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  • Yeah, no way.

    I'd move to the middle of nowhere and work multiple jobs on a farm and in construction. Learn how to grow food, and build things. Meet the farmer's daughter, and marry her. Then, buy my own land, grow my own food, and build my own things.

    by greenowl
  • I already do this. I live in a small village where there isn't even a wired Internet connection (wireless only). I work full-time with LLMs, on own product ideas and client projects (all LLM led).

    I started investing in farms, have 50 pigs and 100+ chickens now. We are planning to grow to 100 pigs and 2000 chickens in a year. We will start growing Shiitake mushrooms in a few months too.

    by brainless
  • Slight problem with step “buy my own land”. Your working 2 blue collar jobs and paying rent are incompatible with this plan.
    by y-curious
  • I get this is basically advice for young founders and entrepreneurs, but i would ignore that request and encourage 17 year olds to spend time trying to find a happy medium between work and life.

    Being a super rich and an unhappy workaholic, or a super-impressive engineer who wakes up one day at 45 and realizes they regret wasting half their life (I ran into way too many of these) is a much worse fate than "not being rich from your startup" and working a relatively regular job while feeling fulfilled and happy by more than just work.

    Especially in the US, which is uniquely bad at this and encourages people to work themselves to death, mental health and work life balance are much more valuable things for 17 year olds to focus on than finding good startup ideas.

    In case you think i'm being a bit dramatic, let's look at the state of 17 year old mental health in the heart of Silicon Valley:

    "The City of Palo Alto and the Palo Alto Unified School District approved a funded contract to place 24/7 human security guards and monitors at all four local Caltrain grade crossings, including the Churchill Avenue crossing directly adjacent to Palo Alto High School."

    (in case it's not obvious, it's because of suicides by high school students)

    The 17 year olds do not need advice on better startups, and this situation will never get better if we focus our advice on how to be better at work instead of how to be better at life. This will require redirecting the conversations.

    by DannyBee
  • Thank you. They need human contact, not more "sit in a room alone and get stressed as fuck for little ROI" tech bullshit. Unless the kid has a genuine, self-motivated interest in learning these things (a great, positive thing that should be nurtured), they should file pg's advice under "ok boomer."
    by rglover
  • If I were 17 again I'd prepare to go for volunteering overseas after high school for 1-2 years (plenty of free options in the EU where you might only need to cover the plane ticket). See the world, you learn a new language, help others and then think about what you want to do.
    by haunter
  • I think a problem a lot of people are grappling with here is that due to LLMs and AI generally, it’s basically impossible to predict what the future will look like or what jobs will still be around.

    I’d probably say something like: do something you enjoy and seems like it might be useful, but accept that the pace of change may mean that whatever you study ends up being irrelevant.

    Whatever solution there ends up being to this, it’s not going to be one that an individual 17 year old can implement. We’re past the point where individual good and bad choices matter that much to economic outcomes.

    by Chance-Device
  • I would advise any somewhat ambitious 17 year old to avoid tech and get into healthcare if they can stomach human interactions and bodily fluids. Sure, it is not all sunshine and rainbows, but there will still be plenty of work helping people who are ill or elderly. Even in the worst-case economic scenario, medicine will be a more socially rewarding and stable life path.
    by maciejzj
  • I appreciate the sentiment and I'm pretty curious how I could train an LLM, even are really basic one from 5yrs ago without nuts hardware.

    That said, I a good starting point for a 17yo is reading about perceptrons[0], then the basics of neural networks[1] (ex. 3-layer perceptron) then writing a program to train a 3-layer perceptron and classifying the MNIST dataset[2] - a dataset of characters.

    This can anywhere between a day and a week and you will demystify the basics of neural networks and work your way forward with more advanced contemporary concepts.

    Fun fact: any multi-layer perceptron neural net can be reduced to a 3-layer perceptron network.

    [0] https://en.wikipedia.org/wiki/Perceptron [1] http://geeksforgeeks.org/deep-learning/neural-networks-a-beg... [2] https://www.kaggle.com/datasets/hojjatk/mnist-dataset/data

    by oldsklgdfth
  • Horrible advice. This may have been good advice 10 years ago, but not today. There are no positions for people who "kind of understand how toy LLMs work" because so many engineers do these days. Most of the real LLM optimization work is at the edge of research and highly proprietary and not something you could ever do without infra that costs millions.

    But of course, 10 years ago this wasn't obvious.

    by loveparade
  • Very silly reply. If you learn how toy LLMs work at 17 don't you think that would help you at university and grad school? There's plenty of time to go into the private sector workforce later.
    by Myrmornis
  • What would be better advice for a 17 year old?
    by wy35
  • Yeah he's a moron with a lot of money, that's about it. I'm sure he's said the same thing about various other bags he had bets on throughout the years.
    by dakolli
  • you don't reach cutting edge immediately. you start with the basics
    by aero-glide2
  • The point of courses like "Nand to Tetris" is not to become CPU designer. It is not useless just because you can't build a chip factory.

