Oracle announces that Oracle MySQL HeatWave now supports in-database machine learning, in addition to transaction processing and analytics.

Qeexo announces that its Qeexo AutoML platform now supports machine learning on Arm Cortex -M0 and Cortex -M0 processors, which power devices including sensors and microcontrollers from companies such as Arduino, Renesas, STMicroelectronics, and Bosch Sensortec. The Arm Cortex-M0 processor is the smallest Arm processor available, and the Cortex-M0 processor builds on Cortex-M0 while further reducing energy consumption and increasing performance. Qeexo is the first company to automate adding machine learning to a processor of this size. The Cortex-M0 and Cortex-M0 processors are designed for smart and connected embedded applications, and are ideal for use in simple, cost-sensitive devices due to the lower power-consumption and ability to extend the battery life of critical use cases such as activity trackers. Machine learning models built with Qeexo AutoML are highly optimized and have an incredibly small memory footprint.

A new TDWI Checklist Report examines best practices for data engineering and management to support machine learning with a focus on collecting, cleansing, transforming, and governing new and big data for analysis. In a new TDWI Checklist Report, "Five Data Engineering Requirements for Enabling Machine Learning," Fern Halper, vice president and senior director of TDWI Research for advanced analytics, notes how a new generation of data is reinvigorating interest in AI and machine learning -- and providing new challenges to enterprises of all sizes. Machine learning does what its name implies -- it is a system that learns to identify patterns by examining data. There are two approaches: supervised (where the system is given the desired target and learns to predict the same outcome based on attributes) and unsupervised (where there are no predefined outcomes, and once trained, the model is tested against additional data to make sure the model is valid). Although still in the early mainstream phase of adoption, machine learning is being deployed in a wide range of use cases, including recommendation engines, fraud detection, churn analysis, and cybersecurity.

An article explores how Nvidia Corp. microchips, the kind that are used in video games and by social media networks for photo tagging, are being applied to medicine. They are being used to add machine learning to medical imaging. The idea is to use the technology to spot conditions such as cancer and Alzheimer's disease earlier and faster. But one potential consequence of advancements in this area is reduced dependence on radiologists. Luminex has raised its offer for Nanosphere to obtain its molecular diagnostics technology from 83 million to more than 100 million.

An article explores how Nvidia Corp. microchips, the kind that are used in video games and by social media networks for photo tagging, are being applied to medicine. They are being used to add machine learning to medical imaging. The idea is to use the technology to spot conditions such as cancer and Alzheimer's disease earlier and faster. But one potential consequence of advancements in this area is reduced dependence on radiologists. Luminex has raised its offer for Nanosphere to obtain its molecular diagnostics technology from 83 million to more than 100 million.