Symbolic AI never managed to scale to significant and general real world problems. Neither did Machine Learning, not until the advent of fast processors and mas

Symbolic AI never managed to scale to significant and general real world problems. Neither did Machine Learning, not until the advent of fast processors and massive datasets for training which broke the scale-barrier. Rule-based expert systems (as opposed to SAT, etc) based on Symbolic AI also have the issue that for non-trivial problems, coding the rules themselves usually requires programming expertise in addition to the domain knowledge required to capture the business logic. Things have improved a lot since the 80s, but applications remain fairly niche.