A monthly roundup of news about Artificial Intelligence, Machine Learning and Data Science. 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.
Open Source AI, ML & Data Science News
PyTorch 1.0 has been released with faster performance, better support for distributed computing, a new C++ frontend, and a model-sharing repository.
Tensorflow 2.0 will include a built-in implementation of Keras for deeper integration and support of eager execution.
Industry News
The AI Now Institute has published the AI Now Report 2018, and makes 10 recommendations related to the social impact of AI technology.
Stanford’s AI Index 2018 Annual Report documents the year’s progress in AI teaching, research, and humanlike capabilities.
Tableau adds SSL support for connecting the R server for its R integration feature.
AWS Lambda adds support for Python 3.7, and offers a customization framework for supporting other programming languages.
New features in Amazon SageMaker: semantic segmentation, early stopping for automatic model tuning, and tools for tracking machine learning experiments.
H20.ai’s machine learning platform now available as a hosted service on AWS.
Microsoft News
Microsoft calls for government regulation on the use of facial recognition technology.
The Microsoft Connect event on December 4 included several product announcements related to Machine Learning and AI, summarized below.
Azure Machine Learning service is now generally available. This service orchestrates the training and deployment of machine learning modules, using resources managed on-premises or in Azure. Capabilities include:
Azure Notebooks, the hosted Jupyter Notebooks service, has been updated. New features include:
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A refreshed user interface, with improved project management and notifications.
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Upgrades to the free compute image, and the ability to use paid virtual machine (including GPU-class) instances to provide the compute kernel.
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Streamlined integration with Azure Authentication and Azure Machine Learning service.
ONNX Runtime, a cross-platform, high-performance engine for inferencing with trained ML models in the Open Neural Network Exchange (ONNX) representation, has been released as open source.
ML.NET 0.8, the open-source machine learning framework for .NET, is now available with new recommendation scenarios and a feature importance tool.
The Language Understanding service can now be deployed in a self-hosted container.
The Translator Text API now offers customized translation to support specialized expressions and vocabulary.
Neural Text to Speech, a preview feature of Cognitive Services Speech Service, synthesizes spoken voices indistinguishable from real people.
Azure Functions now supports serverless deployment of Python functions. This blog post provides detailed examples.
Azure SQL Database now provides integration with the R language (in preview).
AzureR: a new suite of packages to manage Azure services with R.
Learning resources
The book Bayesian Methods for Hackers is now available as a series of Jupyter Notebooks with code in Tensorflow.
A tutorial on causal inference in computing systems, presented by Amit Sharma and Emre Kicima at KDD 2018.
A guide to resources and tutorials for getting started with machine learning on Azure.
A tutorial on packaging Cognitive Services APIs into containers and running them on a Docker-enabled platform.
Pattern Recognition and Machine Learning, the 2006 book by Christopher M Bishop, is now available for free download.
A 4-part series on the history and recent advancements in neural word embeddings.
Applications
Using a computer vision model to measure building footprints in satellite images.
Using active learning to track the migration of endangered bird species.
Using deep learning to improve the effectiveness of diabetic retinopathy models.
Using computer vision to quantify fish stocks in Australia.
A collection of reference architectures for deploying machine learning and AI models to real-time applications and batch processes with Azure.
Find previous editions of the monthly AI roundup here.