The thing with pointing out "AI can't do X!" is that, if you keep refining X into something narrow and precise enough, you'll eventually cross a threshold where a realistic amount of engineering and training data make X possible.
AI can always do *specific* things -- as long as they're sufficiently specific and you're investing sufficient effort / data.
The problem with AI isn't that it can't do a specific X, it's that it has basically no intelligence at all at this time. No general cognitive abilities.
The problem with AI isn't that it can't do a specific X, it's that it has basically no intelligence at all at this time. No general cognitive abilities.
Intelligence simply means moving to a different part of the specificity / effort spectrum, one where you can master broad tasks with little effort.
You can always make up for a lack of intelligence by reducing task uncertainty (making X more specific) or investing more effort.
You can always make up for a lack of intelligence by reducing task uncertainty (making X more specific) or investing more effort.
No matter how stupid the student, they can always pass the exam if you give them a set of problems very similar to what they will be tested on (reduced task uncertainty), and if they're willing to spend countless hours studying them (more experience).
What's hard is to improvise from little experience in the face of high uncertainty and novelty. That's what biological intelligence has evolved for. That's what current algorithms and models can't do at all.
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