Neuromorphic computing in Artificial Intelligent Systems
Title: Neuromorphic computing in Artificial Intelligent Systems
Abstract:
Neuromorphic computing emulates the structure and dynamics of biological neuronal networks in mathematical models and in hardware. Neuromorphic hardware has been shown to surpass conventional CPU and GPU by several orders of magnitude in many AI tasks. Applications of neuromorphic technology range from smart sensing to adaptive movement control, solving constrained optimization problems, and simultaneous localization and mapping. In this talk, I will explain the place of this field in the overall AI landscape, show examples of the state of the art work, and picture our vision for its future applications.
Bio:
Dr. Yulia Sandamirskaya leads the Applications Research team of the Neuromorphic Computing Lab at Intel. Her team develops spiking neuronal network based algorithms for neuromorphic hardware to demonstrate the potential of neuromorphic computing in real-world applications. Before joining Intel, Yulia led a group “Neuromorphic Cognitive Robots” in the Institute of Neuroinformatics at the University of Zurich and ETH Zurich. She was chairing EUCog—the European Society for Artificial Cognitive Systems and coordinated an EU project NEUROTECH, creating and supporting the neuromorphic computing technology community in Europe.
Date and Time
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- Date: 27 Jul 2021
- Time: 11:20 AM to 12:00 PM
- All times are (GMT+10:00) Australia/Queensland
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- Co-sponsored by QUT Centre for Robotics
Speakers
Dr. Yulia Sandamirskaya of Intel, Neuromorphic Computing Lab, Munich
Neuromorphic computing in Artificial Intelligent Systems
Abstract:
Neuromorphic computing emulates the structure and dynamics of biological neuronal networks in mathematical models and in hardware. Neuromorphic hardware has been shown to surpass conventional CPU and GPU by several orders of magnitude in many AI tasks. Applications of neuromorphic technology range from smart sensing to adaptive movement control, solving constrained optimization problems, and simultaneous localization and mapping. In this talk, I will explain the place of this field in the overall AI landscape, show examples of the state of the art work, and picture our vision for its future applications.
Biography:
Dr. Yulia Sandamirskaya leads the Applications Research team of the Neuromorphic Computing Lab at Intel. Her team develops spiking neuronal network based algorithms for neuromorphic hardware to demonstrate the potential of neuromorphic computing in real-world applications. Before joining Intel, Yulia led a group “Neuromorphic Cognitive Robots” in the Institute of Neuroinformatics at the University of Zurich and ETH Zurich. She was chairing EUCog—the European Society for Artificial Cognitive Systems and coordinated an EU project NEUROTECH, creating and supporting the neuromorphic computing technology community in Europe.