Red Hat seeks to be the platform for enterprise AI

Still, there are use cases in which a smaller model can work just fine – and be significantly faster and cheaper.

“I heard a couple of customers at the conference mention that the model is going to be good enough,” says IDC’s Rosen, who attended the Red Hat Summit. “One customer said, ‘A 70-billion-parameter model is not useful for us. We can’t handle it. We’re a health care organization and we don’t have the resources to run that bigger model.’”

Finally, the last missing piece of the AI puzzle is agents. Agents are a more recent development in the generative AI space, and are used to handle complex, multistep workflows that involve planning, delegation, testing, and iteration.

Microsoft’s AutoDev, for example, uses autonomous AI agents to create a fully automated software development framework. If Red Hat does support agents at some point, it would be in OpenShift AI, which is the MLOps platform, says Red Hat’s Katarki. “That’s where I would say your AI agents would live and be connected to do various kinds of agent workflows,” he says.