[ethbro]

The author's general problem is that he seems ignorant (or willfully ommiting) the expert systems period in AI (realized and popular in the 80s, academic foundations discovered in the 60s and 70s).

I agree with the article that GP AI is likely to ultimately be a fusion of bottom-up with top-down systems, and that expert systems seem to be getting short shift after their earlier failures while neural networks are possibly receiving overly optimistic expections.

To be fair, I believe this is the author: https://en.m.wikipedia.org/wiki/Gary_Marcus , and he appears to have a cognitive neuroscience background as opposed to computational AI. So I wouldn't be surprised if he actually was unaware of 1960s-80s CS AI research.

[candiodari]

Examples of top-down algorithms, in my opinion (since bottom-up and top-down are debatable concepts in many concrete situations), include:

- Genetic algorithms

- Q learning

In the sense that they learn general behavior first and then learn ever more little "tricks" to be used in particular situations. Both are more effective when combined with ANNs. But when they start they're only aware of very high level goals.

That said, I also have kids, and while they're bigger now, I would argue the idea that humans work top-down from the very beginning doesn't survive caring for a toddler for a few hours (babies can't really move, so they don't make particularly stupid decisions. Toddlers and up to teenagers make idiotic decisions that make sense from particular perspectives. For instance, they exhibit extreme short term decision making (like taking a huge risk of falling down just to get a little piece of candy).

Top-down decision making isn't just something that is eventual emergent behavior, it's learned behavior. Telling a toddler that to get candy he should go to the store, get flour, sugar and ... and follow this recipe doesn't work. They get distracted after 30 seconds. It's not that they're trying to fail, their mind just doesn't let them focus beyond a certain (short) amount of time. Adults have the same limit, just longer time, but they have learned to compensate for it. For instance using TODO lists, or project plans.

[ethbro]

I've always had the suspicion that memoization (or lack thereof) is the primary reason really young children do and think a lot of the ways they do.

As adults, it seems like we don't actually experience every sensation of the world anymore. Most of the time it's already high level categorized (e.g. "apple") by the time it hits our conscious mind.

[candiodari]

I agree, it's obvious that human intelligence is >99.9% a behavior copying algorithm. What we call rational thought is in reality restricted to conscious exercise and it is a learned skill. A trick, nothing more, and especially not a core part of our behavior. It is not that different, at a low level, from learning to juggle balls. Rational behavior, firstly, most people just don't have it at all, and secondly even in the people who do behave rationally occasionally, it is only when things are happening slowly enough and they're putting in constant effort toward maintaining that rational behavior, constantly second-guessing themselves and going back in memory every few minutes to evaluate your own actions and formulate a plan.

And if you've been to the third world (or just a large poor part of a large western city), you'll know this is true: billions of people have never learned to act rationally, and only few and far between will ever act rationally. You can do a thought exercise with these people and figure out with them what the rational action is, and the vast majority will simply act anyway.