Valeo: See the Invisible, page-175

for reference here is the original Valeo ann from the company:



https://www.asx.com.au/asxpdf/20200609/pdf/44jgtl9y2svb55.pdf


BrainChip Signs Joint Development Agreement with Tier-1 Automotive Supplier

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BrainChip to collaborate on the development of neural network processing solutionsfor Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV) • Evaluation to integrate the AkidaTM System-on-Chip (SoC) as a neural network processor

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Aliso Viejo, California – 8 June 2020 – BrainChip Holdings Ltd (ASX: BRN), a leading provider of ultra-low power high performance AI technology today announced the signing of a joint development agreement utilizing BrainChip’s Akida neuromorphic SoC with Valeo Corporation, a Tier-1 European automotive supplier of sensors and systems for Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV).The Agreement provides for specific performance milestones and payments that are expected to cover the Company’s expenses. The term of the Agreement is defined by the achievement of performance milestones and the availability of the Akida device. The Agreement was binding upon execution. Either party can terminate the Agreement for convenience with specific notice. Thevalidation of the Company’s Akida device by a Tier-1 supplier of sensors and systems to the automotive industry is considered to be a significant development.In ADAS and AV applications, real-time processing of data is critical for the safety and reliability of autonomous systems. Suppliers and manufacturers in the automotive industry have recognized that the advanced and highly efficient neuromorphic nature of the Akida SoC makes it ideally suited to process data at the “Edge” for their advanced system solutions. By combining the Akida neural network processor with sensors, the resulting system can achieve ultra-low power, minimum latency, maximum reliability, and incremental learning. This is a major advancement over current architectures which require large amounts of data to be transmitted to a Central Processing Unit (CPU) or Graphics Processing Unit (GPU), which has the burden of processing all data from all sensors and then combining the results to make a decision or retrain the network for new classifiers.