“as if brains are getting instinct… “

Not sure what you’re trying to say here?

Those three points (taken from Searl btw) are not neccesary conditions of AI, they are categorical distinctions of AI types, which are, Turing test, symbolic reasoning and sentience.

i) Turing test

Turns out to extrememly easy (relative to the other two) to “pass” this. Humans are so vain and shallow that all you have to do in order to convince them that they are having an intelligent conversation is take their own words, change them a bit and feed them back to them. You can do this in a few hundred lines of code. Many people will happily chat with Eliza-like chat bots for ages before getting bored with their own reflection.

ii) Symbolic reasoning

This is the step that is currently challenging to us. Contrary to the TFA summary and some other comments, parsing is not the difficult step. The ability to deconstruct well written language and extract meaning and intention is quite possible, although borderline syntactic constructs are notoriously difficult, ie “The boat floated down the river sank” The difficult step is to represent this and perform useful operations akin to human-like reasoning upon it. Blocks-world type limited reasoning is possible – the domain must be kept very small. This is the domain of expert systems and knowledge based systems which have been around since the 1950s.

iii) Sentience

This is the big one. This is what most people understand by intelligence. There is not even any common sense definition of it let alone some hint of a plan to achieve it. Many hypothesise the key to this is deep recursion and self reference, others assert that consciousness is necessarily like schizophrenia and requires at least two computers each mirroring the other (as in left-right brain). Some think it merely a matter of critical complexity. Noone really knows and probably will not within our lifetimes.

Good introductory texts to read (imho, – these were all second year AI texts I read in the 1980s) on this subject are Churchland, Searl, Minsky, Hoffstadter, Dennet. Another interesting book is Penrose, which deals specifically with sentience. I recommend Jackson on expert systems and Bishop on neural nets.

It’s worth noting that this comes from an Israeli research company. Many Israelis are notorious fantatsists and masters of talking up bullshit research projects to attract money. In recent years they have “invented” force-fields, time-machines, God knows what else. I always pronounce it “Isn’t Really Research”

So this is just a KBS using Wiki as input . Stanford did this back in the early 1990s with a smaller database of human knowledge and basically concluded the idea was dumb. It is more likely to fail with a larger database, not less because the problem is permuatative complexity. The only way to achieve any semblence of AI is to use neural topologies that collapse the dimensions of the data set into something managable, but these take a long time to train.