FEDERATED LEARNING
Obsolete already?
Federated learning is a promising solution to distributed model training. But, the approach comes with a few key challenges such as high computational resource requirements, coordination burden among counter-parties, risk of reverse engineering training data, and low IP protection for models. Contemporary solutions like TripleBlind provide superior protection for data in-use. Download our whitepaper to learn how our technology solves for these challenges and more.