Intel, which has been flying underneath the radar in the "edge" computing sector, is trying to become player in the edge market with strategic moves and key products.

The growth of IoT devices, the development and rollout of 5G networks, and advancements in AI have all come together to enable the "edge." The edge is a broad term to refer to all the data endpoints that exist outside of the datacenter. So we are talking about devices such as smartphones, voice assistants and PCs, but also IoT devices and sensors gathering information out in the world.

Until recently, the the data gathered from these “edge” devices had to be routed back to the cloud and/or datacenter in order to be and processed for insights, but organizations are looking to perform these functions on physical compute structure, at or near the data source itself. This concept called is “edge computing.” Within edge computing, there is the on-premise edge (when a network operator runs virtualized environments across an on-prem, distributed edge architecture), and the network edge (the point where networks connect to the Internet and other third-party networks).

Intel is offering a holistic portfolio around for enabling edge compute. Through strategic acquisitions and internal development, the company has amassed a portfolio with processors, accelerators, SoCs, VPUs, and FPGAs geared specifically towards compute at the networking and on-prem edge. Furthermore,Intel is offering open source toolkits, fostering a developer and partner community to leverage this technology.

Intel recently updated its 2nd Xeon Scalable Platform, bringing higher core counts, larger cache sizes, and higher processor frequency to the table. At the same time, the company unveiled a significant expansion of its 5G networking infrastructure offerings, including the new Atom P5900 Intel architecture-based 10nm SoC for wireless base stations. Intel has set the ambitious goal of being the number one provider of silicon for 5G base stations come the year 2021.

In terms of AI accelerators, Intel is using the technology and resources it got from its recent acquisition of Habana Labs. Intelplans to replace its Nervana chips.

In the computer vision segment, Intel acquired Movidius in 2016. The company’s Myriad VPUs seek to enable on-device, low power deep learning and visual data processing for applications such as security cameras other IoT devices. Intel also has its Arria line of FPGAs and SoCs, designed to deliver high performance at lower power for applications spanning automotive, datacenter, military, communications and more. In addition, the integrated AI acceleration is available today on Intel Xeon Scalable and that platform is widely used for AI inference today for data centric applications.

Intel is also offering developers the free OpenVINO developer toolkit, which focuses on edge AI acceleration. The OpenNESS toolkit focuses on fostering open collaboration in the realm of the network and enterprise edge, with the specific goal of enabling 5G development and deployment. Intel’s Open Visual Cloud software stack seeks to do the same in realm of media, graphics and analytics, featuring end-to-end sample pipelines for developers. Intel says Open Visual Cloud is optimized for cloud native deployment and designed for commercial off-the-shelf x86 architecture as well as Intel’s many accelerators.

For the network edge, Intel's partners include Lenovo, Red Hat, Advantech, Caswell, Inventec, Lanner, Nexcom, World Wide Technology, Ericsson, ZTE, Verizon, Vodafone, Nokia, China Telecom and many more. For on-prem edge computing, Intel is working with the likes of Foxconn and QNAP.