This episode discusses the challenges of creating truly intelligent machines. The
author explores past and present attempts to imbue AI with commonsense reasoning,
focusing on projects like Cyc, which aimed to manually encode human
knowledge. The text also examines the difficulties of programming abstraction and analogy-making abilities
into AI, using Bongard problems as a compelling example of human
capabilities that remain elusive to machines. Finally, the author
considers the limitations of current deep learning approaches and argues
for the importance of embodiment in achieving
human-level AI. The author's own research on analogy-making programs
and their application to visual scene recognition is described.
