshots of the textbook on my iPhone, and upload a chapter at a time. 2. I have it summarize the chapter into markdown by analyzing screenshots. You could probably achieve this simpler, if you just had the textbook in PDF. 3. I walk with my boy Clau-crates. I've done this for a couple of weeks and haven't seen it revert back into its typical context-dumping behavior. On second read, there's probably some clean up I could do. Thanks for making me pull it out and look at it. Things that could probably be improved: - tell it to cross-check resources online to further ground itself - use simple, short sentences (long sentences make the brain blur a bit) - not be sycophantic (it seems like project mode has discarded with my root-level anti-sycophancy prompt)
• delifue 2mo ago
  The author says it's "100% accurate and free of hallucinations" but I am sceptical. Although I don't know much about chip production, when I ask LLMs about advanced topics like memory order LLMs tend to hallucinate more than entry-level questions. But the point is that I didn't found that LLM hallucinated before knowing it deeper. It's possible that LLM hallucinates but you don't find out because you are just learning it.
• Revanche1367 2mo ago
  I only use LLMs for explaining things if the subject is one I’m deeply familiar with and can independently and easily verify the facts. Doing so with new knowledge areas is very risky for obvious reasons. For example, “explain how the code in this file works,” I am familiar with the overall codebase, I know the purpose of the file, and I can read it or write tests to verify if I suspect what it’s telling me isn’t correct. Or, if it’s really important, I can overcome my introvertedness and ask the team member who wrote it…but that’s a last resort nowadays, which I am very thankful for. In 99% of cases since at least Claude 4.2 days, Claude and Codex have been very accurate. Gemini on the other hand messes up more frequently and sometimes does weird things like try to delete files it’s not familiar with, at least the 3.6 flash model I’ve been using lately does this. But, code explanations are still good for the most part.
  • controlbird 2mo ago
    100% agreed.
• tamdnq 2mo ago
  haha, I did the same to study new topic and then realized how personalized education will turn out in the near future. The only thing left is keeping a curious mind and ask a lot of questions !!
• anon-3988 2mo ago
  I am very interested in figuring out how people use LLMs for learning. I definitely have the knowledge, but it is severely autistic in a way. OTOH, I am curious if there's a "practical value" to this exercise? If the LLM already contains the information and implementation knowledge to implement the networking stack inside an FPGA by itself, what value do I gain by learning about HDL, TCP, the bespoke Xillinx tooling, reading the documentation, reading papers on the implementation and going through every bit of details and theory. I feel like there's a meta skill that is more worthwhile for "practical value".
  • mfalcon 2mo ago
    You can't simplify learning that way, learning is expanding your mental horizon, by learning something you grow and can take bigger things.
    • kajaktum 2mo ago
      But you can also learn how to use LLM The point about higher level of abstraction yadda yadda
• chadcmulligan 2mo ago
  These animations are great. I have learnt so many things from LLM's, cross checking things is easy enough, but the hallucinations are really not much of a thing any more (in my experience). When you deep dive on things it does seem to get very wordy sometimes (this is claude anyway). Its taught me flutter and dart without opening a book (with the occasional reference page), set me straight on monads finally, refined some linear algebra, various bits of history, and philosophy, I'm learning spinors at the moment. Is some of it wrong - maybe, but it's not like my brain is 100% accurate any way, and when I need accuracy I look up references. It is fantastic getting a broad overview of a subject you don't know or a precis of a current subject, and its so much faster.
  • killingtime74 2mo ago
    It's not close to zero. https://artificialanalysis.ai/?omniscience=omniscience-hallucination-rate https://artificialanalysis.ai/?omniscience=omniscience-hallu.... Hallucinations bring to question what you think you've learned. That's going to cost long-term if you labor under mis-apprehensions until you maybe figure out you learned something wrong.
    • chadcmulligan 2mo ago
      where's it mentioned on that link? I can't seem to find hallucinations (don't worry found it). Yes, sometimes its wrong, most times its right, cross checking is fairly easy, not using it because of the possibility its wrong seems a baby with the bath water thing. I learnt a lot of functional programming from it, stuff I've always wanted to learn, but just didn't have the time and really the sources can be difficult, it really explained things well, and as someone else said in this thread, you can ask questions over and over until you understand, asking a person that (if you can get an expert) would drive them nuts. Maybe my experience isn't typical, its hard to tell, everyone reports something different.
