Strand 5: Brain-inspired Machine learning and Artificial Intelligence Algorithms and Applications

Researchers: Eric Robson, Jerry Horgan, Kevin Doolin

Artificial intelligence (AI) is the development of intelligent machines and systems that mimicking the human brain. Over the years, numerous research initiatives have led to sophisticated AI algorithms that are capable of performing tasks to the level of humans. This TBI research strands aims to develop AI and machine learning algorithms that mimic the human brain, incorporating communication and connectivity of neuronal networks, all the way to cognition processes at the brain level. Since AI algorithms are far from the capabilities of the human brain, especially in terms of resources and energy consumption of computing systems, these algorithms will be deployed over Hyper Scale Systems (HSS). HSS will be used to provide a dynamic software layer that will seamlessly interact with all the associated hardware elements of TBI. It is specifically designed to provide the large-scale, plasticity, and low-latency (high-speed) processing and storage (cognitive) resources that are required to augment (or emulate) brain functions. HSS will be used to hide or abstract the high level of system complexity that is created by dense interconnectedness at scale.

Research Objectives:

  • Development of neuronal network simulation models that can represent AI algorithms that also incorporates learning functions.
  • Development of AI platforms that can be executed on Hyper Scale System, providing remote intelligence to external devices, systems, as well as supporting new applications for Brain Machine Interfaces.