BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, brain-inspired AI, today announced that it will be demonstrating gesture recognition capabilities with its Akida™ 2 processor technology running in combination with Prophesee’s event-based camera in Hall 5 Booth No. 5-213 at Embedded World 2025 in Nuremberg, Germany March 11-13. BrainChip will also demonstrate its edge LLM model based on Temporal Enabled-Neural Networks (TENNs) at the event.

BrainChip’s Akida technology demonstrates the possibilities of embedded AI. As part of its exhibition at Embedded World, the company will showcase the benefits of low-latency and ultra-low power consumption for gesture recognition using the Akida 2 FPGA platform in conjunction with the Prophesee EVK4 development camera. Unlike other approaches, the combination of Prophesee’s event-based vision sensors with Akida’s event-based computing can capture extremely high-speed movement with high sparsity so that only information relevant to the gesture is processed, enabling faster response times. These computer vision systems open new potential in areas such as autonomous vehicles, industrial automation, IoT, security and surveillance and AR/VR.

Integrating Prophesee event-based vision sensors with Akida's event-based processing will enable the development of new, compact SWaP (Size, Weight, and Power) form factors, unlocking fresh product opportunities in the market.

“By combining our technologies, we can achieve ultra-high accuracy in a small form factor, empowering wearables and other power-constrained platforms to incorporate advanced video detection, classification, and tracking capabilities,” said Etienne Knauer, VP Sales & Marketing at Prophesee. “Processing our event-based sensor data streams efficiently leverages their sparse nature, reducing computational and memory demands in the final product.”

Dr. M. Anthony Lewis, Chief Technology Officer at BrainChip, will present “Fast Online Recognition of Gestures using Hardware Efficient Spatiotemporal Convolutional Networks via Codesign” March 12 at 1:45 p.m. as part of the Embedded Vision track. Lewis will discuss how TENNs developed by BrainChip can be used to tackle a wide range of vision tasks. The presentation will highlight how the co-design of the model architecture, training pipeline and hardware implementation can combine to achieve State-of-the-Art performance, using the gesture recognition task as an example.

“I am eager to present to attendees of Embedded World how faster gesture recognition is a game-changer and the opportunity to showcase the advancements that are possible through the combination of our neuromorphic Akida processor and Prophesee’s event-based vision camera,” said Dr. Lewis. “The ability to detect and track using event-based vision sensors with unprecedented efficiency, precision and low power at the edge solves a key challenge for AI developers and opens up an array of possibilities across a wide spectrum of applications.”

BrainChip’s Akida is an event-based compute platform ideal for robotics, drones, automotive and other visual sense-detect-classify-track requirements that cannot support massive compute resources. BrainChip offers a comprehensive range of software, hardware and IP products that can be integrated into both existing and future designs, with a roadmap for customers to deploy multi-modal AI models at the edge.

As the premier global event for the embedded systems community, Embedded World brings together leading experts, key players and industry associations to explore the latest advancements in embedded systems, including hardware and software design, M2M communication, and complex system solutions. To learn more about BrainChip’s participation at Embedded World and to register for the event, interested parties are invited to visit https://brainchip.com/embedded-world-2025-march-11-13/.

About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY)

BrainChip is the worldwide leader in Edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida™, uses principles that mimic the human brain, analyzing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables Edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security. Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like Tensorflow/Keras. In enabling effective Edge compute to be universally deployable across real world applications such as connected cars, consumer electronics, and industrial IoT, BrainChip is proving that on-chip AI, close to the sensor, is the future, for its customers’ products, as well as the planet. Explore the benefits of Akida at www.brainchip.com.

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