Tiny Machine Learning Development Board Now Available for Building Low-Power Voice, Audio and Sensor Applications using Edge Impulse's Embedded ML Platform IRVINE, Calif., Sept. 29, 2021 (GLOBE NEWSWIRE) -- Syntiant Corp, a provider of deep learning solutions making edge AI a reality for always-on applications in battery-powered devices, today unveiled its TinyML Development Board, an easy-to-use developer kit aimed at both technical and non-technical users for building machine learning-powered applications in smart products, such as speech commands, wake word detection, acoustic event detection and other sensor use cases. Equipped with the ultra-low-power Syntiant NDP101 Neural Decision Processor, the TinyML board can enable speech and sensor applications to run at under 140 and 100 microwatts, respectively, delivering 20x more throughput and 200x efficiency improvement compared to traditional MCU-based systems. Sized at 24 mm x 28 mm, the Syntiant TinyML board is a small, self-contained system that allows trained models to be easily downloaded via Edge Impulse through a micro-USB connection without the need for any specialized hardware. The new board also is fully compatible with Arduino's open-source platform. "Syntiant's TinyML board is another example of how we are advancing AI pervasiveness by moving machine learning from the cloud to the edge," said Kurt Busch, CEO of Syntiant.

The ability for marketers to gauge intent these days is spooky. Performing a simple Google search for "hotels in Angeles City" while sitting in a cafe in Manila will suddenly surface "cheapest transport from Manila to Angeles City" ads in your Facebook stream. It knows you'll need cheap transport to get there so you can spend your money on other things. What you may find even more surprising is when you're talking to a mate on the phone about the carnal pleasures of Angeles City and suddenly STD test ads start appearing in your Twitter feed. Is your phone really listening to what you're saying?

Since the HAL9000 and Star Trek's M-5 Multitronic, the power and capabilities of AI have always been oversold by both Hollywood and Silicon Valley. Although we're still waiting on machines that can carry on an intelligent conversation, AI has been creeping into many objects in our everyday lives behind the scenes, making them more useful and proactive. People are most familiar with the intelligent assistants built into devices like the Amazon Echo, Google Nest Hub and Apple HomePod, but as I wrote more than three years ago, these rely on cloud backend services for most of their smarts, using local hardware primarily to recognize their wake word and listen for follow-up questions. The combination allows surprisingly sophisticated deep and machine learning models to run on embedded systems. Until recently, shoehorning AI software into a battery-powered device has required data scientists skilled in working with the constraints of an embedded SoC, but recent advances in AI development and automation frameworks, categorically termed TinyML, greatly expands the realm of smart devices.

Syntiant, an Irvine, California-based startup with big name backers like Intel and Microsoft, said its custom chips could be used to push Amazon's Alexa into smaller, battery-powered devices like wearables and wireless headphones that wake themselves up when they hear the voice assistant's wake word or other commands. Amazon just approved its deep learning accelerators for use with Alexa Voice Services (AVS). The company's NDP100 can be programmed to continuously listen for 64 wake words or specific sounds--like glass breaking or a baby crying--with power consumption in the range of 150 uW and more than 100 KB of SRAM. "These chips are purpose-built for keyword spotting such as wake words like Alexa, and now our processors can be used for quickly developing voice applications in battery-powered devices," chief executive Kurt Busch said in a statement. Syntiant, which was founded by former engineering executives from Broadcom, has raised over $30 million in funding from investors including Microsoft's M12, Amazon's Alexa Fund, Applied Ventures, Intel Capital, Motorola Ventures, and Robert Bosch Venture Capital.