Comment by _hao | Hacker News Reader

Comment by _hao | Hacker News Reader

I won't try to predict the future as far as such ML models will take our jobs or not. However, I'd like to point out to most people that working on and studying fundamentals won't be a time wasted. Even if programming disappears as an employable job, people will still need to understand and learn things. You'll still need to know the math/physics/philosophy/history/literature/art/music etc. It might turn out that it's going to be more important than ever for us to be more confident and strict in our own skills and knowledge. And I'd also suggest to broaden our horizons. We should become good at a couple of different things like the polymaths of old.

IF you have to spend hours debugging ML generated code for something critical you better know exactly what you're doing. If you have to generate a Harry Potter Balenciaga meme video (the whole Balenciaga meme and all the different versions are hilarious btw) you better have some visual/art and musical sense in order to make it funny and engaging.

I think the end of the world is greatly exagarated. We actually have much bigger problems than "AI".

> I think the end of the world is greatly exagarated. We actually have much bigger problems than "AI".

Millions of people are going to have problems putting food on the table and providing a roof over their head, if the progress of these AIs doesn't halt immediately, or if some form of UBI isn't enacted.

If it keeps progressing in the current rate I think it's hundreds of millions world-wide, basically most of the middle class in the private sector in the developed world. Governments will HAVE to seriously retrain people (while giving them income) to become teachers, health care workers or wherever humans are still needed.

That's an opinion framed as a fact. It's equally likely that more people will have jobs as "AI" becomes increasingly adopted across sectors, where new jobs will emerge to integrate them, of existing jobs are supplemented by them.

Why half research "immediately"?

One sad, but possible, future is that it's not difficult to learn machine learning techniques, but to actually achieve anything with it you need hundreds of millions of dollars to spend on training and compute.

An existential double whammy; going back and forth between feeling you're smart enough to compete, if only you had the capital, and that the computers are smarter and better at everything.

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