Another limit of federated machine learning is data labeling. Most machine learning models are supervised, which means they require training examples that are manually labeled by human annotators.

Use of federated learning, for example, led to a 50x decrease in the number of rounds of communication necessary to get a reasonably accurate CIFAR convolutional neural net for computer vision.

Machine Learning In Video Games There’s a good reason the below machine learning demo has over three million views on YouTube – it’s a brilliant example of how this technology learns and ...

Machine learning, for all its benevolent potential to detect cancers and create collision-proof self-driving cars, also threatens to upend our notions of what's visible and hidden.

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...