Manufacturing's use of machine learning can help implement better strategies for improved outcomes and optimized solutions.
Using machine learning to accurately predict and improve the health and life of a battery will enable manufacturers to embed this software straight into their battery devices and improve the in-life service for the consumer.
The Cisco IoT Center adds machine learning and other enhancements designed to help providers better manage IoT cellular environments and 5G use cases.
Incorporating machine learning capabilities into BI solutions will bring sophisticated analytics to more people, groups, and business units.
Deep learning is capable of incredible things, but if you are working with mostly structured data for straightforward purposes, Machine Learning can be a much more viable and affordable application, especially as a smaller organization with limited resources.
Smart thermostats have been around for a while, but researchers at Swiss federal laboratory Empa have gone one step further, adding machine learning.
Constraint solvers take a set of hard and soft constraints in an organization and formulate the most effective plan, taking into account real-time problems.
Companies are increasingly generating huge volumes of data at the network edge. Massive volumes of data are flowing from smart meters, Internet of Things (IoT) sensors, autonomous vehicles, health monitors, and industrial automation devices, to name just a few sources.
Eveline was developed based on the personal experience of Eveline co-founder and CTO Carson Chen and his wife.
As more transport goes electric and more homes become self-sufficient, the need for longer-lasting, denser batteries will become ever greater.