If you are interested to hear more about the advancements of Artificial Intelligence in Bioscience, join Special Interest Group on Artificial Intelligence in Biomedicine http://benevolent.ai/blog/benevolentai/join-the-special-interest-group-on-artificial-intelligence-in-biomedicine/
Dr Caswell Barry, Principal Research Associate, UCL Cell & Development Biology joined the Artificial Intelligence in Bioscience Symposium 2017.
Abtract: The last five years have seen huge gains in the capability of machine learning, particularly deep learning and deep reinforcement learning, approaches that have been shaped by our understanding of the mammalian brain. Indeed, there has been considerable dialogue regarding the extent to which these fields should continue to be influenced by neuroscience. However, there has been far less information flow in the opposite direction; while the machine learning field has been effective at absorbing lessons from neuroscientists, the potential for machine learning to inform our understanding of the brain is only now starting to be explored. By presenting preliminary work from my own lab as well as work conducted in other labs, I will make the case that machine learning provides a new way to understand how information is processed and transformed in the brain. In short, not only do machine learning techniques provide a powerful set of tools for dealing with large neural datasets, they also provide a way of building and testing models of the brain.
