IIT-M’s winter course on machine intelligence begins

S Vishnu Sharmaa, INN/Chennai, @Svs037

The winter course on Machine Intelligence and Brain Research of Center for Computational Brain Research (CCBR) at Indian Institute of Technology, Madras (IIT-M) premises began recently.

Sources say, course is designed to provide to students and researchers an interactive perspective on intelligence and brains in general from a neuroscience and engineering perspective

The course is being held from 2 to 10 January on IIT-M campus. The course received over 400 registrations with course credits being offered to 50 IIT Madras students.

This year’s workshop comprises fundamental and research lectures from distinguished speakers from all over world as well as hands-on tutorials on fundamentals of neuroanatomy, machine learning and data analysis on brain signals.

Director of IIT-M Professor Bhaskar Ramamurthi said they are hoping to see a large amount of global collaboration in the CCBR, which is already working with researchers across the world.

This is the fifth edition of the annual workshop with students benefitting tremendously as they gain exposure to the latest advances in Computational Brain Research and the intersection between biotechnology, machine learning and brain research, he said.

Kris Gopalakrishnan, Chairman, Axilor Ventures and  Co-Founder, Infosys said they have chosen to take up brain research at CCBR as it is one of the fast growing fields and one of the few remaining unknowns in Science.

The Artificial Intelligence, Machine Learning wave will increase processing power, increase storage capacity on the cloud, increase availability of data and impact every industry and aspect of life, he said.

Professor Partha Mitra, Crick, Clay Professor of Biomathematics at Cold Spring Harbor Laboratory and H.N. Mahabala Chair Professor, CCBR, IIT Madras said technology in the 21st century will be made by engineering and brain research and the MIBR (Machine Intelligence and Brain Research) Course is all about that.

The course has modules on vision, audition, speech, language and reinforcement learning, he said. Modern Machine Learning is training-data hungry, requires orders of magnitude, more training data than biological brains.

Biological brains have species-specific, adaptively evolved prior structure, encoded in the species genome and reflected in the mesoscale brain connectivity, he added.

The center’s activities focus on three distinct areas namely the circuitry of the brain, the functions of the brain and brain inspired computing. Some of the goals that the center is working towards include understanding the basic principles of organization of the brain across species, understanding the fundamental functions of brain networks.