Artificial Intelligence, a field of computer science aimed at building machines that can learn and reason like humans, has known tremendous accelerations recently thanks to advances in computing power and the availability of massive amounts of data.
The development of Machine Learning with Neural Networks is opening up vast opportunities.
However, such training frameworks have been struggling with a trilemma:
How can system robustness, data privacy, and learning scalability be ensured all at the same time?
This demonstrator presents the recent evolutionary steps in AI and the advancements developed by CEA List’s team in the field of decentralized machine learning to solve this trilemma.