Edge AI

Edge computing can lower network traffic, reduce latency and facilitate local decision making, all by processing data locally.

Peer-to-peer serverless infrastructure, powered by blockchain technology and built using the spare capacity all around us.

Edge computing is where server resources, ranging from credit-card-size computers to micro data centers, are placed closer to data and information-generation sources, to reduce the latency and bandwidth issues associated with large-scale cloud computing.

Read about the future of cloud computing. Get an intelligent, consistent, and comprehensive platform from cloud to edge with Azure.

Edge computing promises to improve performance and reduce costs.

Today’s applications use AI for a variety of tasks from translating text on webpages to object recognition in images, making machine learning models a critical part of application development. Users expect this functionality to be fast and reliable, while developers want to keep proprietary machine learning models reliable and secure.

Long an intermediary, Cloudflare is turning itself into a viable alternative to AWS.

The company is expanding its US network in a big way, and it’s turned to two edge data center startups for help.

Cloudflare is uniquely positioned to become a major player in an Internet 3.0 world, where politics matter more than economics.

A CDN edge server is a computer that exists at the logical extreme or “edge” of a network. An edge server often serves as the connection between separate networks.

Cloudflare Workers® is one of the largest, most widely used edge computing platforms. We announced Cloudflare Workers nearly three years ago and it's been generally available for the last two years.

The evolution of the network edge as the enterprise accelerates their digital transformation. The network edge is becoming a critical fixture of every hybrid and multi cloud strategy to improve the security, performance and reliability of enterprise digital infrastructures.

Edge computing brings computation closer to the network edge, optimizing IoT devices and web applications. Learn about the pros and cons of edge computing.

The Cloudflare-NVIDIA partnership will be a 'massive platform on which developers can deploy applications that use pre-trained or custom machine learning models in seconds.'

On April 16, Intel and Udacity jointly announced their new Intel® Edge AI for IoT Developers Nanodegree program to train the developer community in deep learning and computer vision.

Strengths and weaknesses of using AI on the Edge.

In recent years, the advancements in deep learning, which is a subset of Artificial Intelligence (AI), have accelerated the growth of AI applications and services. From personal assistants to recommendation systems, AI never fails to amaze us.

Artificial Intelligence can change all industries. Today we explore its effects on edge computing and what it has to offer to edge computing in the future.

AI in Edge Computing. The rapid rise of the applications powered by Artificial Intelligence raises the data center's technical requirements in AI future.

Artificial Intelligence (AI) is coming to every device near you, according to  Samsung NEXT Ventures   managing director Brendon Kim. During a conversation with MIT Technology Review’s Elizabeth Bramson-Boudreau at the  EmTech Digital conference  in San Francisco

Read how the power of AI and edge computing is critical to driving operational efficiencies and productivity gains.

Edge AI processes algorithms locally on devices on the edge of a local network. Here is how it is transforming computing.