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Comment by jvanderbot | Hacker News Reader

I'm biased, but I think the answer is semi structured problems.

Automating a tractor that has to till or seed is much easier than a self driving car, and alleviates some very low margins high labor intensive activities.

(I work at a place that is automating logistic yard operations, which is fixed cost, well structured, and predictable problem/environment)

I think "everywhere all the time" AI for chat, driving, coding, or medical image analysis etc is a pipe dream absolutely. And what we will lose when it all pops is the pragmatic solutions to solveable problems that sound more like "algorithms for assistance occasionally or part time".

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> ... semi structured problems.

i think i agree with this,

> I think "everywhere all the time" AI for chat, driving, coding, or medical image analysis etc is a pipe dream absolutely.

but i'm not sure i'd put medical image analysis in this group. i mean, aren't there already several examples of software outperforming humans in this domain?

There are also several examples of software outperforming drivers. Yet here we are with a growing suspicion of self-driving cars.

There's no extreme correct. The correct future is a blend of software and human control, with, I suggest, a bias towards software in well-structured areas, and a strong bias towards huamns elsewhere. And it's humans after all that would structure the world for software. That's fine, it's how it's always been with machines. We just don't want to throw the baby out with the bathwater when we lose trust in "AI".

Where I work, we use AI for tasks that are similar to analyzing medical imaging (but not medical). It easily outperforms humans. Not in terms of accuracy in identifying features -- it's about the same as people in that -- but in terms of speed.

That seems true for both chatgpt and ai art programs. The output is unverifiable, often crap, and very fast to get. I'd argue we're losing something if we make it impossible for human experts to get trained in professional settings by outcompeting them with ai.

> semi structured problems

What's the state of the art with A.I. digesting RDF, OWL, and the like ?

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