Syntiant’s Speech Recognition Chip Certified for Alexa

Syntiant, an AI chip start-up based in Irvine, California, received the news on August 7 that its Neural Decision Processors (NDP), NDP100 and NDP 101, have been certified by Amazon. This allows the integration of the chips into a variety of Alexa-based devices.

The company is already well supported by a number of heavyweight tech investors including Amazon’s Alexa Fund, Intel, Microsoft’s M12 Venture Fund and Robert Bosch Venture Capital GmbH. To date, Syntiant has raised US$30 million.

Clearly, being certified by Amazon is another major coup for the company and will enable device OEMs to offer a built-in “always-on” Alexa listening experience in even the most power-sensitive battery-powered devices including earbuds and Bluetooth headsets, smartwatches, IoT sensors, and remote control devices as well as introducing voice control into other entirely new form-factor devices.

This will considerably expand the Amazon Echo ecosystem and offers a potentially huge market opportunity for Syntiant. Counterpoint forecasts that the wireless hearables market alone will grow to 175 million units globally by 2021.

Interestingly, Syntiant already has a partnership with earbud vendor Bragi, who is using Syntiant’s processors in its wireless earbuds and in May it announced that it is also working with Taiwanese gaming company MSI to introduce “voice in-game” features via Amazon Alexa.

Let us take a closer look at the newly certified Syntiant products. The NDP10x series of speech and audio processors are custom built to run neural workloads. They are primarily designed for integration into various types of voice and audio-enabled devices. According to Syntiant, the processors can recognize up to 64 words or other sensor patterns while consuming just 150 microwatts. The company claims that this is a 200-fold improvement over what a typical microcontroller can offer.

With dimensions of just 1.4 mm x 1.8 mm, the chip is supplied in a 12 ball WLBGA package and is typically connected directly to a digital microphone which triggers a larger, usually sleeping, system within a device (Exhibit 1). Once awake, this system interrogates the NDP100 to determine which wake word or command it heard. The chip also has a three-second audio buffer in case the system needs to catch up on what was said during its wakeup routine.

As with most AI ASICs, the chip only performs inferencing. Training happens in the cloud using Google’s TensorFlow software library with the resultant neural network parameters programmed directly into the chip as firmware using Syntiant’s proprietary algorithms. The inference engine can classify 100 words per second.

Syntiant’s NDP100 voice-recognition chip

Exhibit 1: Syntiant’s NDP100 voice-recognition chip

Syntiant’s technology is based on “processor-in-memory” architecture, and it is one of a small band of start-ups focused on developing an all-analog memory computing solution. However, its first products, the NDP10x series of processors use digital multiply-accumulate (MAC) units rather than flash memory-based multipliers.

Performing computation “in-memory” eliminates both the memory bandwidth and memory power penalties normally associated with CPU-based processors, resulting in significant reductions in overall power consumption. Other start-us involved in this space include Mythic and Gyrfalcon, but Syntiant seems to be the only company focused on low-power audio applications.

In future products, the company intends to replace the digital MACs with low precision but very accurate analog MACs which should result in further, and possibly significant, power savings. This will make its chips even better suited to ultra-low-power applications. However, mass-producing an analog-based design presents its own set of challenges, which is perhaps why Syntiant initially opted for a digital MAC design.

The company is also developing a 20 TOPS/Watt NPD chip to process video which should be sampling in H2 2019 and should enable it to expand into more markets.

Syntiant NDP 100 architecture

Exhibit 2: Syntiant NDP 100 architecture

Syntiant is one of ten AI chip start-ups profiled in Counterpoint Research’s upcoming report on the AI chip start-up market. Other companies profiled include Efinix, FlexLogix, Graphcore, Gyrfalcon, Habana Labs, Mythic, ThinCI and Wave Computing.

Mobile XR : The Future of Extended Reality (AR/VR/MR)

The next generation of connectivity (5G, WiFi 6, 802.11ay) is poised to enhance the way we interact with the current crop of devices. Extended Reality – XR (VR/AR/MR) is one such technology that will benefit from the introduction of 5G and Artificial Intelligence (AI). The present generation of XR devices requires either a smartphone or a powerful PC to deliver some level of immersive experiences. This experience sometimes is limited as the smartphone alone is not powerful enough to deliver a truly immersive experience and connecting with a PC requires it to be tethered with a wire, sometimes creating a barrier for the immersive experience. Though we are seeing standalone XR devices beginning to proliferate but most of these devices are bulky, power hungry as most of the processing is concentrated or centralized. The standalone “Mobile XR” has tremendous potential not only to interact or consumer immersive content but also to create. However, there needs to be some technical breakthroughs which can drive sleek, ultra-lightweight XR devices form-factor which can offer powerful XR experiences more efficiently.

New Technologies: 5G & AI

At the 4G/5G Summit 2018, Qualcomm showcased a concept XR technology that it has dubbed “Boundless XR”, a photorealistic Mobile XR over 5G. A 5G capable XR device with a powerful processor and augmented by edge cloud computing.

Exhibit: XR Device with 5G connectivity and augmented edge cloud infrastructure.

Source: Qualcomm
  • A powerful processor will enable the XR device to have on-board processing capabilities, eliminate the need for it to be tethered to a PC.
  • Connectivity over 5G will provide a reliable and low latency link to the cloud infrastructure delivering high-quality content to the device.
  • A third significant feature in the XR ecosystem will be the deployment of edge cloud for faster computing. The edge cloud also improves the overall network efficiency and improves the availability of content to users as and when they need it.
  • High-speed connectivity and processing power together will be able to deliver the XR experience with better and immersive content, further overcoming the limitation of the present XR devices.
  • Further, on-device + cloud-based AI can drive the fluidity of the overall XR experience with better optimization of sensors, image stabilization, object detection, semantic segmentation and so forth

New Techniques: Split Rendering

Exhibit: Split Rendering - Distributed XR Workloads Processing for More Efficient Form-Factors .

Source: Qualcomm 4G/5G Summit

This creates an opportunity for new players to enter the XR ecosystem, especially the network operators that missed out on the cable TV revolution. For starters, the content will be delivered over the 5G network and will require a reliable connection from a network provider. In addition, network operators can monetize their investment in 5G by providing the edge cloud infrastructure that will host content. It will also allow the device to have better rendering by splitting complex computation between the servers and the XR device itself. Faster and robust connectivity will further content providers like NextVR delivering live entertainment and online gaming companies to engage the user with-in the ecosystem.

Silicon and system level, players such as Qualcomm are working on specific technologies like Split Rendering, 5G and on-device AI which should remove a number of barriers for XR devices to take off. However, this technology is still in its nascent stage and will only mature once there is a robust 5G infrastructure in place.

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