>The amount of computations for a human to do the same tasks is thousands of orders of magnitudes less.

That may very well be true now. And in fact, this was true of more rudimentary calculations early on in computing history, where humans were definitely more efficient, particularly for more abstract mathematics. But Moore's Law comes at you fast. Even without more efficient compute, it's rather wild how much more efficient models are becoming these days just from algorithmic and training improvements.

So, maybe for now, certainly. Are you confident that will be the case in 5-10 years? And is that really your barometer for success?

>And when a human learns these things they usually remember how to, and are able to extrapolate that knowledge into new and fresh problem spaces.

That is certainly a limitation for now, but plenty of academic research is being done on how to address that in a more individualized way. That said, the models also have the advantage of synthesizing learnings from user interactivity back into a future release and essentially applying that globally, which is pretty neat.

There's also some cool techniques to sort of bridge the gap today, like compound engineering.

>Next time you get a new and a fresh and an inspiring idea, and you spend hours solving a unique problem nobody has ever done before. You can take comfort in the fact that a few months later some lame and uninspiring developer can write the same problem in a prompt and get the plagiarism machine to steal your work, just in a more lame and uninspiring way.

But that's the thing: it's becoming pretty clear that the "plagiarism machine" can probably take that same problem in a prompt, having never been trained on my code, and still solve it.

In that case...maybe it doesn't feel great to have someone copy my idea. But that is certainly not plagiarism in the way you mean it. And when you put ideas out into the world, you can't be certain that someone else won't copy and remix it into something new. That's kind of how the world works already, but we're just seeing the barrier to entry decline.

> Are you confident that will be the case in 5-10 years?

Yes, I am. I am very confident that general purpose digital computers will never be more efficient then human minds in generating moderately complex code.

Why am I so confident... Well, it has been over 10 years since AlphaGo beat top go player Lee Sedol. AlphaGo was able to beat the a world class go player by doing several thousands orders of magnitude more computations then Lee Sedol, and it did so by spending several orders of magnitude more energy then the top human go player. Today, over 10 years later, the top go machines are able to beat world class go players much easier, but still do so using the exact same strategy of outcomputing the humans with thousands of orders of magnitude more computations, and spending orders of magnitudes more energy.

Things did not change in the past 10 years, I see no reason why it should change 10 years from now.

>Things did not change in the past 10 years, I see no reason why it should change 10 years from now.

Has it not? Why do you say that?

Also, do we still require a Deep Blue sized supercomputer for chess? :)