> limitations you are talking about apply only to deep learning (which is frequently and mistakenly confused for AI nowadays) Deep learning is also where all t

> limitations you are talking about apply only to deep learning (which is frequently and mistakenly confused for AI nowadays) Deep learning is also where all the money and attention is going, and where the revolutionary gains have been seen in the last few years. They’re pretty good at compressing huge datasets into a queriable structure and generating features for hierarchical data, but are just one component of a generalized system that could handle something like war. > By far the biggest problem is to formalize the real world and build a realistic simulation which the AI system can play with Strong agree! The fundamental challenge is to create digital model of the world with enough detail & accuracy that you can run optimizations on it and trust the results. This is as true for robotic aircraft as it is for autonomous cars or an e-commerce data warehouse. People need to decide what subset of the world to observe, deploy & maintain sensors to collect those observations, build information systems to organize & serve the observations, and maintain the whole thing. Then maybe you can start running AI/ML on it.