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 I’ve noted over the past month or so.
Open Source AI, ML & Data Science News
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.
A retrospective on the R Project, now in its 25th year, from Significance Magazine.
Google announces Cloud AutoML, a beta service to train vision, text categorization, or language translation models from provided data. The fast.ai blog evaluates the claim that AutoML works without the need for machine learning skills.
Google announces Edge TPU, a hardware chip and associated software to bring AI capabilities to edge devices.
Oracle open-sources GraphPipe, a network protocol designed to simplify and standardize transmission of machine learning data between remote processes.
AWS Deep Learning AMIs now include ONNX, making it easier to deploy exported deep learning models.
Amazon Rekognition is available in two new regions: Seoul and Mumbai. The video analysis service caused a stir when the ACLU reported it matching pictures of members of Congress to a database of criminal mugshots.
RStudio introduces Package Manager, a repository management server product to organize and centralize R packages.
Data from the O’Reilly Machine Learning Adoption Survey reveal that most machine learning models are built by in-house data science or product development teams, with only 3% adopting cloud-based ML service.
Anaconda Enterprise 5.2 adds capabilities for GPU-accelerated machine learning.
TechNative’s review of Microsoft’s AI philosophy and technologies, and the roadmap ahead.
Power BI Desktop now offers Python integration (in preview).
AI for Accessibility, a $25M Microsoft program applying artificial intelligence to help people with disabilities.
The Chartmaker Directory, an index of dozens of data visualization types with examples in more than 30 software tools.
An overview of the benefits and limitations of FPGUs compared to CPUs and GPUs for numeric computing.
A guide to deep learning applied to natural language processing, for those new to the field.
Containerized R and Python Web services with Docker and Microsoft ML Server.
Design, architecture, and implementation of an R-based recommendation system in Azure.
A guide to distributed deep learning in Spark, using Azure Batch and Azure HDInsight.
Google’s Machine Learning Guides, with machine learning tips and a guide to text classification.
Field Guide to Machine Learning, a 6-part video series from Facebook Research.
What Data Scientists Really Do, according to a Harvard Business Review article.
Survey analytics company Crunch uses R to provide a data visualization service.
Finding optimal staff composition for a professional services company, with Azure Machine Learning.
Find previous editions of the monthly AI roundup here