5 ms·

LLMs make learning new material easier than ever. I use them a lot and I am learning new things at an insane pace in different domains. The maximalists and ske

• junon 1y ago
  On the flip side, I wanted to see what common 8 layer PCB stackups were yesterday. ChatGPT wasn't giving me an answer that really made sense. After googling a bit, I realized almost all of the top results were AI generated, and also had very little in the way of real experience or advice. It was extremely frustrating.
  • roxolotl 1y ago
    This is my big fear. We’re going to end up in a world where information that isn’t common is significantly more difficult to find than it is today.
    • andersa 1y ago
      It's going to be like the pre-internet dark ages, but worse. Back then you only didn't find the information. Now, you find unlimited information, but it is all wrong.
      • svara 1y ago
        I don't know, this sounds a lot like in the late 90s when we heard a lot about how anyone could put information on the internet and that you shouldn't trust what you read online. Well it turns out you can manage just fine. You shouldn't blindly trust anything. Not what you read, not what people say. Using LLMs effectively is a skill too, and that does involve deciding when and how to verify information.
        • andersa 1y ago
          The difference is in scale. Back then, only humans were sometimes putting up false information, and other humans had a chance to correct it. Now, machines are writing infinitely more garbage than humans can ever read. Search engines like Google are already effectively unusable.
          • vohk 1y ago
            I think there will be solutions, although I don't think getting there will be pretty. Google's case (and Meta and spam calls and others) is at least in part an incentives problem. Google hasn't been about delivering excellent search to users for a very long time. They're an ad company and their search engine is a tool to better deliver ads. Once they had an effective monopoly, they just had to stay good enough not to lose it. I've been using Kagi for a few years now and while SEO spam and AI garbage is still an issue, it is far less of one than with Google or Bing. My conclusion is these problems are at least somewhat addressable if doing so is what gets the business paid. But I think a real long term solution will have to involved a federated trust model. It won't be viable to index everything dumped on the web; there will need to be a component prioritizing trust in the author or publisher. If that follows the same patterns as email (ex: owned by Google and Microsoft), then we're really screwed.
        • skeeter2020 1y ago
          >> Well it turns out you can manage just fine. You missed the full context: you would never be able to trust a bunch of amateur randos self-policing their content. Turns out it's not perfect but better than a very small set of professionals; usually there's enough expertise out there, it's just widely distributed. The challenge this time is 1. the scale, 2. the rate of growth, 3. the decline in expertise. >> Using LLMs effectively is a skill too, and that does involve deciding when and how to verify information. How do you verify when ALL the sources are share the same AI-generated root, and ALL of the independent (i.e. human) experts have aged-out and no longer exist?
          • svara 1y ago
            > How do you verify when ALL the sources are share the same AI-generated root, Why would that happen? There's demand for high quality, trustworthy information and that's not going away. When asking an LLM coding questions, for example, you can ask for sources and it'll point you to documentation. It won't always be the correct link, but you can prod it more and usually get it, or fall back to searching the docs the old fashioned way.
      • koolba 1y ago
        Content from before the AI Cambrian explosion is going to be treated like low-background steel. https://en.wikipedia.org/wiki/Low-background_steel https://en.wikipedia.org/wiki/Low-background_steel
  • m11a 1y ago
    The solution is kagi.com imo. Before AI generated results, the first page of Google was SEO-optimised crap blogs. The internet has been hard to search for a while.
    • deleted 1y ago
      [deleted]
  • endofreach 1y ago
    It will dawn on non-tech people soon enough. Hopefully the "AI" (LLM) hypetrain riders will follow.
• blibble 1y ago
  how do you gain anything useful from a sycophantic tutor that agrees with everything you say, having being trained to behave as if the sun shines out of your rear end? making mistakes is how we learn, and if they are never pointed out...
  • svara 1y ago
    It's a bit of a skill. Gaining an incorrect understanding of some topic is a risk anyway you learn, and I don't feel it's greater with LLMs than many of the alternatives. Sure, having access to legit experts who can tutor you privately on a range of topics would be better, but that's not realistic. What I find is that if I need to explore some new domain within a field I'm broadly familiar with, just thinking through what the LLM is saying is sufficient for verification, since I can look for internal consistency and check against things I know already. When exploring a new topic, often times my questions are superficial enough for me to be confident that the answers are very common in the training data. When exploring a new topic that's also somewhat niche or goes into a lot of detail, I use the LLM first to get a broad overview and then drill down by asking for specific sources and using the LLM as an assistant to consume authoritative material.
