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Summary: This is a summary of an article originally published by The New Stack. Read the full original article here →
Does data for artificial intelligence and machine learning need their own workflows and orchestration system? It does, according to Union.ai, which offers an open source solution called https://flyte.org/ that provides workflow and orchestration to fit the unique demands of data, not software. “The number one feedback we get from people who use orchestrators for machine learning is that they’re not made for AI workflows, machine learning workflows, because you’re forced to write https://thenewstack.io/from-yaml-engineer-to-yaml-herder/ code, you’re forced to do understand https://thenewstack.io/docker-versus-kubernetes-start-here/,” https://www.linkedin.com/in/steinmartin/, chief marketing officer and head of developer relations at https://www.union.ai/, told The New Stack. “You’re forced to really do things that machine learning engineers, data scientists and researchers don’t do.”
It is Union’s position that a good data and artificial intelligence orchestrator provides: Management and security: RBAC, data ownership, multitenancy, and scheduling
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