2023 BrainChip Discussion, page-3880

November 16, 2023
About tinyML Asia
Machine learning (ML) is at the forefront of providing artificial intelligence to all aspects of computing. It is the technology powering many of today’s advanced applications from image recognition to voice interfaces to self-driving vehicles and beyond. Many of these initial ML applications require significant computational resources most often found in cloud-scale data centers. To enable industry usage and adoption, it is, therefore, necessary to significantly reduce the power consumed to bring applications to end devices at the cloud edge (smartphones, wearables, vehicles, IoT devices, etc.) and to reduce the load on required data center resources.
  
10:15 am to 10:35 am

Solutions and Applications
Brainchip’s Specialized Akida Architecture for Low Power Edge Inference with HW Spatiotemporal Acceleration and On-chip Learning
Nandan NAYAMPALLY, CMO, Brainchip

Abstract (English).
1:15 pm to 2:00 pm

Keynote by Saeed Afshar from Western Sydney University
Optimized Event-Driven Spiking Neural Network for Low-Power Neuromorphic Platform