BrainChip Holdings Ltd announced
Quantum Ventura Inc. will use
BrainChip's Akida technology to develop new cyber threat-detection
tools.
In this federally funded phase 2 program, Quantum Ventura is creating
state-of-the art cybersecurity applications for the U.S. Department of
Energy under the Small Business Innovation Research (SBIR) Program. The
program is focused on "Cyber threat-detection using neuromorphic
computing," which aims to develop an advanced approach to detect and
prevent cyberattacks on computer networks and critical infrastructure
using brain-inspired artificial intelligence.
"Neuromorphic computing is an ideal technology for threat detection
because of its small size and power, accuracy, and in particular, its
ability to learn and adapt, since attackers are constantly changing
their tactics," said Srini Vasan, President and CEO of Quantum Ventura
Inc. "We believe that our solution incorporating BrainChip's Akida will
be a breakthrough for defending against cyber threats and address
additional applications as well."
"This project with the Department of Energy offers an ideal opportunity
to demonstrate how Akida opens up new possibilities in cybersecurity,
including the ability to run complex AI algorithms at the edge, reducing
the dependency on the cloud," said Rob Telson, Vice President of
Ecosystems & Partnerships at BrainChip. "We are excited about the
progress that Quantum Ventura are making with BrainChip in this project
which is extremely vital to the safety of the nation's infrastructure."
The Akida neural processor and AI IP can find unknown, repeating
patterns in vast amounts of noisy data, which is an asset in cyber
threat 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 micro watt 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
fan-less embedded, edge devices.