UPDATED 14:43 EDT / MAY 23 2023

AI

Ansible Lightspeed taps LLMs and foundation models for AI-powered IT automation

Open source has been a boon for the digital enterprise. For one, it birthed the Ansible Automation Platform for software provisioning, configuration management and application deployment — among other things.

But as it evolves with the times, what other capabilities are being worked into the Ansible suite? And which technologies will spearhead them?

“Lightspeed is about a two-year project that we’ve been working on in conjunction with the IBM Research team,” said Tom Anderson (pictured, right), vice president and general manager of the Ansible Business Unit at Red Hat Inc. “They brought the expertise on large language models and foundation models, and we brought the expertise on Ansible, obviously in automation. We’re bringing those two things together to apply generative AI to a very specific use case, which is Ansible Automation for the enterprise.”

Anderson and Rich Henshall (left), director of Ansible product management at Red Hat, spoke with theCUBE industry analysts John Furrier and Paul Gillin at Red Hat Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the signals emerging from Ansible on its trajectory moving forward. (* Disclosure below.)

Unlocking the next level of operational efficiency

Just announced and with a release date later this year, Lightspeed takes two of AI’s main qualities — shaving time spent on repeatable tasks and its trainability — and lends them to Ansible’s IT automation workflows.

“We wanted to help generate more efficiency and value from what people do to give them more time for more of what they’re able to do,” Henshall said. “I think a big difference now with the AI-driven change is moving away from the idea of replacing people to that of supercharging them and pairing that with the ability to actually train something to specifically help around a set number of tasks.”

In enabling human intelligence, AI will reduce the entry barrier into the Ansible ecosystem for end users from a domain expertise standpoint, Anderson added.

“If I want to automate a storage subsystem with Ansible, I need to know the Ansible language to write a playbook to do it,” he explained. “I also need to know the storage subsystem and the interface of what I want to do. If we can lower the Ansible bar for domain expertise over time, then we’ll start bringing more and more people into the family.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Red Hat Summit:

(* Disclosure: Red Hat Inc. sponsored this segment of theCUBE. Neither Red Hat nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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