• blackqueeriroh 2mo ago
  For everyone who thinks you can’t learn with LLMs, Dr. Cat Hicks, psychological scientist and author of the recent book “The Psychology of Software Teams[1],” who worked at Google and founded the Developer Success Lab at Pluralsight, has written two skills called learning-opportunities[2] and learning-goal[3] that use validated learning science to help you learn while using LLMs. Cat also has an awesome podcast with her wife, Ashley Juavinett, Phd, called Change, Technically.[4] I encourage everyone to check out her work! She’s dedicated her life to helping software developers get the support they need inside organizations to be seen as humans, not just robots. 1: https://www.drcathicks.com#book https://www.drcathicks.com#book 2: https://github.com/DrCatHicks/learning-opportunities https://github.com/DrCatHicks/learning-opportunities 3: https://github.com/DrCatHicks/learning-goal https://github.com/DrCatHicks/learning-goal 4: https://www.changetechnically.fyi https://www.changetechnically.fyi
• Duanemclemore 2mo ago
  Buildings are a fantastically complicated and interesting complex problem space. I found my architecture studio students using it to ask technical and code questions about the buildings they were tasked with designing. I observed that the inaccurate information it was returning was compounding... To be clear, I say "inaccurate" rather than "wrong" in this case because even if the information it returns is factually correct to the question being asked, students don't have an understanding of the complexity of the interdependent tectonic, regulatory, and spatial / experiential factors of a building sophisticated enough to ask their questions of the specificity and nuance necessary to get a good output that addresses the entire problem. Anyway - with the students still learning to ask questions the right way, and the conditionally-incorrect facts making their learning more complicated rather than less, I hit on a strategy for them to use LLM's that seemed to help much better. I suggested that instead of ask the LLM for the factual answer, or even better for the facts and an explanation, that they ask it to direct them to the proper place in the source material to find the answer themselves. Then, to treat it like a lab partner. IE: Hey Claude I'm looking for "x." Claude: "look at foo, bar." Thank you - chapter (foo) part (bar) table (goo) says "car." However I notice that footnote (hoo) says there's an exception if "dar." Which is what I have. Walk me through this exception... It seemed to have good results as a guide to understanding the disparate bodies of knowledge that they will eventually have to keep together in their heads and work synthetically and non-linearly through, rather than just as an external source of blindly trusted authority.
• socalgal2 2mo ago
  Open engine factory, stuff is flowing opposite direction of the conveyor belt it’s on. 100% accurate!
• markusde 2mo ago
  "Complex topics" in this case means reading 22 AI-generated paragraphs that supposedly cover the entire chip manufacturing process. If the author seriously thinks this level of detail is complex then they have psychosis.
• lwxyfer 2mo ago
  [dead]
• mnsh 2mo ago
  having llm audit all my work/code, and generate review pages (as a teacher) of before/after with working examples is incredibly useful. Its something no course can do for me, even a teacher wouldn't have enough patience to go through each one of my mistakes. having things defined/have correct solution to compare for review is useful, and keeps llm on track. Don't think i would trust llm if it were reviewing it all on its own
• kaycey2022 2mo ago
  That's it? It doesnt feel right. This feels good enough for a casual dinner table conversation and not much more.
• internetguy 2mo ago
  this is pretty cool! it feels very good for getting a brief summary/overview of something and getting a beginner's level grasp.
• nirbendavid 2mo ago
  I usually learn compelx topics using the image generator of an LLM, capabilities like GPT-Image2 or Nano-Banana. I give it like a complex paper -> turn into visualzation or a poster, then ask quesitons and it helps me understand someitmes a very complex paper rather easily. The jump that nanobanana / gpt-image-2 had done is pretty wild.
• throwaw12 2mo ago
  This looks very interesting, something I was also trying to do with my learning. One thing I wonder is, do you mentally 'fight back' monotonicity of your interactive tool? All seem to be in 3D space, with low-poly, like in a factory moving through the belt and giving you an information + textual description to read more But sometimes you want to visualize the charts, or graph of simulations, or maybe even the parts of an item in the rocket.
