Was it? Alpha-beta pruning is from 1957 they had a decent idea chess of what human-beating computer chess would be like and that it probably wasn't some pathway to Turing-test-beating AI.

But because AI is not like us, we have different results at different stages — eg, they’ve been better at arithmetic for a hundred years, games for twenty, and slowly are climbing up other domains.

But I think general problem solving is a part of it. Coming up with its own ideas for possible solutions rather than what it generalized from a training set, and being able to try them out and iterate. In an environment it wasn't specifically designed for by humans.

(not claiming most humans can do that)

My dog doesn't know what I do for a living, and he has no concept of how intelligent I am. So if we're limited by our own intelligence, how would we ever recognise or measure the intelligence of an AI that's more advanced than us?

If an AI surpasses us, not just in memory or calculation but in reasoning, self-reflection, and abstraction, how would we even know?

It was seen as so difficult to do that research should be abandoned.

Projects in category B were held to be failures. One important project, that of "programming and building a robot that would mimic human ability in a combination of eye-hand co-ordination and common-sense problem solving", was considered entirely disappointing. Similarly, chess playing programs were no better than human amateurs. Due to the combinatorial explosion, the run-time of general algorithms quickly grew impractical, requiring detailed problem-specific heuristics.

The report stated that it was expected that within the next 25 years, category A would simply become applied technologies engineering, C would integrate with psychology and neurobiology, while category B would be abandoned.

https://en.wikipedia.org/wiki/Lighthill_report

that's what the exponential lift off people want right

For now, this is a good thing: Given how generally LLMs are displacing juniors, if this was a situation where doing the same thing but harder can replace experts, it replaces approximately all of them.

But: in limited domains, not the "G" of "AGI" but just specific places here and there, AI does beat human experts. Those domains are often sufficiently narrow that they don't even encompass the entire role — think "can analyse an X-ray for cancer, can't write up its findings" kind of specificity. Indeed, I can only think of two careers where even the broadest definition of AI (some kind of programmable system) has been able to essentially fully replace that occupation:

1. https://en.wikipedia.org/wiki/Jacquard_machine

2. https://en.wikipedia.org/wiki/Computer_(occupation)

Depends on what you consider a "Turing's Test".

Fooling unsuspecting humans is relatively easy, it has been done with relatively simple software and some trickery. LLMs can do that too of course.

A more convincing "Turing's Test" would be:

- You have one interrogator, and two players, one human and one computer

- The interrogator, after chatting with both players has to find which is which

- The interrogator is an expert in the field, he knows everything there is to know when it comes to finding the computer

- The human player is also an expert, he knows how to solve problems that are hard for computers to solve, he also knows what to expect from the interrogator

- The interrogator and human player collaborate to find the computer

- The interrogator and human player are not allowed to have shared information that the computer doesn't have (and ideally, they shouldn't know each other personally), but everything else is fair game