Neuromorphic Computing: Relevance for the industry скачать в хорошем качестве

Neuromorphic Computing: Relevance for the industry

Neuromorphic computing, inspired by biological neural networks, offers a transformative approach to AI by addressing the challenges of power consumption, data volume, and latency in edge devices. This video introduces the basics of neuromorphic computing, focusing on spiking neural networks (SNNs) and their advantages over traditional artificial neural networks (ANNs). It covers key topics such as data encoding, training methods, and hardware innovations, including neuromorphic sensors like event-based cameras. Highlighting its industrial relevance, the video showcases real-world applications like drone object identification, gesture recognition, and robotic arm control, demonstrating the efficiency, adaptability, and scalability of neuromorphic technology. 00:00 The problem statement Theory 01:27 Differences and similarities between ANN and SNN 02:53 Times and spikes 03:51 Data encoding 05:44 Training Hardware 07:23 Chips 08:32 Sensors 12:02 Recap 13:27 Industrial use cases Learn more about Neuromorphic Computing @ fortiss: https://www.fortiss.org/en/research/f... https://www.fortiss.org/en/research/f...