491–500 of 725 posts
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 comp…
I disagree with the premise. Learning should not be done only as a direct path to getting paid. Learn to create pattern matching and intuition to solve future problems. When you are 17 it is a good time to understand how the world works so you can build on top of it in the future. If we assume most tech is going to have an LLM as part the stack, a solid basis in how LLMs work is likely to help you in future endeavors…
Earlier quoted context omitted.
If someone writes a browser in their teens, they will probably learn more about the web than if they were just writing web pages
They'll learn so much more that won't transfer to as many job opportunities. For ex, say more about C++ and less about cutting edge CSS (because modern browser tech is an ocean). I suppose they might luck into other adjacent or unrelated roles with the same skills.
Building a browser in the early web was actually a very achievable goal for exactly the reasons it isn’t now. There was not JS. No CSS. No SVG. In fact very few widely supported image formats (and graphical browsers weren’t around in the earliest days of the web anyway). TLS didn’t exist. HTML only had a subset of methods. And even POST was usually just managed by CGI/BIN calling an external process, often written in C++ or Perl.
It was a simpler time.
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 comp…
This is a wildly incorrect and myopic view on the world. Finetuning model is cheap and incredibly useful for deployment. You don't need to pre-train a frontier llm from scratch to make useful models. There is tons of domains where you and fine-tune llms and deploy them for value in companies and for your own entrepreneurship ambitions. I have made this a big part of my career for the last few years and now I'm workin…
But there are also a lot of prerequisites, namely does the enterprise have its sh*t together on a technical level. Does it have the processes and data pipelines available to train and benefit from these models? Probably not!
Applied ML is at the crown of a tech pyramid whereas most enterprises are still struggling at ground level. Being able to build from be ground is likely a safer skillset than only knowing how to work at the (non-existent) apex.
Earlier quoted context omitted.
If someone writes a browser in their teens, they will probably learn more about the web than if they were just writing web pages
They'll learn so much more that won't transfer to as many job opportunities. For ex, say more about C++ and less about cutting edge CSS (because modern browser tech is an ocean). I suppose they might luck into other adjacent or unrelated roles with the same skills.
That’s like saying someone who fabricates cars doesn’t have the skills to drive them. Perhaps not, but they’re very well placed to pick it up quickly. They’ve also shown they can do something far more challenging, which is actually better than hiring for narrow immediate skills.
In other words: I’d hire that candidate in a heartbeat.
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…
You're right that it's probably a little too in the weeds, but it's also a nice clear and fun objective that teaches you the basics. Like building a TODO list in JavaScript to learn webdev or a Gameboy emulator in C++ to learn how a CPU works.
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…
Since he has not given any reference point it is equally as good advice as „just learn everything slightly valuable“.
So the real question is: „What should I not learn in favor of learning this.“
Or in other words: His comment is not usable because it can mean anything or nothing.
Earlier quoted context omitted.
Yes. It's like looking at the (Apollo) moon rocket launch and then suggesting teenagers should learn to build rockets in their garages for the coming space age. It is viable as a toy project, but there are vanishingly few career opportunities.
It's like looking at the early internet and then suggesting teenagers should write browsers as their projects instead of webpages.