Neuro-Symbolic AI — Why Symbolic Intelligence Is Still Mandatory
The past five years have felt like a reckoning. Large Language Models have proven more capable than anyone predicted — they translate languages, write code, reason about physics, and pass bar exams. And yet, every major lab investing in AI safety and robustness has come to the same uncomfortable conclusion: LLMs alone are insufficient. Intelligence requires both statistical reasoning and deterministic logic. A note on terminology: the term “artificial intelligence” is itself a misnomer. We still don’t know what intelligence is. Neuroscientists, philosophers, and cognitive scientists disagree on its very nature. What we’re actually building are systems that solve problems. And Feynman was right about flight: we don’t build planes by imitating birds. We build them by understanding aerodynamics. Similarly, we build intelligent systems not by copying human cognition, but by understanding what intelligence fundamentally requires. …