Australian Laureate Fellowships - Grant ID: FL210100045
Funder
Australian Research Council
Funding Amount
$3,245,263.00
Summary
Energy-efficient artificial intelligence using quantum technologies. Artificial intelligence (AI) is transforming society but standard technologies come with significant hidden costs: training even a single, common, learning model can emit 5 times more carbon dioxide than the lifetime emissions of the average car. This Fellowship aims to develop artificial intelligence platforms using Australia’s significant investment in quantum technologies to bypass traditional approaches to AI. The expected ....Energy-efficient artificial intelligence using quantum technologies. Artificial intelligence (AI) is transforming society but standard technologies come with significant hidden costs: training even a single, common, learning model can emit 5 times more carbon dioxide than the lifetime emissions of the average car. This Fellowship aims to develop artificial intelligence platforms using Australia’s significant investment in quantum technologies to bypass traditional approaches to AI. The expected outcomes are neuromorphic computers that operate efficiently—with low-energy cost—and rapidly—achieving speeds impossible with conventional electronic approaches. The anticipated benefits are transformative technologies for AI, new applications across society, and new tools for exploring brain function and cognition.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100149
Funder
Australian Research Council
Funding Amount
$3,280,000.00
Summary
Autonomous learning for decision making in complex situations. The project aims to create a novel research direction – autonomous machine learning for data-driven decision-making – that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively h ....Autonomous learning for decision making in complex situations. The project aims to create a novel research direction – autonomous machine learning for data-driven decision-making – that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively handle tremendous uncertainties in data, learning processes and decision outputs, particularly enabling smart learning in massive domains, massive streams, and massive-agent sequentially changing environments. The project’s outcomes are expected to improve data-driven decision-making in multiple industry sectors.Read moreRead less