In the marketplace for artificial intelligence technology, giant companies like Google, Amazon, and Microsoft offer a powerful, centralized approach: They sell access to platforms for machine learning that hoover up vast amounts of users' personal and proprietary information and use that data to train AI models. A new development called federated learning offers an alternative to the centralized model. It promises to distribute the power of machine learning to mobile phones, IoT devices, and other equipment on the network edge. The payoff: Better performance and enhanced data security. By distributing AI training to the edge, "you speed up the training process significantly, and you get better accuracy," says Marcin Rojek, co‑founder at byteLAKE, a Poland‑based company working on federated learning solutions using Internet of Things (IoT) devices.
Mar-17-2019, 09:26:36 GMT