BrainChip Holdings Ltd (ASX: BRN), a leading provider of ultra-low power high performance artificial intelligence technology, today announced it is sponsoring and presenting at tinyML Summit, a virtual event March 22-26, 2021. TinyML Summit will feature technical progress and ecosystem development within the “tiny” machine learning industry to enable ultra-low power ML in edge applications.
Tiny ML is a growing field of ML technologies including hardware (dedicated integrated circuits), algorithms, and software capable of performing on-device data analytics at extremely low power to enable a range of always-on applications, primarily in battery-operated devices. Tiny ML is common in audio, visual, navigational, biometric, and medical devices as well as other commercial and industrial uses.
Kristofor Carlson, BrainChip’s Manager of Applied Research, will present a talk “It’s an SNN future: Are you ready for it? Converting CNN’s to SNNs” on Wednesday March 24 from 12:00-1:00 p.m. In this session, Carlson explains how event-based Spiking Neural Networks address the deficiencies of conventional Convolutional Neural Networks, and highlights the ease of use of enabling more efficient and effective technology solutions. Following the presentation Carlson will host a Q&A in BrainChip’s Virtual booth from 1:00pm to 2:00pm.
“BrainChip appreciates the opportunity to showcase our achievements in neuroprocessing at the edge that allow even lower-power, higher-performing AI in audio, vision, olfactory, lidar and other edge sensors,” said BrainChip Chief Development Officer Anil Mankar. “The field of tiny ML includes industry, academia, start-ups, governmental and non-governmental organizations, and TinyML Summit brings us all together to work collectively and advance the state of the market.”
BrainChip’s Akida™ brings artificial intelligence to the edge in a way that existing technologies are not capable. The solution is high-performance, small, ultra-low power and enables a wide array of edge capabilities. The Akida (NSoC) and intellectual property, can be used in applications including Smart Home, Smart Health, Smart City and Smart Transportation. These applications include but are not limited to home automation and remote controls, industrial IoT, robotics, security cameras, sensors, unmanned aircraft, autonomous vehicles, medical instruments, object detection, sound detection, odor and taste detection, gesture control and cybersecurity. The Akida NSoC is designed for use as a stand-alone embedded accelerator or as a co-processor, and includes interfaces for ADAS sensors, audio sensors, and other IoT sensors.
