Red Hat AI/ML and MLOps Customer Success Stories

March 21, 2022Alex Handy1-minute read

How can MLOps improve your business outcomes?

Just a few years ago, the idea of integrating AI/ML into a business workflow was the stuff of fanciful startups and Silicon Valley dreams. But as the practice has begun to solidify as a legitimate business tool for large enterprises, AI/ML has become more than just a great way to spend compute resources. It's a path to surfacing better customer experiences, creating better outcomes and even to saving lives.

All of these benefits don't just arrive on the scene because an administrator installed some software, however. AI/ML at scale, and the the speed of business, is one of those technology spaces that has now merited its own term: MLOps.

While the fundamentals of MLOps are squarely rooted in DevOps, the actual implementation of these algorithms and the usage of them day to day falls onto the same teams that are tasked with implementing the digital transformation: the developers.

Enabling those developers requires robust systems of data management, ingestion, and processing, similar to classic business ETL work, but at significantly larger and faster scales. Additionally, the specific use case for each AI/ML application is unique and must be tailored to meet the individual needs. While the systems enabling MLOps can be reused for multiple projects, the actual AI/ML projects themselves can range from matching buyers to goods, to predicting medical conditions ahead of time.

Today, unlocking the business power of AI/ML is no longer an item on the future roadmap. It is a differentiator that can make the difference here and now. Just ask any of our customers> here's a whole swath of case studies and information about how businesses are using Red Hat products to operationalize AI/ML.

Red Hat MLOps Success Stories

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About the author

Alex Handy

Principal Product Marketing Manager

Red Hatter since 2018, technology historian and founder of The Museum of Art and Digital Entertainment. Two decades of journalism mixed with technology expertise, storytelling and oodles of computing experience from inception to ewaste recycling. I have taught or had my work used in classes at USF, SFSU, AAU, UC Law Hastings and Harvard Law.

I have worked with the EFF, Stanford, MIT, and Archive.org to brief the US Copyright Office and change US copyright law. We won multiple exemptions to the DMCA, accepted and implemented by the Librarian of Congress. My writings have appeared in Wired, Bloomberg, Make Magazine, SD Times, The Austin American Statesman, The Atlanta Journal Constitution and many other outlets.

I have been written about by the Wall Street Journal, The Washington Post, Wired and The Atlantic. I have been called "The Gertrude Stein of Video Games," an honor I accept, as I live less than a mile from her childhood home in Oakland, CA. I was project lead on the first successful institutional preservation and rebooting of the first massively multiplayer game, Habitat, for the C64, from 1986: https://neohabitat.org . I've consulted and collaborated with the NY MOMA, the Oakland Museum of California, Cisco, Semtech, Twilio, Game Developers Conference, NGNX, the Anti-Defamation League, the Library of Congress and the Oakland Public Library System on projects, contracts, and exhibitions.

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Red Hat AI/ML and MLOps Customer Success Stories

How can MLOps improve your business outcomes?

Red Hat MLOps Success Stories

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Alex Handy

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