AI, Machine Learning and Data Science Roundup: March 2019

This is an eclectic collection of interesting blog posts, software announcements and data applications from Microsoft and elsewhere that I've noted over the past month or so. TensorFlow Privacy: a Python library for training machine learning models with differential privacy, for use with sensitive data to generate models that don't learn details about specific people. Tensorflow Federated, an open-source library for Federated Learning, enabling many participating clients to train shared ML models while keeping their data local. Open AI has published a paper describing GPT-2, an unsupervised language model that can generate paragraphs of coherent text that could be mistaken for human writing. Only a scaled-down version has been released, for fear of abuse.