I feel similarly. Much worse, I cynically worry sometimes that the criticisms of the 60s/70s "AI Boom" are what got "lost" rather than any major advancements we

I feel similarly. Much worse, I cynically worry sometimes that the criticisms of the 60s/70s "AI Boom" are what got "lost" rather than any major advancements were "gained" since. A lot of 60s/70s optimism indeed got eaten by a general sense of "if we just had more storage and speed and larger datasets" (as we'd suspect from what we saw in recent improvements), but some of it got eaten by "it produces reasonable looking results but here's all the reasons it's a sandcastle of sparkling statistics that falls apart as the training set grows worse". I have a worrying gut feeling sometimes that so much of current ML enthusiasm missed some of those 70s/80s memos on reasons to be concerned about applying some of these "sandcastles" to the "hurricane" of modern data. We may have only massively scaled garbage in, garbage out more than anything else this AI/ML boom.