Unless the voice assistant boom driven by Google and Amazon tapers off, microphones could be embedded in everything from thermostats and refrigerators to wearables and headphones over the next few years. Tapping into the push to control almost anything with simple spoken commands, a number of companies are trying to train battery-powered devices to be better listeners.
Syntiant, a semiconductor startup founded last year by former engineering executives from Broadcom, is trying to slash the power required for always-on listening applications such as keyword spotting or speaker identification. The company is building chips based on 40-nanometer NOR flash memory that store machine learning models and perform operations in the same place. It plans to enter volume production in the first half next year.
The Irvine, California-based company is jumping into the market for chips aiming to be more efficient than CPUs, graphics processors (GPUs) and digital signal processors (DSPs). Unlike Nvidia, which dominates the training market, Syntiant is focused on running inference inside devices without shipping workloads to the cloud, potentially improving privacy, lowering latency and saving bandwidth. Like training, inference today usually takes place in data centers.