alt Hacker NewsThe amount of computations for a human to do the same tasks is thousands of orders of magnitudes less. 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 how the first person to run CPython in WASM did that, and that is why the plagarism machine can now do the same (only a thousand times more lame and uninspiring).
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.
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> The amount of computations for a human to do the same tasks is thousands of orders of magnitudes less.
OK then - do it, faster.
> You can take comfort in the fact that a few months later some[...] developer can [solve] the same problem [using your work]
Isn't that what collaboration and sharing software is supposed to be all about?
>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.