Brains Minds and Machine Advanced Research Training Course - Project Summary The question of intelligence—how the brain produces intelligent behavior and how to endow machines with human-like capabilities—represents one of the greatest challenges in science and technology. Solving this problem requires a deep understanding of how natural intelligence emerges, with computational rigor sufficient to reproduce similar intelligent behavior in machines. Success in this endeavor will not only enhance our understanding of ourselves but also enable the development of machines with human-like intelligence and potentially even make humans smarter. While today’s AI technologies are impressive, they differ fundamentally from human intelligence. We still lack a clear understanding of the mechanisms underlying the robustness, generalization, and continual learning capabilities of biological intelligence. A synergistic integration of neuroscience, cognitive science, engineering, mathematics, and computer science holds the potential to unlock significant progress. By elucidating how human intelligence works, we can develop more sophisticated and biologically inspired AI algorithms. This in-person course aims to cultivate a community of leaders with a deep understanding of neuroscience, cognitive science, and computer science. These individuals will be well-positioned to advance the scientific understanding of intelligence, contribute to the creation of truly biologically inspired AI, and use this knowledge to build computational tools to address brain disorders. Throughout the course, students will engage in tutorials to gain hands-on experience in these topics. Core presentations will be delivered collaboratively by experts in neuroscience, cognitive science, and computer science. Lectures will be followed by afternoon computational labs and evening research seminars. A central component of the course will be research projects guided by faculty and TAs. Many of these projects may evolve beyond the course, leading to publications in scientific journals.
