So things like having systems that are that are interpretable, having systems that can work with different kinds of data that can integrate knowledge from other sources, that’s sort of the domain of Broad AI.
Would you say like that a narrow (AI) gets a little better then a little better, a little better, a little better, a little better, then, ta-da!
When we think about Broad AI, we really are thinking about a little bit ‘press the reset button, don’t throw away things that work.’ Deep learning is a set of tools which is tremendously powerful, and we’d be kind of foolish to throw them away.
Some of the work we’re doing now is building systems where we use neural networks to extract structure from these noisy, messy inputs of vision and different modalities but then actually having symbolic AI systems.