BrainChip Holdings Ltd, the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, was issued its latest U.S. patent, further strengthening its IP portfolio related to sustainable and efficient AI technologies.
Patent US 11,853,862, “Method, Digital Electronic Circuit and System for Unsupervised Detection of Repeating Patterns in a Series of Events,” facilitates learning in a digital hardware implementation of a spiking network. A key aspect of this unique approach is its effectiveness in performing accurate unsupervised detection or learning of repeating patterns, even when these patterns are embedded in high levels of noise, while being extremely efficient in reducing computing time, energy consumption and silicon footprint.
BrainChip’s Akida IP and MetaTF tools seamlessly transform contemporary neural networks into event-based or spiking networks. This patented technology uniquely synergizes with the converted spiking networks, enabling the streamlined deployment of edge learning algorithms and unlocking use cases that conventional AI tools or solutions cannot attain.
“While we push the bounds with our innovative neuromorphic technology, preserving its integrity is paramount,” said Sean Hehir, CEO of BrainChip. “With 13 patents issued in the U.S. alone, we stand as leaders in developing and implementing next generation AI technologies for intelligent Edge devices and on-chip processing.”
BrainChip’s portfolio now comprises 19 issued patents (13x US, 4x AU, 1x EP, 1x CN). In addition, there are nearly 30 pending patent applications across the US, Europe, Australia, Canada, Japan, Korea, India, Brazil, Russia, Mexico, and Israel.
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, AkidaTM, uses neuromorphic principles to 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
SOURCE: Businesswire