• jchook 2mo ago
  This looks like the most convoluted and token heavy way to consume a bulleted list.
• tizerluo 2mo ago
  [flagged]
• matherial 2mo ago
  This is, without exaggeration, probably the fiftieth blog post or long-form comment about how someone is using an LLM for "complex learning", and I'd just really like to see at least one of these to be accompanied by a statement saying what are the kinds of problems the author can now confidently solve that they couldn't before. In my experience, LLMs are really good for taking up your time and making you feel like you're learning, in the same way that many of the popular educational videos on YouTube are fun to watch and don't really teach you anything. If you ask an LLM to give you a 500-word summary of quantum physics, it'll give you an oversimplification that probably leans on a hodgepodge of pop-sci metaphors. And if you start drilling down, you risk drilling down on these ELI5 metaphors, which can get you farther away from truth.
  • matheusmoreira 2mo ago
    > 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.
    • noisy_boy 2mo ago
      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.
    • fluoridation 2mo ago
      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?
      • matheusmoreira 2mo ago
• SwtCyber 2mo ago
  One concern though: "100% accurate and free of hallucinations" is doing a lot of work. A second LLM pass can catch some mistakes, but it can also confidently agree with the first one
• tito 2mo ago
  I ran this on ship tracks to see the global warming result. It built a toy climate model for cloud forcing: https://ship-tracks-tycoon.netlify.app https://ship-tracks-tycoon.netlify.app For background, in 2020 the International Maritime Organization changed fuel standards globally. The intent was to reduce pollution, which is great for human health. But, it turns out some of that pollution was supporting cloud formation and creating a cooling layer globally. And temperatures started to climb when the pollution was removed. I haven't looked through how it's doing the calculations yet but this kind of visualization is full of possibilities if done right. Thanks for making this guide! Here's the code and publications/sources on Github for anyone to poke through: https://github.com/titojankowski/ship-tracks-tycoon https://github.com/titojankowski/ship-tracks-tycoon And since the details of ship tracks are a newer topic for me, I'm curious about Gell-Mann Amnesia. Next I'm going to apply this to a topic I understand well and will report back. Stay tuned! (will be tomorrow, bookmark or reply to this thread)
  • tito 2mo ago
    I wanted to understand how well this process works for a topic I already know. I made for carbon dioxide removal, which I work on. First shot had most of the visualizations well made. And it was nice to see what I work on in a visual way that I hadn't seen before. I added labels to the warming graph and a removal build out graph too: https://removal-valley.netlify.app https://removal-valley.netlify.app (while I saw familiar inputs as the sources, I didn't go through to make sure the numbers are all tied in properly, so that's where I would recommend someone proceed with this draft. But the things that are visualized, and how they're visualized, that's good to go) I also had it animate the history of focused research organizations (a topic I was looking to learn about). That one is more a history of the space, and after that ends it's a simulation: https://fro-park.netlify.app https://fro-park.netlify.app All three of these started with the prompts given in the OP and put into Claude. I haven't reviewed the actual numbers underpinning the models yet (nothing jumped out at me though as terribly wrong) so I included a "Draft" tag at the top of the page. Code for both is on my GitHub: https://github.com/titojankowski/removal-valley https://github.com/titojankowski/removal-valley https://github.com/titojankowski/fro-park https://github.com/titojankowski/fro-park
• ziofill 2mo ago
  It depends what you mean by “learn”. To have a superficial idea of the high level concepts of a step-by-step process, sure, a 3d visualization like the ones this author makes can work. But it stops there.
• weedfroglozenge 2mo ago
  The self importance this author has is sickening. No wonder he's chronically talking to chatbots.
• antonyragleap 2mo ago
  The back-and-forth questioning seems especially useful for exposing gaps in your mental model rather than just producing a summary.
• hasley 2mo ago
  One of the most exciting things about LLMs for me is to have someone with which I can discuss about technical/scientific/engineering things. Since usually I do not have a human at hand (or do not want to annoy people around me). Especially conversations that involve formulae can get really interesting and insightful. Of course, you have to be careful with the answers. Especially when the discussions get longer. But usually I see that it is time to stop or to start a new session when the formulae do not make so much sense anymore or when the LLM repeats itself. But with enough caution, LLMs are really a not-so-bad intellectual sparring partner for discussing ideas and insights.
