Syntiant Surpasses Milestone of 10 Million Processors Shipped

Syntiant Corp., a deep learning chip technology company advancing AI pervasiveness in edge devices, today announced that it has shipped more than 10 million of its Syntiant NDP100 and Syntiant NDP101 Neural Decision Processors (NDPs) to customers across the globe. 

Since the company’s founding in 2017, Syntiant has achieved unprecedented success in the semiconductor industry, embedding its always-on deep learning solution with power-restricted voice and sensor applications in millions of edge devices, ranging from earbuds to mobile phones to laptops.

“We believe there isn’t another chip company dedicated to machine learning that has been able to achieve what we have accomplished in a little over three years,” said Kurt Busch, CEO of Syntiant. “Today’s milestone is further evidence of how our entire team, in close collaboration with our global supply chain partners, from design to testing to production, continues to execute flawlessly in bringing our technology to millions of edge devices, making them smarter, more efficient, and more helpful to people in their daily lives.”

Embedded with the Syntiant Core 1™, the company’s first generation neural network, the NDP100 and NDP101 microwatt-level processors achieve 100x efficiency and 10x the throughput over traditional CPUs and DSPs, providing highly accurate artificial intelligence functionality to battery-powered devices, free from a cloud connection and with minimal power consumption. The NDP100 processor runs voice, audio and sensor applications consuming only 140uW (microwatts) with low latency, such as keyword spotting, wake word detection, speaker identification and audio event and environment classification, as well as sensor analytics.

“Syntiant’s innovative technology is helping drive the growing adoption of hands-free, voice control in edge devices,” added Busch. “We’re excited about the future, and we look forward to accelerating our production ramp in 2021 as consumers across the world increasingly rely on deep learning to bridge the gap between people and technology.”