This article discusses the history of AI, the split between neural networks and symbolic AI, and the recent vindication of neurosymbolic AI through the advancements of models like o3 and Grok 4. It argues that combining the strengths of both approaches is crucial for achieving true AI and highlights the resistance to neurosymbolic AI from some leaders in the deep learning field.
“we found no evidence of formal reasoning in language models …. Their behavior is better explained by sophisticated pattern matching—so fragile, in fact, that changing names can alter results by ~10%!”
