It seems everyone took my comment to hint that Minsky was wrong. I did not mean to indicate that. I wanted to know who was still doing non-ML intelligent machine stuff, since ML is all I ever hear about in HN.
HN is an echo chamber when it comes to certain topics. IJCAI, AI magazine, AGI conferences etc would be the best place to look at scientific cutting edging work on intelligent machines that includes non-ML work. The research reported in these places is not always flashy like what the HN crowd loves, but represents unsolved problems being solved in a variety of ways.
The Berkley course on AI on EdX is also a good option to understand what is happening in the field. A lot of $$ goes into non ML stuff. Don't get me wrong ML is important, but right now, is not the only game in town. Would be nice to have pure learning machines, but we are quite far from that (despite all the hype and genuine exciting developments in recent years).
> HN is an echo chamber when it comes to certain topics.
There's a way to change that: educate the community by submitting meaningful stories on new topics. Those are the best submissions and we're always on the lookout for them.
In the field of machine translation, I'd say GF/MOLTO ( http://grammaticalframework.org/ ) is pretty cutting-edge non-ML AI (though the definition of what's AI keeps changing, I don't know if people would call this stuff part of AI any longer?).
Funny, GF is what made me reconsider my views! Amazing that a small team of non-ML academics outside the US can beat an army of ML researchers in companies like Google, MSFT etc.
http://ijcai-15.org
Also, even in things like question-answering, pure ML is not the state-of-the-art. E.g., IBM Watson had a bunch of different algorithms.
http://ieeexplore.ieee.org/xpl/tocresult.jsp?reload=true&isn...
We will eventually get there with a pure learning system, but not yet. Till then, we need less FUD. :)