A unified memory stack that functions as a memristor as well as a ferroelectric capacitor is reported, enabling both energy-efficient inference and learning at the edge.
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.
