MicroAI Demonstrated Edge-Native AI at CES

11 JANUARY 2022

MicroAI™, the pioneer in edge-native artificial intelligence (AI) and machine learning (ML) software, demonstrated its Launchpad™ quick-start deployment tool and MicroAI Security software at this year’s CES® exhibition, which took place in Las Vegas from 5th to 7th January 2022.

MicroAI demonstrated Launchpad with iBASIS, a global communications solution provider. Using connectivity provided by iBASIS, the demo showed how Launchpad can be easily used to manage MicroAI software running on embedded devices, and to handle data from multiple sensors, for example temperature information, as well as to manipulate, analyze and present this data on a single screen. The demo also showed how Launchpad can securely administer an entire fleet of SIM cards, all within the same portal, thus simplifying mobile device management for customers.

“Edge-native AI enables embedded AI software to run on microcontrollers and microprocessors in endpoint devices, transforming how AI can be made available right where data is captured,” said MicroAI CEO Yasser Khan. “Launchpad provides a straightforward way for companies to manage this – opening up new opportunities across many industry sectors.”

At CES, MicroAI also presented its innovative MicroAI Security software at the iBasis booth. MicroAI Security provides a revolutionary approach to mitigate cyber-attacks, and to help protect critical assets, IoT devices, and industrial and manufacturing systems. It uses a proprietary embedded AI algorithm that can detect, alert, and visualize cyber security intrusions in real-time, and runs directly on edge and endpoint connected devices. The algorithm teaches a connected device to self-monitor and provide alerts when anomalous behavior is identified.

In a separate suite in the Trump International Tower, MicroAI demonstrated how its software can be used by manufacturers. MicroAI is collaborating with KDDI, who provide a private LTE network for the system. The MicroAI software enables data from sensors in a factory to be analyzed by edge AI algorithms, for example monitoring vibration for predictive maintenance of machine tools. MicroAI Grid then enables a manufacturer to link up multiple sites around the world, so data and intelligence can be automatically shared.

MicroAI

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