Edge AI: Its Critical in Moving Industries – and the World, to a Better Future
Article originally posted on Embedded Computing Design.
Empowering Generative AI at the Edge: Unveiling the SAKURA-II Benefits
Introduction
Have you heard about our newly announced SAKURA-II platform?
AI Drives the Software-Defined Heterogeneous Computing Era
The rapid development of artificial intelligence (AI) applications has created enormous demand for high-performance and energy-efficient computing systems.
Multimodal Generative AI on Energy-Efficient Edge Processors
Edge computing will grow exponentially in the next few years, as more and more devices and applications demand low-latency, high-performance, and privacy-preserving computation at the edge of the network.
Efficient Edge AI Chips with Reconfigurable Accelerators
DNA IP and MERA are a potent combination, reducing the hardware-specific knowledge OEMs would otherwise need to power AI applications efficiently.
Connecting Edge AI Software with PyTorch, TensorFlow Lite, and ONNX Models
Data scientists and others may have concerns moving PyTorch, TensorFlow, and ONNX models to edge AI software applications – MERA makes it easy and is model-agnostic.
What is edge AI inference doing for more devices?
AI inference is a common term - but what is edge AI inference? EdgeCortix provides an answer in terms of workloads, efficiency, and applications.
Scoping The AI Chip Landscape Part II: Linley Spring Processor Conference 2021 Highlights | EdgeCortix
This post will cover the artificial intelligence (AI) processors and technologies presented in the recent Spring Processor Conference 2021 organized by The Linley Group
Moving to the Edge: The Greenfield Opportunity | EdgeCortix