    Watching Karpathy's "Zero to Hero" won't make you AI specialist. It will improve your understanding of the basics.

    by d0mine
  • I agree more with Yann LeCunn's salty reply. Over long run, knowing how autoregressive language models work from scratch will be just one step in having foundational understanding, and they might become dated... like knowing how a CRT monitor work. Something of historical interest and good for learning, but not crucial to being well-rounded.

    There are other types of models like diffusion models right now that are showing more efficiency and have a higher ceiling for improvement. Understanding math and fundamentals are more important.

    by LarsDu88
  • Yann has been consistently wrong about the limits of LLMs.
    by lern_too_spel
  • As someone who's at a similar age and was interested in learning how to do this, there just aren't enough resources to do so. Most LLM research is in the form of academic papers, and there isn't any 'popular' way to learn these things, and besides that all said research assumes you have a B200 cluster ready to go. If you have weaker hardware (say an 8GB nVidia GPU, which is what I have) you're going to be limited to fine tuning small models or torturing yourself working the GPU for days per iteration trying to run things like https://github.com/karpathy/nanochat, which is hardly an educational experience. Renting cloud GPUs is expensive, and at this age the most I could muster up for experimentation is probably $100 or so, which only gets me 25 or so hours on a B200 which just isn't enough. So why would I bother myself with this if I'm already at a disadvantage because of not having access to the right hardware and when surely there are better ways to spend my time? I concluded the only way to learn and be competitive is by finding work at an AI lab somehow (not happening at 17), or studying ML at the right university.

    Putting this in contrast with programming, I learned coding when I was 8, and it was incredibly stimulating to learn because you can quickly iterate and there were thousands of books and YouTube tutorials that dumb everything down and teach you fundamentals. All you needed was a $300 computer, and you can learn nearly anything you want, without being gatekept from this or that because you don't have enough vRAM / an sm_100 GPU.

    by deepllm
  • I'll use this post as a shameless opportunity to tell more people about a little side project, I made:

    http://languagemodelbuilder.com teaches you (in a few hours to days) how to build an LLM from scratch. It's entirely free, without accounts, and without data collection.

    by felixrieseberg
  • This is great, thank you!
    by le-mark
  • Mac only? Wild.
    by darksim905
  • Beautiful work! What prompted you to build this? Pun not intended.
    by bentt
  • Man, this is excellent! thank you so much for sharing this for free
    by zethsg
  • This is the coolest link I saw on HN the last 2 months. You rock man !

    Thanks a ton for building this.

    by teitoklien
  • Nice! Please post screenshots and videos for people not ready or able to install yet.
    by spolitry
  • I wish this was available for young folk in Romania: As it happens: macOS: 2.70% of desktop operating-system usage in Romania; OS X: 2.55%; Combined Apple desktop share: approximately 5.25%; Windows: 90.65%; Linux: 4.02% or so AI tells me.
    by vixen99
  • I'm (more than) twice that age, but I've spent time learning this exactly this from videos by Andrej Karparthy and from books by Sebastian Raschka.

    I didn't do it because it was useful to me in a practical sense. It's because LLMs are fascinating and I want to know how they work. From that perspective it's been a great experience. I have afirm grasp of the basics. This makes it much easier to understand frontier concepts like compressed latent attention. I can follow the field and understand it.

    Not sure I would have got as much out of it at seventeen. I have a lot of background and experience which made it much easier to learn. I wasn't struggling with the linear algebra or with python. I already knew pytorch and neural networks. That helped a lot and I covered these tutorials fast and could skip over large sections. A few evenings and the odd weekend day over a couple of months was enough for me.

    For seventeen year olds the tutorials are good enough to make it possible to learn this but it would have taken a lot longer to understand. On the other hand I would have learned a lot more. I think I would have learned a lot of valuable stuff.

    However I also think 17 year old me was studying for his A levels and probably this was right choice in terms of maximising future opportunities. I'm not sure I think learning about LLMs instead is sensible. Indeed it might be bad advice. But I can absolutely agree with the sentiment.I think 17 year old me would have wanted to do this too.

    by fancyfredbot
  • so can u explain to me how they are works?
    by firemelt
  • Which resources from these two would you recommend? Or just blanket-recommend all their videos/books?
    by sarmike31
  • A lot of people here are responding to the message but not to the meaning.

    It would be a good idea for young people to deeply know how these programs work. Not so that they can spend their career building them, but so that they can approach the next class of problems we'll all start trying to solve, with intuition all the way down to the weights and underlying mathematics. And also, to develop a healthy intuition of when "Just LLM it" will not be the right choice.

    "Build an OS" wasn't a common university project because we were all expected to go out and work on Windows, but because understanding the bare-metal firmware for a computer helps you deeply understand how to intuit building for a whole class of problems.

    by mattlutze