One reason to avoid such topics is that it is more difficult to make forecasts based on current experiments (which I suppose is a reason to be concerned if things keep on going this way, since by the same token it may be hard to see the end until we are there).
The question I find most interesting about deep learning, and about local search approaches of this flavor more broadly, is the plausibility that they could go all the way with relatively modest theoretical insight. The general consensus seems to be “probably not,” although also I think people will agree that this is basically what has happened over the last few decades in a number of parts of machine learning (deep learning in 2014 doesn’t have too many theoretical insights beyond deep learning in 1999), and appears to be basically what happened in computer game-playing.
This is closely related to my other comment about evolution, though it’s a bit less frightening as a prospect.
A lot of activities in the real world could be re-defined as games with a score.
-If deep learning systems were interfaced and integrated with robots with better object recognition and manipulation systems than we have today, what tasks would they be capable of doing?
-Can deep learning methods be applied to design? One important application would be architecture and interior design.
In order for deep learning to generate a plan for real-world action, first an accurate simulation of the real-world environment is required, is that correct?
One reason to avoid such topics is that it is more difficult to make forecasts based on current experiments (which I suppose is a reason to be concerned if things keep on going this way, since by the same token it may be hard to see the end until we are there).
The question I find most interesting about deep learning, and about local search approaches of this flavor more broadly, is the plausibility that they could go all the way with relatively modest theoretical insight. The general consensus seems to be “probably not,” although also I think people will agree that this is basically what has happened over the last few decades in a number of parts of machine learning (deep learning in 2014 doesn’t have too many theoretical insights beyond deep learning in 1999), and appears to be basically what happened in computer game-playing.
This is closely related to my other comment about evolution, though it’s a bit less frightening as a prospect.
A lot of activities in the real world could be re-defined as games with a score.
-If deep learning systems were interfaced and integrated with robots with better object recognition and manipulation systems than we have today, what tasks would they be capable of doing?
-Can deep learning methods be applied to design? One important application would be architecture and interior design.
In order for deep learning to generate a plan for real-world action, first an accurate simulation of the real-world environment is required, is that correct?