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The original study explicitly argued for deliberate practice. Musicians who didn't do that could not become experts.

Super interesting, when Quantum computing would enable really large models, or much larger contexts. But QRAM is even more behind than pure fault-tolerant gates.

I also don't like this focus on practical applications. It is true for me as an engineer, that in the end I want to build something. But when I force myself to focus only on the practical part, just as you said, the whole context is missing. There is this meme of a guy still living with his parents, and trying to acquire all knowledge. This is actually a dangerous mind virus. Learning is an idle activity, often confused with being a do no good. But for me at least this is the only way to really grok something. In university at the summer break, I could only really go through the math and enjoy it, without the stress of exams and cramming. And now it is the same, I learn things idly, and trust in the universe that the application will come, which it always does somehow.

it's only because you can send texts via imessage on a macmini. that's it.

For me that creativity is very well expressed by the principle of abduction. With induction, generalise towards rules, or deduction, use rules on data, we have this combination of patterns via different contexts. I think abduction might not be possible via LLMs.

It is a bit like in "Profession" by Isaac Asimov. We will still have the need for some people who will write code manually, fix the craft. We will need the "Feeble Minded" asylum that is actually a secret sanctuary for society's true creators. Because everyone else relies on generated code, they can only repeat what is already known. Only the people who learn the hard way through actual studying possess the creativity and intelligence required to invent new knowledge and create new educational tapes.

Always store the location, too. Space-Time is a thing.

that's why I still love the quest3, just for the potential. but xreal makes more sense, and then a more open platform. but I think post-covid we approach neuromancer more than ever.

I feel like Qiskit is the standard nowadays, and maybe because of the early mover advantage it will prevail after NISQ (Noisy Intermediate-Scale Quantum). It's actually just a Python framework.

there's actually a really good book that bridged it well for me when I was doing my bachelors, A Little Java, A Few Patterns. this is from the famous lisp books for groking FP.

I think it all depends on the shape of the problem. I love Prolog for its expressive power, sometimes. Complex simulation problems are really nice to model in OCaml or CLOS, and then again, maybe remodelling in Prolog brings some insights. And often writing a recursive function in Lisp is all you need to understand a complex system. It's all layers. An outer shell to prolog would be a theorem solver for example, because Prolog is a very rudimentary one.

Yes, I also tried coffee first time when in England when 13, and it was like a revelation. I understand that beer and cigarettes are an acquired taste, they tasted terrible, but coffee was a love at first sip.

When doing my Bachelor degree my dad gave me an old thinkpad to run on linux. It was a horrible experience for preparing powerpoints, papers, etc. But I still have that command line muscle memory and an eye to spot errors which really helped me in my career. In my final year I bought myself a macbook because I earned real money doing a consulting internship. But the unix muscle memory stayed, and I found working with IDEs so wasteful. In my first years at my job I rejected word and excel still to do everything in groff and awk.