Compact, Ultra-Low-Power Microchip for Always-on Voice and Sensor Applications Brings Multi-Modal Artificial Intelligence to Edge Devices in All Industries
Irvine, Calif., January 4, 2023 — Syntiant Corp., a provider of deep learning solutions for edge AI applications, today introduced the Syntiant NDP115 Neural Decision Processor™, the newest addition to its family of special purpose silicon, built using the company’s Syntiant Core 2™ inference engine than can run multiple neural network loads at under 1mW.
Available in a 2.1 mm x 2.1 mm 25-ball WLBGA package (0.4mm ball pitch), the NDP115 is small, yet powerful enough to deliver highly accurate, cloud-free audio and sensor AI processing for a wide variety of edge products, ranging from consumer electronics, such as hearables and wearables, to the smart home, such as remote controls, to industrial solutions for predictive maintenance.
“The NDP115 offers the multi-modal functionality of our Core 2 inference engine in a compact, cost- and power-efficient solution for ultra-power and size constrained applications,” said Kurt Busch, CEO of Syntiant. “Combined with our machine learning software models, the purpose-built NDP115 enables developers to easily deploy full audio and sensor processing solutions that address all kinds of consumer and commercial use cases, from home security to industrial IoT.”
Able to run speech inferences at 280 microwatts, the NDP115 is designed to natively run multiple deep neural networks on a variety of architectures, such as CNNs, RNNs and fully connected networks. Ideal for close-talk, far-field, keyword speech and audio event classification applications, the NDP115 also supports I2C and pulse density modulation (PDM) interfaces for sensor fusion, multi-axis acceleration, tilt, magnetic field and pressure.
Key product features include:
- Syntiant Core 2 neural processor
- Support for concurrent neural networks, including multi-sensor fusion
- Embedded user programmable HiFi-3 DSP with 144KB 64 bit data RAM and 64KB 64 bit instruction RAM
- Embedded Arm Cortex M0 microcontroller
- Direct input of PCM audio and support for up to 5 audio streams
- I2C controller and target modes for sensor control and integration
- Up to 13 GPIO pins
- Flexible clock generation
- Onboard firmware decryption and authentication
- 25-ball WLBGA package (0.4mm ball pitch)
The Syntiant NDP115 is now shipping in production volumes. Pricing for 10Ku quantities is $3.25 per unit.
CES 2023
Syntiant will be demonstrating its end-to-end deep learning solutions for always-on vision, audio and sensing applications at CES 2023, including the NDP115 Neural Decision Processor at the Venetian Hotel (Room 108, 36th floor). Visit www.syntiant.com/ces to schedule a demo of the company’s technology being deployed in smart homes, battery management systems, teleconferencing solutions and event detection devices, among other use cases.
About Syntiant
Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering end-to-end deep learning solutions for edge deployment. The company’s purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant’s advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions, with proprietary model architectures and hardware-specific optimizations, that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world’s leading strategic and financial investors including Intel Capital, Microsoft’s M12, Applied Ventures, Robert Bosch Venture Capital, the Amazon Alexa Fund and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com or by following Syntiant on Twitter @Syntiantcorp or LinkedIn.
