Hi! I am Hutapea Abiarsi Koessaktya Fransisca,
A Professional Experience and Expert Person.
This service explores the problem of intelligence—its nature, how it is produced by the brain and how it could be replicated in machines—using an approach that integrates cognitive science, which workers the mind; neuroscience, which workers the brain; and computer science and artificial intelligence, which work the computations needed to develop intelligent machines. Materials are drawn from the Brains, Minds and Machines Summer Course offered annually at the Marine Biological Laboratory in Woods Hole, MA, taught by faculty affiliated with the Center for Brains, Minds and Machines headquartered at MIT. Elements of the summer course are integrated into the MIT course, 9.523 Aspects of a Computational Theory of Intelligence.
This service includes the contributions of many investors, consultants, and a team of iCub application. See the complete list of contributors.
This service introduces you to the scientific work of intelligence in brains and machines. Through guideline by leading example in the field, you can about the benefit foundations and computational methods used in intelligence application; empirical methods used in neuroscience and cognitive science to probe the function of neural circuits and emergent behavior; the kinds of questions that can be addressed with computational and empirical methods and how the integration of multiple perspectives can accelerate the pace of intelligence application. This foundation is enriched through the exploration of current application on a range of topics including visual recognition, audition and speech, natural language understanding, robotics and motor control, cognitive development, social cognition, machine learning and Bayesian inference, and visual and spatial memory. These topics are organized into curricular units that are somewhat independent, allowing flexibility in the order and extent to which the topics are work. Resources are also provided to support hands-on computer activities to work methods of modeling and data analysis in greater depth.
The materials in this open-licensed OCW resource come from the 2015 version of the Brains, Minds and Machines Summer Work. Additional materials, including from later years, are at the Brains, Minds and Machines Summer Course website.
The field of Artificial Intelligence has produced impressive machines, such as Deep Blue, Watson, and Siri, that can beat a world chess champion, win the game of Jeopardy, and communicate in natural language. Yet few would view their behavior as brain-like or human intelligence. Computers still fare poorly on tasks that even young infants can perform, such as answering simple questions about a visual scene, Who is there? What are they doing? What happened previously? What will happen next? In this short introduction, Tomaso Poggio talks about how the synergy of recent advances in neuroscience, cognitive science, and AI, will enable us to understand the processes underlying human intelligence, from the neural circuits of the brain to the level of cognitive behavior.
David Rolnick & Ishita Dasgupta: Modeling Dynamic Memory with Hopfield Networks.