In many ways, what we're seeing is a modern-day rehash of the "symbolic" versus "connectionist" approaches to AI, with critics like Marcus on the "symbolic" camp ("we need more understanding!") and engineers and scientists who build AI systems, like Sutton, on the "connectionist" camp ("we need more computation!").
There are also AI researchers seeking to bridge the two approaches. Here's a recent example that seems significant to me: https://news.ycombinator.com/item?id=34108047 . Maybe we will eventually find that the "symbolic" and "connectionist" approaches are actually not different, as people like Minsky contended?
I read the interview expecting exactly what you describe. Instead I found a nuanced and illuminating discussion —- at least for a non-expert such as myself. Marcus references the symbolic vs connectionist debate and (at least by his own description) seems to be what you call a “bridger” of long standing.
His objections seem concrete and well supported — not just repeating “but does it really understand” over and over. (Admittedly there is some of this.)
The connectionist approach is disturbing to me when taken to its logical extreme, which for me is essentially a variation of the paperclip maximizer only the target is "consume as many resources as necessary to build the best approximation of human like intelligence."
> with critics like Marcus on the "symbolic" camp ("we need more understanding!") and engineers and scientists who build AI systems, like Sutton, on the "connectionist" camp ("we need more computation!").
> There are also AI researchers seeking to bridge the two approaches.
I don't know if he does it with his work in practice, but throughout the interview Marcus says he wants to bridge the approaches. I think he references a really old talk or article from himself calling for that too.
For all the screaming of the symbolic researchers we have yet to see much from their approaches. All the recent very impressive advances in AI have been connectionist approaches.
Also a lot of the things that symbolic researchers have been claiming connectionism can’t achieve turned out to be emergent properties of connectionist approaches
Yes, I agree! I mean, it sure seems as if critics from the "symbolic" camp keep moving the goal posts, doesn't it?
The "constant moving of goal posts" is one of the reasons why I think the two sides may converge: Engineers and scientists on the "connectionist" side could very well find ways to build AI systems that rely on "dumb" computation at massive scales to reason about symbols representing entities in the external world, simultaneously silencing and satisfying the critics -- who, as always and as ever, will say they were right all along.
In many ways, what we're seeing is a modern-day rehash of the "symbolic" versus "connectionist" approaches to AI, with critics like Marcus on the "symbolic" camp ("we need more understanding!") and engineers and scientists who build AI systems, like Sutton, on the "connectionist" camp ("we need more computation!").
There are also AI researchers seeking to bridge the two approaches. Here's a recent example that seems significant to me: https://news.ycombinator.com/item?id=34108047 . Maybe we will eventually find that the "symbolic" and "connectionist" approaches are actually not different, as people like Minsky contended?