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A growing number of organizations want to take advantage of AI and machine learning, but finding the right tools and staff to do so can be difficult. Among other challenges, there’s a shortage of data scientists who can actually build machine learning models.
“There’s a huge talent gap for AI right now,” Rajen Sheth, director of product management for Cloud AI at Google, said to ZDNet. “It’s a very new area, and there aren’t a lot of people who know how to use it right now.”
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To address that challenge, Google Cloud is rolling out a set of new products aimed at maximizing the impact of a data scientist’s work. The first product, Kubeflow Pipelines, makes it easier for data scientists to coordinate with the other members of a team needed to actually bring a machine learning model into production. The second product, the AI Hub, serves as a marketplace where anyone from an organization can access machine learning components such as data sets or models.
“The vast majority of models that data scientists create never make it to production,” Sheth said. “You’re taking that really valuable asset of a data scientist and wasting it.”