I know some people doing old-school logic-based AI research. They’re happy because there’s more AI funding in general, and they can present themselves as “what neural networks are missing” or “the next big thing”. Or they come up with projects involving hybrid systems.
Symbolic AI? Pretty sure a combo of that and ML would be needed. Pure ML is too unreliable and have limited coherence, and nobody knows how to program useful symbolic AI from scratch. But if you combine them they can cover each other’s weak spots.
I know some people doing old-school logic-based AI research. They’re happy because there’s more AI funding in general, and they can present themselves as “what neural networks are missing” or “the next big thing”. Or they come up with projects involving hybrid systems.
Symbolic AI? Pretty sure a combo of that and ML would be needed. Pure ML is too unreliable and have limited coherence, and nobody knows how to program useful symbolic AI from scratch. But if you combine them they can cover each other’s weak spots.