Quantum Ventura developed the CyberNeuro-RT (CNRT) technology offering in partnership with Lockheed Martin Co’s MFC Division and Pennsylvania State University.

Laguna Hills, Calif., January 17, 2025 – BrainChip Holdings Ltd, the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI, has announced its integration into an innovative technology offering that leverages the Akida™ processor to provide cybersecurity protection for WiFi access, home router, small enterprise routers and other network access devices.

Quantum Ventura developed the CyberNeuro-RT (CNRT) technology offering in partnership with Lockheed Martin Co’s MFC Division and Pennsylvania State University under partial funding from the US Department of Energy. BrainChip supplies at-the-edge neuromorphic processing to facilitate on-chip learning for deployment network-specific attack detection. Akida’s small form factor provides magnitudes less power consumption than a GPU, overcoming form factor and power limitations of internet-connected devices that otherwise would be unprotected.

“CyberNeuro-RT is the only game in town for implementing managed cybersecurity support of edge devices that cannot rely on a central server to identify threats and attacks due to cost or power issues,” said Srini Vasan, President and CEO of Quantum Ventura. “Having the neuromorphic capabilities that BrainChip provides directly integrated into CNRT better allows for the detection of threats across multiple devices that otherwise would be vulnerable to exploitation.”

The implementation of Akida into CNRT is a direct result of BrainChip’s and Quantum Ventura’s previously announced partnership to develop state-of-the-art cyberthreat-detection tools for the US Department of Energy under the Small Business Innovation Research (SBIR) Program. The result of this collaboration highlights BrainChip’s ability to work with partners to bring edge AI compute to next-generation products and markets.

The Akida neural processor and AI IP can find unknown repeating patterns in vast amounts of noisy data, which is an asset in cyberthreat detection. Once Akida learns what normal network traffic patterns look like, it can detect malware, attack signatures, and other types of malicious activity. Because of Akida’s unique ability to learn on-device in a secure fashion, without need for cloud retraining, it can quickly learn new attack patterns, enabling it to easily adapt to emerging threats.

BrainChip IP supports incremental learning, on-chip learning, and high-speed inference with unsurpassed performance in microwatt to milli-watt power budgets, ideal for advanced AI/ML devices such as intelligent sensors, medical devices, high-end video-object detection, and ADAS/autonomous systems. Akida is an event-based technology that is inherently lower power than conventional neural network accelerators, providing energy efficiency with high performance for partners to deliver AI solutions previously not possible on even battery-operated or fanless embedded, edge devices.

“In today’s always-connected, always-on world, there is an increasing need for cybersecurity solutions that can thwart attacks through otherwise unsecure devices connected to the network,” said Sean Hehir, CEO of BrainChip. “We are proud of our work with Quantum Ventura to integrate threat detection using AI on a neuromorphic platform to provide high-quality protection against cybersecurity threats. Akida’s on-chip learning can adapt to new threats and redirects unknown threats to the cloud, providing faster and more cost-efficient analysis capabilities than otherwise possible.” 

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