Electroengineering / Microtechnics
Extremely energy-efficient artificial intelligence is now closer to reality after a study by UCL researchers found a way to improve the accuracy of a brain-inspired computing system. The system, which uses memristors to create artificial neural networks, is at least 1,000 times more energy efficient than conventional transistor-based AI hardware, but has until now been more prone to error.
A new technique that synchronises the clocks of computers in under a billionth of a second can eliminate one of the hurdles for the deployment of all-optical networks, potentially leading to more efficient data centres, according to a new study led by UCL and Microsoft.
Last job offers
- Computer Science - 6.1
Researcher in Deep learning and optimisation for extreme-scale computational imaging