Civo Announces Launch of New Machine Learning Managed Service

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Civo, the cloud native service provider, has announced its new Machine Learning (ML) managed service, “Kubeflow as a Service” aimed at improving the developer experience and reducing the resources and time required to gain insights from ML algorithms.

The surrounding infrastructure required to support ML is both vast and complex. Many organizations spend the majority of their time and resources dedicated to ML on setting up infrastructure components, such as process management tools, data verification, and machine resource management. Indeed, Gartner research shows that only 53% of AI projects make it from prototype to production. While infrastructure is still a requirement, developers would rather have easy access to usable insights of value.

Civo aims to combat this by running these components as an ML managed service, supporting the tools and frameworks most required by developers using ML. By handling the heavy lifting, Civo will make ML accessible to organizations of all sizes. Many smaller organizations are priced out of ML due to the economies of scale required to build the surrounding operations and infrastructure.

“Civo’s ethos of fairly priced simplicity represents a new frontier for the Machine Learning landscape,” said Josh Mesout, Chief Innovation Officer. “Many big tech players are focusing their effort on building tools they think developers want. In reality, most developers have access to the tools already, they just want them to run more efficiently and not have to spend the majority of the time preparing the infrastructure and setting up tooling. Civo’s open source philosophy allows us to focus our efforts where they matter most, providing the right support for the ML tools most in demand whilst giving the end users a greater arsenal of tools at their disposal. Technological landscapes, either cloud or ML, ultimately evolve when they are democratized and are easily accessible to all. We hope to provide every developer looking to use ML with the platform they require to capitalize on its benefits, and in turn, drive the technology forward.”

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