Artificial Intelligence Is Stuck

> If I am following you correctly, you are arguing that walking is a harder problem than language because it took much longer to evolve.

This is a thorny subject. So I am saying that in some objective way, walking is harder than language because Nature took millions/billions of years to traverse the solution space. Then... once we had a huge number of preconditions existing, then we had the development of language.

I am not saying that this means if it takes 10 years to develop language with some artificial means that it will take 100,000 years to develop walking.

What I am pointing to is that we ought to appreciate that if even blind natural selection took that long, then the possibility space to develop a nervous system must be much larger than we have anticipated.

As evidence of this: consider how (at least in popular culture, but also in comp sci in the old days) we developed chess playing computers and it was broadly assumed that breakthroughs in getting robots to walk and talk would soon follow through. That did not happen. It was a natural assumption but it was wrong.

> This seems to assume that a facility for language and advanced mathematics is independent of the existence of a nervous system capable of flexibly interacting with the environment, but it seems plausible, indeed probable, that language, consciousness and math depend heavily on the prior neural infrastructure, and their development was the most recent step in a process that has been going on since the evolution of the first synapse.

I don't know the answer to that. On different days I think one or the other is true. On Day #1 I think Nature obviously required walking before talking, but we could develop them differently, just has we didn't need to develop better horses to produce cars. On Day #2 I think to myself there's a deeper sense in which you really do require walking before talking because otherwise why didn't Nature develop biological microlife which evolved communications ability long before it developed legs. So...

> On the other hand, I am skeptical of the somewhat popular view that the key to generalized AI is to make robots that interact more thoroughly with their environment, and that they will then find their own way to language and consciousness.

We cannot be certain consciousness or intelligence are high probability events once you have life. We could be like those French artifact makers who made such exquisite mechanical toys for the aristocracy but ultimately got nowhere whereas the English inventors meddling with water and steam power really kicked off a revolution.

Who is Silicon Valley is genuinely looking at the fundamentals of A-Life or AI? OpenAI? MIRI? Stanford? DARPA?

> Working at a startup does not make you an expert. Especially when your opinion goes against what pretty much everyone else in the field thinks.

Achievements are perhaps the best yardstick for expertise. Whether a person has worked at a startup or has contrarian viewpoints are both irrelevant.

Gary Marcus was co-founder and CEO of Geometric Intelligence, successfully raised some money and grew a team, [1] then successfully sold the company to Uber, after which he directed Uber's AI lab. He has a PhD from MIT in cognitive science. And he's been a professor of Neural Science at NYU for nearly 20 years. [2]

I'm no expert, but he seems like one to me.

[1] https://www.crunchbase.com/organization/geometric-intelligen... [2] https://www.linkedin.com/in/gary-marcus-b6384b4/

I'm sorry if 'low-hanging' comes off as disrespectful - I'm just guessing that aspects of embodiment, once understood, will be capable of fairly trivial description and reap large consecutive rewards. I remember your u/n from other posts, we seem to have similar interests but you are vastly more educated in the engineering of AI. What's your background, if you don't mind sharing here?

I am suspicious non-contingent aspects to cognition remain that simulation and deep learning don't necessarily grant, though they might well be sufficient. I'm not smart enough to be sure, and I'm stretching for a description: a child self-reared to adulthood in the wild won't display what we usually consider essential facets for 'humanlike' levels of intelligence or competence. We're hardly trying to build a caveman.

They lack whatever is crucial in socialisation -- the ability to make subtle differentiations between other agents' actions and motivations seems to endow self-awareness, and abstractions for successfully handling novel objects and ordering perception relevance. Successful generality to our degree seems to be better 'outsourced' rather than hard-coded into solo agents, at least in the natural examples. Though I understand that's not necessary, perhaps there are good reasons for it. I feel like the first AGI will actually look a lot more like "multiple similarly 'perspected' AIs interacting with one another leads to each carrying the G in AGI". Essentially I'm suggesting it's hard to have generality and relevance to our proficiency (or better) without a 'culture'.

What I'm thinking seems to boil down to inserting some of Piaget's ideas into the philosophy of AI, which might be a bit much, and I'm open to charges of bullshit.

I can't even imagine what relevance magic would have to any of this.

Totally agree

The work on textual understanding is definitely still early days (though the press release makes it seem like it's understanding the entire LOTR, it's just reading a very structured short version) but already crazy impressive: https://venturebeat.com/2015/03/26/facebooks-latest-deep-lea...

On visual QA, Francois Chollet's talk at the TensorFlow dev summit shows how easy it is to get a (again constrained to 1-word answers but still very impressive) video QA system working in like 20 lines of Keras: https://www.youtube.com/watch?v=UeheTiBJ0Io&vl=en