That’s what the hype men say, but increasingly I don’t believe it. I read yesterday that most major AI systems cannot correctly answer “which is larger, 7.11 or 7.9?”.
Often I read of these strange examples, and struggle to remember each one or provide accurate examples when people challenge my claims that these systems still have many flaws. And fair enough. I’ve thought about that recently, and I think this is partly due to the fact that intelligence is a complex highly dimensional phenomenon, and failures in artificial systems manifest as all these weird little quirks and strange behaviors and failures and they are honestly hard for me to remember as an interested lay person.
That said, these systems have loads of shortcomings, and in particular they’re not good at learning from small datasets which means they can’t easily generalize to humanoids (for example) doing the millions of little real world tasks humans do. And they can’t serve as general algorithms for all software problems. They work well with text and pretty well with images but I think we will find for a long time to come significant shortcomings that prevent them from really manifesting as a truly general intelligence.
And I don’t know about this quantum stuff but until we actually solve AGI I don’t think we can really say with confidence what it takes to make intelligence function.