BrainChip integrates AI into IoT applications
- October 2, 2024
- Steve Rogerson

Australian firm BrainChip has introduced a low-power, portable and intelligent device for integrating artificial intelligence (AI) into consumer, healthcare, IoT, defence and wake-up applications.
The Akida Pico is a low-power acceleration co-processor that enables the creation of compact wearables and sensors.
Akida Pico accelerates limited use case-specific neural network models to create an energy efficient, purely digital architecture. It enables secure personalisation for applications including voice wake detection, keyword spotting, speech noise reduction, audio enhancement, presence detection, personal voice assistant, automatic doorbell, wearable AI and appliance voice interfaces.
It is built on the Akida2 event-based computing platform configuration engine, which can execute with power suitable for battery-powered operation of less than a milliwatt. Akida Pico provides a power-efficient footprint for waking up microcontrollers or larger system processors, with a neural network to filter out false alarms to preserve power consumption until an event is detected. It is suitable for sensor hubs or systems that need to be monitored continuously using only battery power with occasional need for additional processing from a host.
The firm’s MetaTF software flow helps developers compile and optimise their specific temporal-enabled neural networks (TENNs) on the Akida Pico. With MetaTF’s support for models created with TensorFlow, Keras and Pytorch, users avoid needing to learn a new machine language framework while developing and deploying AI applications for the edge.
“Like all of our edge AI enablement platforms, Akida Pico was developed to further push the limits of AI on-chip compute with low latency and low power required of neural applications,” said Sean Hehir, CEO of BrainChip. “Whether you have limited AI expertise or are an expert at developing AI models and applications, Akida Pico and the Akida development platform provide users with the ability to create, train and test the most power and memory efficient temporal-event based neural networks quicker and more reliably.”
Akida is an event-based compute platform for early detection, low-latency products without massive compute resources for robotics, drones, automotive and traditional sense-detect-classify-track products. BrainChip (www.brainchip.com) provides a range of software, hardware and IP products that can be integrated into existing and future designs, with a roadmap for customers to deploy multi-modal AI models at the edge.