See how we deliver cloud-level AI inference performance at the edge, with orders of magnitude better energy efficiency and processing speed - while drastically reducing customer operating costs.
One of the biggest challenges facing edge computing is handling the increasing complexity and diversity of data sources and modalities, such as images, videos, audio, text, speech, and sensors. This challenge is where multimodal generative artificial intelligence (AI) comes into play...
The rapid development of artificial intelligence (AI) applications has created enormous demand for high-performance and energy-efficient computing systems. However, traditional homogeneous architectures based on Von Neumann processors face challenges in meeting the requirements of AI workloads, which often involve massive parallelism, large data volumes, and complex computations. Heterogeneous computing architectures integrate different processing units with specialized capabilities...
BittWare, a Molex Company, has selected EdgeCortix’s SAKURA-I, best in-class, energy-efficient, AI co-processor as its edge inference solution."For over thirty years, the BittWare brand has been trusted to bring the best acceleration technology to market. We are delighted to be partnering with EdgeCortix to bring their edge focused SAKURA-I acceleration solution to market.” ~ Craig Petrie, Vice President, BittWare.
Join the EdgeCortix team for a unique AI systems event that will give you both hardware and software tools and techniques for training, deploying, and serving machine learning. Attend EdgeCortix CEO, Sakya Dasgupta's session on September 13th, "Balancing Trade Offs For Edge AI Compute - Making Edge Training & Inference Worthwhile."
