Ex-Red Hat CEO Paul Cormier: Open Source and AI Share History, Challenges

The Red Hat Summit in Denver last week focused on the links between open source and artificial intelligence (AI). A few blocks away, Linux pioneer and former Red Hat CEO Paul Cormier took that topic to Boomi World.

Cormier, who is Red Hat chairman emeritus and sits on Boomi’s board, compared AI today with where open-source Linux stood when he joined Red Hat in 2001. He said open source has led directly to AI, and now AI enterprise adoption faces the same challenges that open source and Linux had to overcome.

“There are so many parallels in the Linux world to the AI world. It’s all sort of built on each other,” Cormier said during a conversation with Boomi CEO Steve Lucas. “Everybody thinks this stuff happens overnight, but it’s been 23 years. We’ve really driven up to this point, and now some of the things in AI are going to have to be invented just like we did in the Linux world for enterprises to be able to consume it.”

Cormier traced a path from open source to Linux to cloud to AI.

“Of course, I'm biased in the Linux world where I spent the last 23 years of my life,” Cormier said. “But it all sort of started with that. Linux wouldn't have happened without open source. Cloud wouldn't happen without Linux being accepted and thriving in the enterprise. And things like containers wouldn't have happened without open-source Linux. How would we have done containers across a hybrid cloud world with a Microsoft operating system that you couldn’t get at? AI couldn’t have happened without all those other things.”

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He pointed out that before open-source development, large vendors such as Cormier’s one-time employer Digital Equipment Corporation (DEC) had proprietary stacks that were silos — and that stifled innovation.

“The innovation with open source just exploded,” Cormier said. “But the biggest problem with it is, how do mere mortals consume it, especially in the enterprise where things like security and reliability are so important? I think we all underestimate how long it takes to get these technologies into the real world. The enterprise is a very unforgiving place. There are many pieces of the application base that they just don't want to touch. The mainframe is still alive, and it’s because those types of applications are too painful to move.”

Paul Cormier: AI Deployment Faces Complex Challenges

Accelerated innovation has brought more complexity, and Cormier sees that complexity as the root of AI’s challenge in the enterprise.

“There's still a lot of work to be done on the consumption of AI laid on top of this complex hybrid model,” he said.

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Cormier said it took six years for Red Hat Enterprise Linux (RHEL) and 10 years for OpenShift to become profitable. He said he expects the next few years will be spent “tying all these things together, making them work, making them consumable. Open source has driven innovation because it gets such a wide swath of people that are contributing to a technical problem. But that technical problem is only in the lab. It's when you start to deploy this out in the enterprise that you really find the big problems.

“I look at these pieces, whether it be open source, Linux, hybrid cloud, integration, AI, I look at these as really cool, separate pieces of innovation," he continued. "Now we have to make it work all together. And as we make it work all together, each one will get better working all together, and each one will get individually better.”

Cormier said vendors will build AI-driven automation into products because “to try to bolt on an automation engine on the back end for every application just wouldn't make sense. And by the way, the customers are probably going to have to train the AI model to deal with the specifics for that transaction based on the factors that are coming into play for that transaction.”

Cormier said software companies are experimenting with AI, much like they experimented with open source in the early days.

“That experimentation will go on for a while and then you'll see things coalesce,” he said. “I think there will be very few companies that are really AI companies, but every software company will be using AI.”

His advice to software companies: Form an AI strategy now, and invest in and experiment with the technology.

“I see so many software companies that don't have a strategy,” he said. “And this is too complex to just take it one day at a time. You really have to really think of what your strategy is, what you're trying to accomplish, and then start the experimentation. There’s always that bottleneck that’s going to drive everything else. And if you don’t understand that, you’re going to inevitably start in the wrong place.”