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.

This is an eclectic collection of interesting blog posts, software announcements and data applications I've noted over the past month or so. ONNX Model Zoo is now available, providing a library of pre-trained state-of-the-art models in deep learning in the ONNX format. In the 2018 IEEE Spectrum Top Programming Language rankings, Python takes the top spot and R ranks #7. Julia 1.0 has been released, marking the stabilization of the scientific computing language and promising forwards compatibility. Google announces Cloud AutoML, a beta service to train vision, text categorization, or language translation models from provided data.

Materials for five new AI-oriented courses have been published to the LearnAI Materials site.

How to Develop a Currency Detection Model using Azure Machine Learning, with details on how the real-time banknote recognition capability of the Seeing AI application was implemented in CoreML.

Using deep learning to generate music: Part 1 and Part 2 on The AI Show on Channel 9.