Earlier quoted context omitted.
We don't even have good generalized robot manipulation. Think of that as monkey-level AI. After half a century of hard work, robot manipulation in unstructured situations still sucks. Go watch DARPA Humanoid Challenge videos or old Willow Robotics towel-folding to see how badly it sucks. Factory robotics works because the work situation is highly structured. On the other hand, once someone cracks that, a huge number…
That's exactly what is about to happen. Deep learning has the potential to do robot control. Currently researchers are beating tons of video games using reinforcement learning with deep networks. Applying the same methods to robots shouldn't be too hard. And we've also come a long way with machine vision as well over the past 5 years.
Deep learning is still mere perception. It doesn't handle memory or processing, it just transforms input into output, typically trained by Big Data, way bigger than necessary statistically speaking, given the world we live in.
AGI requires super aggressive unsupervised learning in recurrent networks, likely with specialized subsystems for episodic and procedural memory, as well as systems that condense knowledge down to layers of the network that are closer to the inputs. At a minimum. And nobody is really working on any of that yet (or at least succeeding) because it's really damn hard.
That's why everyone in "AI" is rebranding as a deep learning expert, even though deep learning is really just 1980s algos on 2016 hardware - you gotta sex up feed forward backprop or you don't get paid.
Edit: to be fair, robot control is much simpler than AGI, and might be mostly solved with deep learning somewhat soon, I forgot the context of your post.