The New Stack Podcast

KubeFlow: Manage AI Workflows With Kubernetes

Episode Summary

Artificial intelligence may be at the peak of its hype cycle for modern businesses, but for the IT administrator it is still a headache, requiring software and processes that may entirely outside the normal sphere of operations. But help is on the way. At Kubecon + CloudNativeCon 2018 last month, David Aronchick introduced the first working version (0.1) of Kubeflow, software that packages the most popular AI and machine learning software so it can be easily run on the Kubernetes container orchestration engine. "We can't ask people to be experts in everything," Aronchick told the audience at Kubecon, in a keynote introducing the technology.  He noted that today's AI tools, such as Jupyter Notebooks or TensorFlow, have to be managed individually and often at great effort (the "bespoke" model). Kubeflow could rationalize this unruly set of software, but offering a common platform upon which they can all be based, and offered easily to the end-user, the data scientist. Watch on YouTube: https://youtu.be/S7qpvr2bZ2U

Episode Notes

Artificial intelligence may be at the peak of its hype cycle for modern businesses, but for the IT administrator it is still a headache, requiring software and processes that may entirely outside the normal sphere of operations. But help is on the way. At Kubecon + CloudNativeCon 2018 last month, David Aronchick introduced the first working version (0.1) of Kubeflow, software that packages the most popular AI and machine learning software so it can be easily run on the Kubernetes container orchestration engine.

"We can't ask people to be experts in everything," Aronchick told the audience at Kubecon, in a keynote introducing the technology.  He noted that today's AI tools, such as Jupyter Notebooks or TensorFlow, have to be managed individually and often at great effort (the "bespoke" model). Kubeflow could rationalize this unruly set of software, but offering a common platform upon which they can all be based, and offered easily to the end-user, the data scientist.

Watch on YouTube: https://youtu.be/S7qpvr2bZ2U