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LG signs Ceva for smart IoT chips

LG signs Ceva for smart IoT chips

Business news |
By Nick Flaherty



LG Electronics (LG) has licensed and deployed the CEVA-XM4 intelligent vision DSP in its latest Edge AI system-on-chip (SoC) for smart appliances.

The XM4 vision DSP from Ceva is used in the LG8111 SoC driving LG’s MoodUP refrigerator on display at CES 2023 this week. It was first displayed in Berlin in September at IFA 2022.

The CEVA-XM4 DSP core, launched back in 2015, enables features such as gesture recognition and pack monitoring in smart home appliances via vision processing, coupled with LGs ThinQ.AI platform.

Local AI processing

The ARM-based chip has an integrated LG-specific AI processor to handle the inputs from the vision, voice and control processors for local inference. The Eris Reference Board for the LG8111, which has a simple 2.4GHz WiFi and Bluetooth connection, connects to Amazon Web Services for cost effective machine learning device development platform for applications such as image classification/recognition, speech recognition, and control intelligence.

“At LG we are always looking to take the user experience to the next level, and our LG8111 Edge AI SoC is the ideal processor for our ThinQ.AI Platform to power our smart home appliances,” said Woonsuk Chang, Smart Solution TP Leader at LG. “The CEVA-XM4 intelligent vision DSP provides advanced computer vision and imaging capabilities within the SoC, camera-enabled features in our products.”

Ran Snir, Vice President and General Manager of the Vision Business Unit at CEVA, added “We are proud to see our CEVA-XM4 DSP adopted by LG in their latest Edge AI SoC. The smart home provides huge opportunities for edge AI, with endless possibilities for innovation to improve the user experience leveraging the camera for embedded vision and AI. We look forward to seeing how LG and its ThinQ.AI developer network advance smart home appliances using intelligent vision and AI.

Ceva has a range of Computer Vision & Imaging platforms and processors for AI at the edge.

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