Double down on the key role Red Hat plays in AI training and enablement.

We don’t care if it’s a machine learning model, a convolutional neural network, a foundation model, et cetera. We can help you train and we can help you refine. Then we can put that model at the edge, which is where we’ve had a lot of focus, so you can ask it questions as close to your customer as you want.

I’m hoping that will shift us from having these big data science experiments work more. Some of them are great, but they can never get to production on it. A lot of development projects can never get to production.

Our goal is ‘How do we shorten that cycle with AI?’ That’s sort of where we play, is in that plumbing space. We help move models to production. We help train them or find models and get them to the edge, but we don’t really care about what type of model it is.

So we get to be excited watching OpenAI work, Hugging Face’s work, IBM, et cetera. It’s great innovation that, obviously, we have to have the stacks to support them, but that’s our world. We know that world.