Brain Inspired Computing Congress Features BrainChip Founder and CTO Peter van der Made
Aliso Viejo, California – November 17, 2020 – BrainChip Holdings Ltd (ASX: BRN), a leading provider of ultra-low power high performance artificial intelligence technology, today announced that the Company’s founder and Chief Technology Officer Peter van der Made will present at the Brain Inspired Computing Congress. The Computing Congress is a virtual event on November 18-19 2020 focusing on prime uses for brain inspired technologies including autonomous vehicles, robotic arm control, and dynamic vision sensing.
Mr. van der Made will address ‘brain inspired’ applications such as cybersecurity, medical and disease diagnostics, odor and taste classification, gesture and facial recognition, and industrial IoT that BrainChip has developed using event-based neural networks trained with spike-timing-dependent plasticity (STDP) – a function of the biological brain.
“Unlike conventional artificial intelligence networks, event-based processing is capable of continuous incremental learning and can adapt to new information. This capability can result in a superior standard of ‘intelligence’ and more closely resembles the human brain,” said Mr. van der Made. “BrainChip’s work in event-based neural processing is paving the way for these brain inspired applications in commercial and beneficial AI.”
The Brain Inspired Computing Congress brings together the leading start-ups, researchers, and multinational companies exploring technologies spanning neuromorphic engineering, event-based sensors, brain-inspired algorithms and biologically plausible neural networks. The event provides an overview and deep-dive sessions on new architectures for neuromorphic chips, event-based sensors, and efforts to create biologically plausible algorithms and explores overlap and differentiation between applications for conventional deep learning and brain-inspired computing.
Mr. van der Made has been at the forefront of computer innovation and invention for 45 years. He designed the first generations of digital neuromorphic devices on which BrainChip’s Akida™ neuromorphic processor is based, and holds its patent. His book Higher Intelligence: How to Create a Functional Artificial Brain, published in 2013, described the architecture of the brain from a computer science perspective. He remains actively involved in the design of the next generation of Akida chips, and in research on advanced neuromorphic architectures. He is also writing a follow-up book on neuromorphic architecture and the algorithms performed in the neocortex.
The Akida Neuromorphic System-on-Chip (NSoC) brings artificial intelligence to the edge in a way that existing technologies are not capable. The solution is high-performance, small, ultra-low power and enables a wide array of AI edge capabilities. The Akida, intellectual property or device can be used in applications including but not limited to smart home, industrial IoT sensors, unmanned aircraft, autonomous vehicles, medical instruments, audio detection, odor and taste detection, tracking, object detection, gesture recognition, keyword spotting, and cybersecurity.
About Brainchip Holdings Ltd (ASX: BRN)
BrainChip is a global technology company that is producing a groundbreaking neuromorphic processor that brings artificial intelligence to the edge in a way that is beyond the capabilities of other products. The chip is high performance, small, ultra-low power and enables a wide array of edge capabilities that include on-chip training, learning and inference. The event-based neural network processor is inspired by the spiking nature of the human brain and is implemented in an industry standard digital process. By mimicking brain processing BrainChip has pioneered a processing architecture, called Akida™, which is both scalable and flexible to address the requirements in edge devices. At the edge, sensor inputs are analyzed at the point of acquisition rather than through transmission via the cloud to a data center. Akida is designed to provide a complete ultra-low power and fast AI Edge Network for vision, audio, olfactory and smart transducer applications. The reduction in system latency provides faster response and a more power efficient system that can reduce the large carbon footprint of data centers.
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