RESEARCH TRIANGLE PARK – Delta Air Lines is moving to the public cloud thanks to a new deal inked with IBM.
As part of the multi-year agreement, Big Blue said it would transform the global airline’s computing environment to run on a hybrid cloud architecture built on Red Hat OpenShift.
IBM is also working with Delta teams to utilize the IBM Garage Methodology and IBM hybrid cloud software, such as CloudPaks, to modernize existing applications and co-create new solutions powering its transformation.
“This will help Delta drive greater software engineering productivity and result in an enhanced customer experience in the future,” the company said per its release.
IBM, which owns Raleigh-based Red Hat and operates one of its largest corporate campuses in RTP, already has an established relationship with Delta.
Early last year, the companies announced a multi-year collaborative effort via the IBM Q Network to explore the potential capabilities of quantum computing to transform experiences for airline customers and employees.
“This agreement expands our longstanding relationship with Delta Air Lines to help them accelerate and navigate their ambitious digital transformation journey,” said IBM’s senior vice president Mark Foster, in a statement. “This long-term project will apply the power of IBM’s hybrid cloud approach, enabling Delta to develop applications once and deploy them anywhere, integrate security across the breadth of their IT estate, and automate operations with management visibility.”
Separately, IBM researchers have designed what they claim to be the world’s first energy efficient AI accelerator chip built on high-performance seven-nanometer technology.
Ankur Agrawal and Kailash Gopalakrishnan, both staff members at IBM research, unveiled the four-core chip at the International Solid-State Circuits Virtual Conference this month, and have disclosed more details about the technology in a recent blog post.
Although still at the research stage, the accelerator chip is expected to be capable of supporting various AI models and of achieving “leading” edge power efficiency.
“Such energy efficient AI hardware accelerators could significantly increase compute horsepower, including in hybrid cloud environments, without requiring huge amounts of energy,” wrote Agrawal and Gopalakrishnan.