Real World vs Computer Abstractions

Observation that easy progress happens inside computers while hard work involves hardware errors, human input, and edge cases that AI struggles with

The commenter suggests that current AI development mirrors the early blockchain era, where progress appears rapid only because it remains confined to clean, internal computer abstractions. While building clever algorithms is "fun" and "easy," the truly difficult work lies in bridging these digital models with the messy reality of hardware errors, leaky APIs, and unpredictable human input. Drawing a parallel to robust databases like SQLite, they argue that the majority of essential code in any mature system is dedicated to handling "impossible" edge cases rather than core features. Ultimately, they warn that the current AI gold rush focuses on the "happy path," while true utility will only be found by tackling the unglamorous friction of the physical world.

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Boy this smells a lot like early days of blogging about block chains, specifically ethereum and friends.

It's not that there's nothing useful, maybe even important, in there, it's just so far it's all just the easy parts: playing around inside a computer.

I've noticed a certain trend over the years where you get certain types of projects that get lots of hype and excitement and much progress seems to be made, but when you dig deep enough you find out that it's all just the fun, easy sort of progress.

The fun progress, which not at all coincidentallly tends to also be the easy progress, is the type that happens solely inside a computer.

What do I mean by that? I mean programs who only operate at the level of artificial computer abstractions.

The hard part is always dealing with "the real world": hardware that returns "impossible" results to your nicely abstract api functions, things that stop working in places they really shouldn't be able to, or even, and this is the really tricky bit, dealing with humans.

Databases are a good example of this kind of thing. It's easy to start off a database writing all the clever (and fun) bits like btrees and hash maps and chained hashes that spill to disk to optimize certain types of tables and so on, but I'd wager that at least half of the code in a "real" database like sqlite or postgresql is devoted to dealing with strange hardware errors or leaky api abstractions across multiple platforms or the various ways a human can send nonsensical input into the system and really screw things up.

I'd also bet that this type of code is a lot less fun to write and took much longer than the rest (which incidentally is why I always get annoyes when programming language demos show code with only a happy path, but that's another rant and this comment is already excessive).

Anyways, this AI thing is definitely a gold rush and it's important to keep in mind that there was in fact a lot of gold that got dug up but, as everyone constantly repeats, the more consistent way to benefit is sell the shovels and this is very definitely an ad for a shovel.

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