- August 27, 2019
The Chinese technology vendor Huawei aims to speed up AI training times with the launch of a new processor in China and a new AI computing framework.
- August 15, 2019
As enterprises rely more on conversational agents to power customer service efforts, tech vendors such as IBM and Google steadily develop new methods of training language models.
- May 07, 2019
For the first time, Google Cloud TPU Pods are available in public beta, enabling machine learning developers and engineers to more quickly deploy and train models.
- May 02, 2019
Databricks user ShopRunner talks about the tools showed at Spark + AI Summit 2019, such as MLflow and Databricks Delta Lake. And Datameer reveals new Databricks integration.
- April 10, 2019
Google's newly unveiled AI Platform offers AI developers a collaborative environment to test, train and deploy machine learning and deep learning models.
- April 08, 2019
IBM has delivered a low-cost workstation tuned to work hand in hand with its Power AC922 server to lower the bar of entry for AI application development.
- March 06, 2019
Google AI, the AI research and development team at Google, made GPipe a framework for building large-scale and accurate deep neural networks open source.
- January 11, 2019
Adding to the Intel Nervana chip line, Intel and Facebook are expected to launch in the second half of 2019 a new processor designed to speed up inference.
- July 31, 2017
Think before you act on artificial intelligence technologies to ensure that your efforts to become a "cognitive business" lead you in the right direction.
- March 10, 2015
Machine learning techniques are far from new. What is new, however, is the number of parallelized data processing platforms available for applications of big data.