• freefaler 2mo ago
  Yes, there are many misconceptions on "learning", but LLM can be useful. The approach that works for me is using Justin's skycak methods he mentions in his books: https://www.justinmath.com/books/ https://www.justinmath.com/books/ Check the shorter "Advice on upskilling" or "The Math Academy way" for well researched approach. So what works for me - open a project in ChatGPT/Notebook LM - dump all the relevant and highly cited materials (textbooks, papers) - dump the advice on upskilling text or a short summary I've written for the LLM - create "Learning Goals", that contain what I want to learn, and how to estimate is my level good enough 1) Ask it to create a learning path from the materials, following the approach. Give that to an adversarial LLM for cross check. (just for sanity check) 2) Ask it to create an "entry test" to check what I do know and what I don't 3) Iterate step by step on each module/submodule from the learning path that intermingles the approach of: small theory step + small practical task + small test. Log what's missing/wrong in my dept log. Give the dept log at the end of the session to the LLM to incorporate/create another test/task. What I have found useful in this approach is that it will generate a lot of practical tests/tasks for me and it will explain a concept in many ways until I understand it. Also it finds some prerequisites I might miss, but based on my tests and debt log unexpected things I thought I understood surface. So with the limits of LLM and while building a mental map of the relevant parts it's usually enough to spot the hallucinations, but if you apply structured approaches these are minimal. And it's super good, because the number of practice tests and explanations is endless. The interfaces are a bit clunky, but current multimodal LLMs are ok with images or even hand writing. I will recommend that structured approach.
• p0w3n3d 2mo ago
  TBH I was expecting something different. When I use LLM for learning I ask it to make questions for me. It's genius in these tasks. I moderate it to not kill me with difficulty but otherwise it's friendly to help me learn and understand
• m0rc 2mo ago
  For learning, I find LLM's helpful as a knoledgeable "tutor" or "friend" during the reading of a complex paper or book. Before, when I got stuck, I spend lot's of time going around different books/pages/papers until I was able to find a simple enough explanation that allowed me to "catch up". Now, I can ask the LLM and then continue from there. Learning from a book is still the best... Although I have been told that learning a complete subject from a book is now an inproductive use of my time... Perhaps they are right, but I still do it.
  • qnleigh 2mo ago
    Learning is an unproductive use of your time??? No one knows how LLMs will change things, but that sounds like terrible advice.
    • m0rc 2mo ago
      You see, it seems that the issue is not learning by itself. But, learning by reading a book cover to cover about a topic. It is not fast enough as the current times seem to require. A complex book can take me 1 year or more (Visual Complex Analysis of its cousing about Differential Geome, Norvig's Modern IA, etc.).
• nalekberov 2mo ago
  > What you get is a beautiful animation that is 100% accurate and free of hallucinations. I am pretty sure this person is a. Ignorant of the fact, that AI is designed to give just answers, they do not care whether they’re true or not b. Have never Cross-checked Information given by AI with reliable sources
• kannanpoem1984 2mo ago
  This is cool project !
• deleted 2mo ago
  [deleted]
• num42 2mo ago
  There is something called tacit knowledge that cannot be easily learned through LLMs. LLMs are currently very good for research and theoretical knowledge. For example, learning how to make mechanical watches involves a lot of hands on, tacit knowledge. That skill would also be transferable to building other precision instruments. I don’t think we can currently learn these kinds of skills easily with the help of LLMs. Even if you know everything about bicycles their mechanics, components, and how they work you still have to learn how to actually build, repair, or ride one through practice. Knowing, understanding, learning, and practicing are completely different things. There are also niche areas of expertise that can take years to develop,not just to the point where you know the terminology and jargon, but where you understand the nuances of the field, can recognize the "unknown unknowns", and eventually have the ability to push the boundaries of existing knowledge. Maybe that is what we should really call learning: not simply acquiring information, but developing enough understanding and practical experience to contribute something new to the field. Ironically, on the same front page of HN, there is a post about Andrew Wiles and this. I don’t think I would be able to comprehend Fermat’s Last Theorem, the Poincaré Conjecture, or Gödel’s Incompleteness Theorems, even with the availability of LLMs.
