In the war for artificial intelligence cloud dominance with the likes of Amazon AI and Google AI, Microsoft's Azure AI team today fired off a salvo that boosts its Cognitive Services offering.
Catherine Havasi, a visiting scientist at MIT and group director at the Media Lab focused on natural language processing and people analytics, is on a mission to help computers understand the world more like a person and less like a machine.
- By John K. Waters
- 03/20/2019
Microsoft updated its open source machine learning framework, ML.NET, to version 0.11 and offered up an engineer to help developers make it work in a production environment.
Coming hot on the heels of the much anticipated TensorFlow 2.0 alpha release, TensorFlow Privacy is an open source library designed to make it easier for developers to train machine-learning models with privacy.
- By John K. Waters
- 03/13/2019
New features in version 0.16 include support for Spark's deep learning pipelines and name entry recognition cognitive service.
Enterprise artificial intelligence (AI) platform vendor Dataiku announced this week that it has updated its namesake platform to version 5.1.
Today the alpha 2.0 version of the popular open source machine learning platform TensorFlow was released on Github.
This week Google announced that it has open-sourced GPipe, a library that can be used to train deep neural networks (DNNs) used in large-scale machine learning projects
Visual Studio Code, the open source, cross-platform code editor from Microsoft that some developers prefer for creating artificial intelligence projects, is itself leveraging AI to make their coding lives easier.
IBM's cloud-based Watson artificial intelligence service is now a portable offering untethered from IBM Cloud, so enterprises can use it on any cloud platform.
CogitAI Inc. wants to improve artificial intelligence enterprise initiatives by removing the human element of manually labeling data for training machine learning algorithms.
Transportation network company Uber has open sourced a homegrown, no-code toolbox for working with deep learning models.
A new open source project from the Amazon cloud platform, Amazon Web Services, optimizes machine learning models to run better in the cloud and on resource-constrained network edge devices.