Backpropagation is a leaky abstraction (2016)

Karpathy's contribution to teaching around deep learning is just immense. He's got a mountain of fantastic material from short articles like this, longer writing like https://karpathy.github.io/2015/05/21/rnn-effectiveness/ (on recurrent neural networks) and all of the stuff on YouTube.

Plus his GitHub. The recently released nanochat https://github.com/karpathy/nanochat is fantastic. Having minimal, understandable and complete examples like that is invaluable for anyone who really wants to understand this stuff.

I was slightly surprised that my colleagues, who are extremely invested in capabilities of LLMs, didn’t show any interest in Karpathy’s communication on the subject when I recommended it to them.

Later I understood that they don’t need to understand LLMs, and they don’t care how they work. Rather they need to believe and buy into them.

They’re more interested in science fiction discussions — how would we organize a society where all work is done by intelligent machines — than what kinds of tasks are LLMs good at today and why.

If everyone had to understand how carburettors, engines and break systems work; to be able to drive a car - rather than just learn to drive and get from A to B - I'm guessing there would be a lot less cars on the road.

(Thinking about it, would that necessarily be a bad thing...)