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OctoML CEO: MLOps needs to step aside for DevOps

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New tools from the Apache TVM inventors promote what are called “intelligent applications,” programs that embed machine learning as functions.

Metaverse: Momentum is building, but companies are still staying cautious Read now “I personally think that if we do this right, we don’t need ML Ops,” says Luis Ceze, OctoML CEO, regarding the company’s bid to make deployment of machine learning just another function of the DevOps software process. The field of MLOps has arisen as a way to get ahold of the complexity of industrial uses of artificial intelligence.

That effort has so far failed, says Luis Ceze, who is co-founder and CEO of startup OctoML, which develops tools to automate machine learning.

“It’s still pretty early to turn ML into a common practice,” Ceze told ZDNet in an interview via Zoom.

“That’s why I’m a critic of MLOps: we’re giving a name for something that’s not very well defined, and there’s something that’s very well defined, called DevOps, that’s a very well defined process of taking software to production, and I think that we should be using that.”

“I personally think that if we do this right, we don’t need ML Ops,” Ceze said.”We can just use DevOps, but for that […]

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