MicroAI Train Machine Learning Models in an Embedded Environment.

MicroAI enables AI training on Renesas MCUs

Introducing AI technology to endpoints to shorten time to market in capital-intensive industries

Edge-native artificial intelligence (AI) and machine learning (ML) product pioneer MicroAI brings MicroAI Atom ML technology to Renesas' RA microcontroller (MCU) ) Announced that it has been integrated into the product line. Working with Renesas, the world leader in microcontrollers, to bring machine learning to MCUs, MicroAI will be the first in the industry to train machine learning models directly in an embedded environment.

Asset owners and manufacturers of industrial, commercial and consumer systems and devices can leverage MicroAI-powered MCUs to quickly deploy edge AI in their machines. This allows you to embed intelligence in your data sources, reducing connectivity, cloud, and operational costs while reducing the time to market for AI-powered solutions. Incorporating MicroAI can provide next-generation intelligence to machines and IoT devices.

Mohammed Dogal, Senior Director of Global Business Development at Renesas, said: “We look forward to working with MicroAI to support its technology with our MCUs. The industry has long wanted to bring asset performance insights and intelligence closer to data sources, but with MicroAI. By working together, we can provide the solution. "

MicroAI, a patented advanced machine learning algorithm that can be mounted directly on machines or IoT devices, provides asset owners and manufacturers with in-depth insights into the behavior, health and performance of their devices and devices. For example, robot welding arms on automobile assembly lines and greenhouse gas efficiency in agriculture. Asset owners and manufacturers are often faced with unforeseen downtime and fixed maintenance schedules, which create unnecessary costs and avoidable maintenance times. If you don't know the performance of your assets, you can only deal with them after they occur.

By improving visibility into production line operations, you can identify what is causing unplanned downtime and annoying events, so asset owners and manufacturers make adjustments to reduce those events and operate. Can proceed smoothly.

Yasser Khan, CEO of MicroAI, said: “Companies around the world were looking for predictive insights into asset performance, behavior, and utilization to increase the productivity of the equipment they deploy. MicroAI is working with Renesas to leverage our technology. It brings machine learning to the MCU, enabling it to train machine learning models directly in an embedded environment and provide that capability. "

Source: MicroAI media announcement


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