    • blibble 1y ago
      this "logic" applied across society will lead to our ruin
      • svara 1y ago
        Say more?
  • perching_aix 1y ago
    > from a sycophantic tutor that agrees with everything you say You know that it's possible to ask models for dissenting opinions, right? Nothing's stopping you. > and if they are never pointed out... They do point out mistakes though?
• elvis10ten 1y ago
  > LLMs make learning new material easier than ever. I use them a lot and I am learning new things at an insane pace in different domains. With learning, aren’t you exposed to the same risks? Such that if there was a typical blind spot for the LLM, it would show up in the learning assistance and in the development assistance, thus canceling out (i.e unknown unknowns)? Or am I thinking about it wrongly?
  • sulam 1y ago
    If you trust everything the LLM tells you, and you learn from code, then yes the same exact risks apply. But this is not how you use (or should use) LLMs when you’re learning a topic. Instead you should use high quality sources, then ask the LLM to summarize them for you to start with (NotebookLM does this very well for instance, but so can others). Then you ask it to build you a study plan, with quizzes and exercises covering what you’ve learnt. Then you ask it to setup a spaced repetition worksheet that covers the topic thoroughly. At the end of this you will know the topic as well as if you’d taken a semester-long course. One big technique it sounds like the authors of the OAuth library missed is that LLMs are very good at generating tests. A good development process for today’s coding agents is to 1) prompt with or create a PRD, 2) break this down into relatively simple tasks, 3) build a plan for how to tackle each task, with listed out conditions that should be tested, 3) write the tests, so that things are broken, TDD style and finally 4) write the implementation. The LLM can do all of this, but you can’t one-shot it these days, you have to be a human in the loop at every step, correcting when things go off track. It’s faster, but it’s not a 10x speed up like you might imagine if you think the LLM is just asynchronously taking a PRD some PM wrote and building it all. We still have jobs for a reason.
    • evnu 1y ago
      > Instead you should use high quality sources, then ask the LLM to summarize them for you to start with (NotebookLM does this very well for instance, but so can others). How do you determine if the LLM accurately reflects what the high-quality source contains, if you haven't read the source? When learning from humans, we put trust on them to teach us based on a web-of-trust. How do you determine the level of trust with an LLM?
• belter 1y ago
  > But if you're willing to learn, this is rocket fuel. LLMs will tell you 1 or 2 lies for each 20 facts. Its a hard way to learn. They cant even get their urls right...
  • diggan 1y ago
    > LLMs will tell you 1 or 2 lies for each 20 facts. Its a hard way to learn. That was my experience when growing up with school also, except you got punished one way or another for speaking up/trying to correct the teacher. If I speak up with the LLM they either explain why what they said is true, or corrects themselves, 0 emotions involved. > They cant even get their urls right... Famously never happens with humans.
    • belter 1y ago
      You are ignoring the fact that the types of mistakes or lies are of a different nature. If you are in class, and you incorrectly argue, there is a mistake in an explanation of Derivatives or Physics, but you are the one in error, your Teacher hopefully, will not say: "Oh, I am sorry you are absolutely correct. Thank you for your advice.."
      • diggan 1y ago
        Yeah, no of course if I'm wrong I don't expect the teacher to agree with me, what kind of argument is that? I thought it was clear, but the base premise of my previous comment is that the teacher is incorrect and refuse corrections...
        • belter 1y ago
          My point is a teacher will not do something like this: - Confident synthesis of incompatible sources: LLM: “Einstein won the 1921 Nobel Prize for his theory of relativity, which he presented at the 1915 Solvay Conference.” Or - Fabricated but plausible citations: LLM: “According to Smith et al., 2022, Nature Neuroscience, dolphins recognise themselves in mirrors.” There is no such paper...model invents both authors and journal reference And this is the danger of coding with LLMs....
• skeeter2020 1y ago
  >> LLMs make learning new material easier than ever. feels like there's a logical flaw here, when the issue is that LLMs are presenting the wrong information or missing it all together. The person trying to learn from it will experience Donald Rumsfield's "unknown unknowns". I would not be surprised if we experience an even more dramatic "Cobol Moment" a generation from now, but unlike that one thankfully I won't be around to experience it.
