IBM unveiled new edge-computing services and solutions this week designed to help enterprises make the most of their transitions to 5G.
Called Vizi-AI, the devkit combines an Intel Atom-based SMARC computer module with the Intel distro of the OpenVINO toolkit and Adlink Edge software.
BrainChip, a provider of advanced neuromorphic computing technology, has collaborated with Socionext, which specializes in software-on-a-chip (SoC) solutions for video and imaging systems, to create a low-power platform for AI edge computing applications.
Chip designer Arm just announced two new processors with the potential to push AI into billions of small, power-and-memory-constrained devices.
Microsoft and AT&T offered an update on their 5G partnership late last month with the aim of using edge computing capabilities to "drive enterprise capabilities" for businesses around the world.
These numbers represent a 217 percent compound annual growth rate (CAGR), with 5G becoming what will be 8.9 percent of all "mobile device connections."
Described as “a vendor-neutral and code-first industry collaboration,” the new Edge Native Working Group was created to drive the evolution and broad adoption of open source software for edge computing.
Silver Peak, a leader in the software-defined wide-area networking (SD-WAN) space, announced updates to its Unity EdgeConnect SD-WAN edge platform that allow for massive scaling.
With edge computing increasingly appearing on lists of exciting, transformational technologies along with next-gen future-tech like artificial intelligence, quantum computing and so on, here's what industry experts are predicting for the space going forward.
Earlier in November Intel announced several new initiatives aimed at advancing artificial intelligence (AI) processing on the edge.
Dell Technologies and mobile service provider Orange recently announced a partnership to deal with new challenges coming with the advent of 5G wireless.
FogHorn recently announced the launch of Lightning Mobile, a new edge computing solution designed for industrial machine learning-focused mobile devices running Android.
The company says it created the board combination with Google's TensorFlow team specifically for artificial intelligence on the edge that focuses on gesture and voice recognition.