BrainChip Presents: A Neuromorphic Processor for Power Efficient Edge AI Applications For more than a decade, The Linley Group has delivered the industry’s premier processor conference. This year, the Linley Fall Processor Conference will feature virtual presentations that run half days on October 20-22 and 27-29, 2020. As you’ve come to expect from our past conferences, we’ll feature the same high-quality technical content while enabling attendees from around the world to participate in the forum via live-stream. Join BrainChip on October 20, 2020, at 10:30 am PT for: A Neuromorphic Processor for Power-Efficient Edge AI Applications Many edge-AI processors take advantage of the spatial sparsity in neural networks models to eliminate unnecessary computations and save power. But neuromorphic processors achieve further savings by performing event-based computation, which exploits the temporal sparsity inherent in data generated by audio, vision, olfactory, lidar, and other edge sensors. This presentation will provide an update on the AKD1000, BrainChip’s first Neural network SoC (NSoC), and describe the advantages of processing information in the event-domain. For more information and to register for this Conference, clickHERE.

In Case You Missed It... BrainChip and VORAGO Technologies Agree to Collaborate through the Akida™ Early Access Program Agreement to Support Phase I of NASA Program for Radiation-Hardened Neuromorphic Processor BrainChip recently announced that VORAGO Technologies has signed the Akida™ Early Access Program Agreement. The collaboration is intended to support a Phase I NASA program for a neuromorphic processor that meets spaceflight requirements. The BrainChip Early Access Program is available to a select group of customers that require early access to the Akida device, evaluation boards and dedicated support. The EAP agreement includes payments that are intended to offset the Company’s expenses to support partner needs. The Akida neuromorphic processor is uniquely suited for spaceflight and aerospace applications. The device is a complete neural processor and does not require an external CPU, memory or Deep Learning Accelerator (DLA). Reducing component count, size and power consumption are paramount concerns in spaceflight and aerospace applications. The level of integration and ultra-low power performance of Akida supports these critical criteria. Additionally, Akida provides incremental learning. With incremental learning, new classifiers can be added to the network without retraining the entire network. The benefit in spaceflight and aerospace applications is significant as real-time local incremental learning allows continuous operation when new discoveries or circumstances occur. CLICK TO READ MORE Are you interested in learning more about the BrainChip Early Access Program? Send us a messageHERE.