Learning with Brain-Computer Interfaces – Prof. Aaron P. Batista

Learning with Brain-Computer Interfaces - Prof. Aaron P. Batista
Fast and Slow Learning with Brain-Computer Interfaces
Aaron P. Batista, University of Pittsburgh

When we learn, the brain changes at nearly every level of organization. Synapses form and strengthen, individual neurons change their tuning properties, and cortical maps expand. My research examines how learning alters the coordinated activity of populations of neurons. This is a particularly important level at which to study learning because it is the action of populations of neurons that drive behavior, generate perceptions, and undergird our cognition.

February 2018
[Read More …]

Powered by WPeMatico

The Power of Artificial Intelligence – US Congressional Hearing, June 26th, 2018

The Power of Artificial Intelligence - US Congressional Hearing, June 26th, 2018
Subcommittee on Research and Technology and Subcommittee on Energy Hearing – Artificial Intelligence – June 26th, 2018

Dr. Tim Persons, chief scientist, GAO

Mr. Greg Brockman, co-founder and chief technology officer, OpenAI

Dr. Fei-Fei Li, chairperson of the board and co-founder, AI4ALL

OpenAI was founded by Elon Musk and Sam Altman
[Read More …]

Powered by WPeMatico

The State of Brain-Machine Interfaces – Prof. Maryam Shanechi

The State of Brain-Machine Interfaces - Prof. Maryam Shanechi
Maryam Shanechi, University of Southern California

With recent technological advances, we can now record neural activity from the brain, and manipulate this activity with electrical or optogenetic stimulation in real time. These capabilities have brought the concept of brain-machine interfaces (BMI) closer to clinical viability than ever before. BMIs are systems that monitor and interact with the brain to restore lost function, treat neurological disorders, or enhance human performance.

February 2018
[Read More …]

Powered by WPeMatico

Quantum Computing – Sergey Frolov, University of Pittsburgh

Quantum Computing - Sergey Frolov, University of Pittsburgh
Majorana fermions are real solutions to the Dirac equation, meaning they are their own antiparticles. For 80 years they have been and continue to be searched for among elementary particles, with some people believing neutrinos to be Majorana fermions. In the context of this talk, Majorana particles are quasiparticles made of millions of electrons in a crystal in a quantum superpositon. We study these quasiparticles for their fundamental importance, which is directly linked to their potential for quantum computers.

June 2017
[Read More …]

Powered by WPeMatico