Speaker |
Daniel Mannion |
|---|---|
Affiliation |
University College London |
Date |
Friday, 26 May 2023 |
Time |
12:00-13:00 |
Location |
Function Space, UCL Centre for Artificial Intelligence, 1st Floor, 90 High Holborn, London WC1V 6BH |
Link |
https://ucl.zoom.us/j/97245943682 |
Event series |
DeepMind/ELLIS CSML Seminar Series |
Abstract |
Are we missing a crucial component of neural networks? The power consumption of today's machine learning hardware is exponentially increasing, often limiting ML models to cloud platforms. In contrast, the brain can operate at significantly lower power consumptions on the order of 20 W. In this talk, we will explore the role in dendrites within biological neural networks and explore whether these could be key to increasing the computational power of neural networks while maintaining smaller network sizes and lower power consumptions. We will explore the properties of biological dendrites, how these might be used to achieve more power efficient ML hardware and finally outline different approaches to constructing this maybe-missing link. If you're developing ML models which may one day migrate to portable battery-operated devices, then this talk will cover topics that should be of interest. |
Biography |
I am a researcher within the Electronic & Electrical department at UCL. My research aims to build hardware that can implement sophisticated machine learning algorithms at low power consumptions. Much of this research is inspired by nature and biological neural networks. For example, my main focus is on replicating dendritic trees and assessing their impact of neural network performances. I am always on the lookout to apply our hardware to new application domains, so if you are interested in migrating your ML models onto portable hardware then please feel free to contact. |