Some folks on the AGI email list have gotten very excited by a video of Demis Hassabis's latest talk about his work with Google Deep Mind, so I thought I'd briefly chip in with my own perspective.
First, regarding the video. It's a well-delivered, clear and concise talk, but so far as I can tell there's nothing big and new there. Demis describes Deep Mind's well-known work on reinforcement learning and video games, and then mentions their (already published) work on Neural Turing Machines... Nothing significant seems to be mentioned beyond what has already been published and publicized previously...
Demis, Shane Legg and many other Deep Mind researchers are known to me to be brilliant people with a true passion for AGI. What they're doing is fantastic! However, currently none of their results look anywhere close to human-level AGI; and the design details that they've disclosed don't come anywhere near to being a comprehensive plan for building an AGI...
Of course, 100 smart guys working together toward pure & applied AGI, with savvy leadership and Google's resources at their disposal, is nothing to be sneered at.... But still, let's not overblow what they've achieved so far....
So far, based on all available evidence, Deep Mind is doing solid R&D aimed at AGI, but they haven't yet done anything that would convince the "open-minded but skeptical researcher" that they are, say, 90% likely to be on the right path. I would say the same about my own OpenCog project: We also haven't yet done anything that would convince the "open-minded but skeptical researcher" that we are 90% likely to be on the right path. For now, there are multiple different approaches to AGI, with various theoretical justifications and limited-scope practical achievements associated with them; and researchers place their confidence in one approach or another based on intuition as much as evidence, since the hard evidence is incomplete and fragmentary.
Personally, I'd rather not see the first AGI owned by a megacorporation, and I'd also rather not see the first AGI be a neural-net trained by reinforcement learning (Deep Mind's preferred approach based on their public materials), since I think
- RL is a very limited paradigm (note some of RL's peculiarities, and also the broader perspective of open-ended intelligence)
- Systems with an explicit probabilistic logic component (like OpenCog) have a far greater chance of being rational (though I admit that rationality is also a limited way of viewing intelligence, it's still something I find important)
My perspective is that with an open source approach properly orchestrated and managed we could get 500-1000 people -- academics, professional developers, hobbyists -- or more actively and aggressively working together, thus far outpacing what even Google Deep Mind can do.... Toward this end, my OpenCog colleagues and I are cooking up a plan to radically grow OpenCog over the next couple years -- beginning with improved documentation and funky demos coming in early 2016. Wish us luck!