Paul Graham: If I Were 17, I'd Learn to Build LLMs from Scratch

I were 17, I'd learn how to build LLMs from scratch

Paul Graham: If I Were 17, I'd Learn to Build LLMs from Scratch

In a tweet, Paul Graham advises a hypothetical 17-year-old to learn how to build LLMs from scratch and train them on accessible hardware, rather than starting a startup. He argues that deep understanding of LLMs would lead to better startup ideas later. Yann LeCun responds, suggesting he'd investigate why LLMs can write essays but not clean bedrooms, and study methods beyond LLMs to address physical tasks.

Notice that what I would not do is try to start a startup. Instead I'd build the foundation of knowledge to base a startup on later.
  1. oersted

    There's this dilemma where in theory there's a ton of demand for engineers that can do real LLM machine-learning, but in practice there are very few available positions and entrepreneurship opportunities.

    The reality is that an incredibly small minority of companies in the world do any real training or optimisation. It's unnecessary and inefficient for most purposes unless you are fully dedicated to being an LLM company, and still then it's a struggle. Those few that do train, they spend most of their budget on compute and have relatively small teams.

    Getting experience in this field requires having access to very expensive hardware to begin with. And the skills will be quite hard to convert into any real value for someone, leading to a decent income, unless you have a ton of funding from patient investors, or you have decent contacts in Bay Area networks to get hired at the right place.

    With all due respect, paulg is in somewhat of a bubble, this is not congruent with the global situation.

  2. mattlutze

    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.

  3. koe123

    While knowledge is always great, I would encourage people not to seek advice from successful people like this (survivorship bias).

    Moreover I am not sure it is even good advice? Would you advise a 17 y.o. to learn how transistors work or how to code (i.e. is LLM training the right level in the stack)? LLM training, a discipline where relevant work is already out of reach for 99.999% of budgets really as essential as this post implies?

  4. fancyfredbot

    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 t […]

  5. fnoef

    If i were 17, I'd try to distinguish who to take advice from, and would definitely learn that VCs have interest to spread a specific agenda in their message. Also, I would get drunk and have as much fun as could, as the misery of working under the treat of being replaced by AI, would simply kill any desire to live past 25.

  6. chris_va

    I am kind of amazed how negative the comments are here, especially on HN.

    Learning to hack something together in high school using the latest technology (vacuum tubes, radios, microprocessors, web/javascript) has been a common theme in the tech world for generations. With LLMs and online tutorials, this isn't even a difficult suggestion. Do people think learning new tech is somehow wasted effort?

  7. greenowl

    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.

  8. felixrieseberg

    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.

  9. Chance-Device

    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.

  10. geremiiah

    I'm usually a fan of pg, but this post is ignorant of modern AI technologies. Building an LLM from scratch is both a trivial and a useless exercise. There's probably in the range of 5000 github repos doing exactly that. What makes LLMs work is scale, and what makes engineering and training LLMs hard is also scale. And scale is not something you can achieve in your garage.

    If the goal is to understand LLMs deeply, one would be better served by either joining one of the big AI companies or doing a PhD.

    And to be honest, I think this journey should have been started 5 years ago, because right now there's too much competition.

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