alt Hacker News> We "literally" couldn't design programs to do the interesting things LLMs can do.
That's a bit of an overstatement.
The entire field of ML is aimed at problems where deterministic code would work just fine, but the amount of cases it would need to cover is too large to be practical (note, this has nothing to do with the impossibility of its design) AND there's a sufficient corpus of data that allows plausible enough models to be trained. So we accept the occasionally questionable precision of ML models over the huge time and money costs of engineering these kinds of systems the traditional way. LLMs are no different.
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Saying ML is a field where deterministic code would work just fine conveniently leaves out the difficult part - writing the actual code.... Which we haven't been able to do for most of the tasks at hand.
What you are saying is fantasy nonsense.
> would work just fine, but the amount of cases it would need to cover is too large to be practical
So it doesn't work.
And all you have to do is write an infinite amount of code to cover all possible permutations of reality! No big deal, really.
It is impossible to design even in a theoretical sense if functional requirements consider matters such as performance and energy consumption. If you have to write petabytes of code you also have to store and execute it.