> it was becoming clear that logic-based AI had hit a wall... Then came machine learning.
In that context, this advance is a sign that there's still momentum going in the current ML paradigm - the hardest board game was at last solved! But as many have pointed out, there's a time in the near future where this approach too will stall short of ambitions. Will this lead to another winter?
For the algorithm ideologues probably yes. The key to current interest was that NN do vision extremely well, which can be built into image search, etc, which can be commercialized. So I think you are right that R&D for self-driving cars will be the sustaining investment in this field for the future, and this will drag AI research towards "animal common sense" as a goal. If they build a hell of safe car and the people buy into it, there could a Cambrian explosion in AI. But its failure or rejection could break the field too.
In that context, this advance is a sign that there's still momentum going in the current ML paradigm - the hardest board game was at last solved! But as many have pointed out, there's a time in the near future where this approach too will stall short of ambitions. Will this lead to another winter?
For the algorithm ideologues probably yes. The key to current interest was that NN do vision extremely well, which can be built into image search, etc, which can be commercialized. So I think you are right that R&D for self-driving cars will be the sustaining investment in this field for the future, and this will drag AI research towards "animal common sense" as a goal. If they build a hell of safe car and the people buy into it, there could a Cambrian explosion in AI. But its failure or rejection could break the field too.