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HomeNewsKneron's New Edge AI Chip Is 2X More Power-Efficient Than Others

Kneron’s New Edge AI Chip Is 2X More Power-Efficient Than Others

Kneron, an edge AI chip maker for edge devices, has released its latest chip that is at least 2x more power-efficient than Intel and Google’s existing processors. KL720 AI SoC focuses on driving the processing needs of real-world use cases such as Smart TVs, AI glasses and headsets, and high-end IP Cams.

According to the company, KL720 AI SoC comes in at 0.9 TOPS per Watt to provide better performance for AI workloads, of course, with an added 2 to 4 times the power-efficiency of the rest. Kneron leverages the Arm Cortex M4 CPU for navigating different workloads across the resources.

The processor can handle heavy workloads at the edge by processing 4K images, Full HD videos, and 3D sensing for fool-proof facial recognition and gesture control for gaming, among others.

Kneron earlier chip–KL520–was focused toward edge AI for smart locks, security cameras, drones, and home appliances. However, with its latest processor, it has doubled down on high-performance tasks at the edge. What differentiates Kneron is that its products deliver high power efficiency. Its first-generation chip (KL 520) runs on 8 AA batteries for fifteen months, thereby delivering value without hassles.

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“KL720 combines power with unmatched energy-efficiency and Kneron’s industry-leading AI algorithms to enable a new era for smart devices. Its low cost enables even more devices to take advantage of the benefits of edge AI, protecting user privacy, to an extent competitors can’t match. Combined with our existing KL520, we are proud to offer the most comprehensive suite of AI chips and software for devices on the market,” said Kneron founder and CEO Albert Liu.

The robustness of their solutions has been recognized by Gartner’s Cool Vendor in AI Semiconductor 2020 and some funding of $40M in January 2020. The company is committed to enhancing end-to-end integrated hardware and software solutions for edge AI.

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Analytics Drift
Analytics Drift
Editorial team of Analytics Drift

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