• FailMore 2mo ago
  I would prefer to view code this way - a flow of data between things... a project I'd really like to work on. Has anyone done anything similar?
  • 8-prime 2mo ago
    There have been numerous approaches doing things akin to that. I remember my university working on such a project. Or at least a similar one, representing a code base as a street network with traffic showing how data flows through the system. I too, would like to have such a tool for viewing larger projects where the flow can be cumbersome to reason about. One issue I guess would be finding the right level of abstraction in the representation.
• BorisBinyaminov 2mo ago
  [flagged]
• floki165 2mo ago
  [flagged]
• curtisblaine 2mo ago
  Those animations are... series of steps, each with a description? How different is this from a plain text list? It's not that you can see forks or that the layout of the assembly line gives you more information. If anything, a plain text list is easier to scroll backwards and forward?
• scotty79 2mo ago
  What I'm missing is an agent window near the text that I could immediately inquire about the details of the process.
• shevy-java 2mo ago
  Looks like a horrible flow. I feel sadness for the guy.
• steve1977 2mo ago
  "Learn complex topics". Yeah, not really. Get a cursory, superficial overview of complex topics? Sure. But that's about it.
• smnplk 2mo ago
  The other day i was trying to learn why there is no internal structure to electrons and other quarks, but it failed. I still dont know.
  • pbmonster 2mo ago
    Good news: nobody does.
• aarjaneiro 2mo ago
  These comments make me wonder if people were unable or unwilling to use search engines effectively
• EagleEdge 2mo ago
  For me the bigger value comes from explaining complex stuff. I remember Andrej Karpathy once said (He was quoting someone else actually) "You can outsource your thinking but you cannot outsource your understanding". I can keep asking LLMs to explain a complex topic until I get it. Ask to explain it 10 different ways, explain it using physical analogies, explain it using visualization. If I don't get it, just say that out loud so that they can keep explaining it to me in different ways. We can keep going that until I really get it. That is the value I get the most using LLMs to learn things, especially complex topics.
  • einpoklum 2mo ago
    > I can keep asking LLMs to explain a complex topic until I get it. Or you'll be confused by the slop it generates, which is very conversational but may be just false. Or - you could "get" something wrong and believe it to be the truth because the AI said so.
• vilfred_sikker 2mo ago
  Really cool idea the sim game approach! I'm trying to find a good approach to learning in the age of agents, though more focused on the actual code I read and write in my day to day. I'm building tech-professor.com which is in beta, where my goal is to setup continuous learning for product teams and developers. It's a hard problem to solve, but I believe that llm-based learning will become better as models improve!
• URMAJESTY68 2mo ago
  > What you get is a beautiful animation that is 100% accurate and free of hallucinations I can appreciate using all of the tools at your disposal to learn a new topic, and in no way want to discourage learning. I've used LLMs myself to question my own understandings and it can be helpful. However, "... 100% accurate and free of hallucinations." isn't a statement someone who just learned the topic is capable of honestly stating.
• phailhaus 2mo ago
  The fact the author thinks every topic can be fit onto a rollercoaster tycoon-style analogy leads me to think they do not actually understand these topics very well.
  • atroche 2mo ago
    From the article: > I proceed asking it to build a simulation of that topic in a low-poly, Rollercoaster Tycoon-like animation Sounds like the Rollercoaster Tycoon part is just referring to the aesthetics/graphics, and the author is just suggesting building a top-down isometric 2D animated simulation (which I agree is a bit limiting, there are definitely some things where you'd want to be able to fly around a 3D space in first person, move time back and forth, manipulate parts of it).
    • phailhaus 2mo ago
      Yeah that's the problem. Imagine trying to learn calculus as a top-down isometric 2D animated simulation. It doesn't make sense for the topic.
      • laurentiurad 2mo ago
        Calculus probably not, but you can find other types of animations for it. Learning how web requests work definitely fits this animation type.
• Thanemate 2mo ago
  I once uploaded a 700 pages book and quizzed chatGPT strictly on its contents. It answered somewhere between 60-90% across 6 quizzes. This was 2 months ago. Those quizzes were fact checking statements, not even problem solving. I'd be extremely cautious to ask it to have it explain any specialized concept even from a document.
