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.
Google has added Natural Language Processing and other functionality to ML Kit, an SDK that provides the company's machine learning expertise and technology for mobile development.
Nvidia recently released Issac SDK, a new software development kit designed to make it easier to add artificial intelligence (AI) and machine learning capabilities to consumer and industrial robotics projects.
In announcing the Spring '19 release of its low-code/no-code software development tooling, Mendix touted the second generation of its artificial intelligence engine to help with code completion suggestions and other AI assistance.
Microsoft's open source, cross-platform ML.NET machine learning framework is now one step away from general availability, which could come as soon as next month following the newly available Release Candidate.
In announcing an update to its open source F# functional programming language, Microsoft indicated future releases will better support machine learning projects.
According to job site Indeed.com, "machine learning engineer" is the best job of 2019, with a growth of 344 percent over the last year and an average base salary of $146,085.
Google-owned DeepMind today released a "large-scale extendable dataset of mathematical questions for training neural models that can reason algebraically."
They feature Intel Deep Learning Boost, designed to support artificial intelligence (AI) and machine learning workloads, and offer "significant" processing speed boosts on the embedded level.
The Amazon cloud, hearing that customers wanted to simplify the complicated and time-consuming process of manually using Amazon Web Services to deploy TensorFlow workloads, announced a new managed service to do just that, and more.