• threeseed 1y ago
  Learning from LLMs is akin to learning from Joe Rogan. You are getting a stylised view of a topic from an entity who lacks the deep understanding needed to be able to fully distill the information. But it is enough to gain enough knowledge for you to feel confident which is still valuable but also dangerous. And I assure you that many, many people are delegating to LLMs blindly e.g. it's a huge problem in the UK legal system right now because of all the invented case law references.
  • slashdev 1y ago
    It depends very much on the quality of the questions. I get deep technical insight into questions I can't find anything on with Google.
  • diogocp 1y ago
    > You are getting a stylised view of a topic from an entity who lacks the deep understanding Isn't this how every child learns? Unless his father happens to be king of Macedonia, of course.
    • kentonv 1y ago
      I can think of books I used to learn software engineering when I was younger which, in retrospect, I realize were not very good, and taught me some practices I now disagree with. Nevertheless, the book did help me learn, and got me to a point where I could think about it myself, and eventually develop my own understanding.
    • threeseed 1y ago
      Learning requirements of a child are different from an adult. They are fine with a lossy, imperfect version of how the world works.
• therealpygon 1y ago
  And yet, human coders may do that exact type of thing daily, producing far worse code. I find it humorous at how much higher of a standard is applied to LLMs in every discussion when I can guarantee those exact some coders likely produce their own bug-riddled software. We’ve gone from skeptics saying LLMs can’t code, to they can’t code well, to they can’t produce human-level code, to they are riddled with hallucinations, to now “but they can’t one-shot code a library without any bugs or flaws” and “but they can only one-shot code, they can’t edit well” even tho recents coding utilities have been proving that wrong as well. And still they say they are useless. Some people just don’t hear themselves or see how AI is constantly moving their bar.
  • brookst 1y ago
    And now the complaint is that the bugs are too subtle. Soon it will be that the overall quality is too high, leading to a false sense of security.
• conradev 1y ago
  Just wrong. Don’t do that I’d personally qualify this: don’t ship that code, but absolutely do it personally to grow if you’re interested. I’ve grown the most when I start with things I sort of know and I work to expand my understanding.
• paradox242 1y ago
  The value of LLMs is that they do things for you, so yeah the incentive is to have them take over more and more of the process. I can also see a future not far into the horizon where those who grew up with nothing but AI are much less discerning and capable and so the AI becomes more and more a crutch, as human capability withers from extended disuse.
• a13n 1y ago
  If the hypothesis is that we still need knowledgeable people to run LLMs, but the way you become knowledgeable is by talking to LLMs, then I don’t think the hypothesis will be correct for long..
  • mwigdahl 1y ago
    We need knowledgeable people to run computers, but you can become knowledgeable about computers by using computers to access learning material. Seems like that generalizes well to LLMs.
  • svara 1y ago
    You inserted a hidden "only" there to make it into a logical sounding dismissive quip. You don't get knowledge by ONLY talking to LLMs, but they're a great tool.
• catlifeonmars 1y ago
  I think what’s missing here is you should start by reading the RFCs. RFCs tend to be pretty succinct so I’m not really sure what a summarization is buying you there except leaving out important details. (One thing that might be useful is use the LLM as a search engine to find the relevant RFCs since sometimes it’s hard to find all of the applicable ones if you don’t know the names of them already.) I really can’t stress this enough: read the RFCs from end to end. Then read through the code of some reference implementations. Draw a sequence diagram. Don’t have the LLM generate one for you, the point is to internalize the design you’re trying to implement against. By this time you should start spotting bugs or discrepancies between the specs and implementations in the wild. That’s a good sign. It means you’re learning
• wslh 1y ago
  Another limitation of LLMs lies in their inability to stay in sync with novel topics or recently introduced methods, especially when these are not yet part of their training data or can't be inferred from existing patterns. It's important to remember that these models depend not only on ML breakthroughs but also on the breadth and freshness of the data used to train them. That said, the "next-door" model could very well incorporate lessons from the recent Cloudflare OAuth Library issues, thanks to the ongoing discussions and community problem-solving efforts.
• hammyhavoc 1y ago
  > LLMs make learning new material easier than ever. I use them a lot and I am learning new things at an insane pace in different domains. Sorry, but the the amount of bad information dispensed by models and the student's ability to go "hey, that's wrong" due to a lack of experience and knowledge means that this is going to lead to disaster very often. People already dispensing terrible information on YouTube because they trusted an AI to generate their voice-over script to explain something when creating learning materials.