IBM this week extended its effort to make artificial intelligence (AI) and machine learning (ML) more accessible, with the release of AutoAI for IBM Watson Studio.
- By Michael Desmond
- 06/19/2019
Companies processing data in real time for AI and machine learning use cases appear to be kicking adoption into high gear, despite concerns about a dearth of developer expertise.
- By John K. Waters
- 06/11/2019
Three months after the alpha version of TensorFlow 2.0 was released, the developers behind the popular Google Brain-created open source machine learning framework have announced that the beta version is now available.
The annual number of AI edge processor shipments (versus sales) is expected to reach 1.5 billion units in the year 2023, according to research publisher IDC.
With artificial intelligence technology impacting nearly every aspect of IT and datacenter operations, a new survey on the software-defined networking (SDN) movement reaffirms AI's influence on new-age networking.
Nvidia EGX has been architected to provide as much low-latency performance as possible, the company said, offering "real-time" "continuous streaming" ability.
The breakthrough could lead to the faster operations and lower power that technologies like artificial intelligence, edge and quantum computing will require in the coming years.
AI2GO is a new "self-serve" platform designed to make it it easy for developers without an AI background to build smart edge-based products for Internet of Things (IoT) solutions and other uses.
Facebook has announced a number of new features and better interop for its increasingly popular open source "Python-first" deep learning tool PyTorch.
Google's Firebase team announced updates to its ML Kit, providing machine learning functionality for Android and iOS mobile apps, during the Google I/O 2019 conference.
At Build 2019 this week, Microsoft introduced support for a Spark API that will enable Cosmos DB to support hybrid transaction and analytic processing workloads (HTAP).
- By Joey D'Antoni
- 05/08/2019
on Thursday Microsoft announced a number of improvements coming to Azure that make it easier for developers without an AI background to build AI solutions and machine learning models.
The upcoming Qualcomm Cloud AI 100 is designed to improve inference performance (as opposed to training) of AI projects while also making use of power more efficiently than other solutions.