• atroche 2mo ago
  Even better (for some topics) would be to play a Factorio-style game (or a Factorio mod). Leaving aside the whole can-we-trust-LLMs aspect, the ChipTycoon page is not really a simulation, and the animation doesn't actually add anything. I like the author's intent, but there's a lot of work to do still before he makes this useful. Surprised no one's dropped a link to Bret Victor's https://worrydream.com/LadderOfAbstraction/ https://worrydream.com/LadderOfAbstraction/ ("A Systematic Approach to Interactive Visualization") yet.
• deleted 2mo ago
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• WorseIsBetter 2mo ago
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• cyrialize 2mo ago
  I've just been using LLMs (specifically DuckDuckGo's chat) to help find research and articles to dive into. I don't really see the point of asking LLMs to summarize something for me when I can just read about it myself. I will do chats back and forth about specific topics, but then always ask for follow up resources I could dive into. This isn't fool proof - I'll sometimes get resources that aren't really what I'm looking for - but it feels better than searching the web. Especially when I don't have a clear idea of what search terms to look for. I haven't tried things like the Socratic method though or having LLMs teach me something! I've really just been focused on reading lately.
• mcfry 2mo ago
  This is cool, but I feel like the information needs to be refined by someone who understands the domain. A long-form educational resource certainly requires many decisions to be made - where to add more/less detail, where to refine, where to better visualize, etc - and humans are still king of the decision domain, for now at least. Even with the visuals, it feels a lot like the step-by-step I might receive from ChatGPT. There's some value add, I guess, because we're visual creatures first and foremost... but it's tentative. I don't see nearly enough discussion on the distinction between LLM and human reasoning, where the boundary lies, that type of thing. It's like we've all collectively buried our heads in the sand and accepted that they'll eventually be able to think exactly like us.
• lubo92 2mo ago
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• neop1x 2mo ago
  Or you could have just opened an existing Intel pdf brochure which explains it with more intuitive illustrations (the search took me 2 minutes and it consumed a fraction of energy) https://download.intel.com/newsroom/kits/chipmaking/pdfs/Sand-to-Silicon_32nm-Version.pdf https://download.intel.com/newsroom/kits/chipmaking/pdfs/San...
• adityazero 2mo ago
  I just ask LLM to to give me a short tutorial on the thing i want to learn but i dont want to start from chapter-1, that is boring. so i upload my resume and say that make this tutorial based on the skillsets i already have. btw, this is a much better experience than watching Youtube videos for learning.
• MetroWind 2mo ago
  I mean it's a complex topic alright, but what you can learn with this is just a watered down pop-science level overview, which is not what I would call "learning". A reasonable test is what I call the enhanced Feynman test: teach what you learnt to others, and be able to defend against reasonable questions. A stretch goal I sometime use is to be able to read recent papers on the topic.
• przemarzec 2mo ago
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• Akrish2026 2mo ago
  This blog in no form or manner outlines how said author has learnt complex topics. The biggest issue with "AI" as of now is its inability to reason. What this means is that it lacks the essential ingredient of the learning process. It does not "understand" what it means to grasp a concept nor does it comprehend the need to present facts in a specific order so said reader can grasp the necessary content. What I can agree with the author, is on its ability to be a glorified search engine; it can put together content for niche topics that is otherwise time consuming.
• vfalbor 2mo ago
  I have created a couple of subjects, the cell and the mitochondria: https://vfalbor.github.io/cell-tycoon/cell/ https://vfalbor.github.io/cell-tycoon/cell/ https://vfalbor.github.io/cell-tycoon/mito/ https://vfalbor.github.io/cell-tycoon/mito/
  • laurentiurad 2mo ago
    looks super cool!
• celurian92 2mo ago
  I am really fascianted by this topic. Like i want to learn about lot of stuff that I couldnt easily and couldnt make time for and also learn critical thinking as well. But i feel llms cant help to learn properly. From many research paper i skimmed ( without llm, from youtube videos though :p) i understand its the friction of not understanding and then getting +/- feedback faster with lots of iteration helps us learn fast. But for knowledge work it seems very hard as there isnt any verifier that can give me the mental mode that will evolve/extend my current mental model. One feedback mechanism can be testing myself on the topic but software engineering related tasks are pretty hard to do without expermiemnt and experience.