Neural Taskonomy and Historical Perspectives in Visual Intelligence

This lecture discusses the importance of establishing a two-way connection between natural and artificial intelligence, emphasizing the concept of Neural Taskonomy, which infers task-derived representations from brain activity. The instructor presents a historical overview of neural networks, starting from the Perceptron model introduced by Rosenblatt in 1958, and explores the evolution of computer power in relation to brain power. The lecture highlights significant milestones in computer vision, including foundational work from the 1960s to the 2010s, and the development of various models and theories in the field. The instructor also addresses the relevance of neuroscience in understanding visual intelligence and the importance of interdisciplinary approaches in advancing the field. The course aims to inspire students to engage with real-world applications and encourages creative project work that bridges theoretical knowledge with practical implementation.