Walid Saba

In this engaging discussion, guests Walid Saba, Gadi Singer, and J. Mark Bishop explore the future of AI beyond deep learning. Saba critiques the limitations of current statistical methods in conversational agents, while Singer emphasizes the need for hybrid models that blend reasoning with data. Bishop dives into the philosophical boundaries of computational cognition, challenging the notion that AI can replicate human understanding. Together, they advocate for a cognitive approach to align AI closer to human values and reasoning.

Dr. Walid Saba, a knowledgeable AI expert and computational linguist, shares his contrarian views on the potential of machines to rule the world. He critiques the limitations of strong AI while acknowledging the impressive achievements of large language models in understanding language. Their discussion covers the challenges of semantics and symbol grounding, highlighting that current models struggle with true comprehension. Saba argues that deep learning demonstrates language competency beyond human replication, emphasizing the ongoing quest for advancing AI capabilities.

Dr. Walid Saba, a Senior Scientist at Sorcero, critiques deep learning's approach to natural language understanding. He argues that reliance on statistical learning leads to failure, akin to memorizing infinity. Saba emphasizes the importance of symbolic logic and human cognitive processes in AI development. He explores the complexities of memory in neural networks, the distinctions between top-down and bottom-up problem-solving, and the need for hybrid models that integrate logic and prior knowledge. His insights challenge conventional methods and advocate for a deeper understanding of cognition in AI.