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Google’s new Vertex AI platform helps companies adopt ML faster

Google’s new Vertex AI platform helps companies adopt ML faster

The new managed platform aims to accelerate the deployment of enterprise AI.

This week Google Cloud announced the general availability of Vertex AI, a managed machine learning (ML) platform. Google says the new platform allows companies to accelerate the deployment and maintenance of artificial intelligence (AI) models.

Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms, Google claims. This enables data scientists and ML engineers across all levels of expertise the ability to implement Machine Learning Operations (MLOps) to efficiently build and manage ML projects throughout the entire development lifecycle.

They call the new platform MLOps. This is supposed to indicate that the new service is to machine learning what DevOps is to application development. The company says MLOps aims to add discipline to the development and deployment of machine learning models. It does this by defining processes that make machine learning development more reliable and productive, according to Google.

Reducing lag time and eliminating manual processes to speed up ML deployment

Today, data scientists grapple with the challenge of manually piecing together ML point solutions, Google says. This creates a lag time in model development and experimentation. The result is that very few models make it into production, they claim.

To tackle these challenges, Google says Vertex AI brings together the Google Cloud services for building ML under one unified UI and API. This in turn simplifies the process of building, training, and deploying machine learning models at scale. In this single environment, customers can move models from experimentation to production faster. They can more efficiently discover patterns and anomalies, Google says.

“We had two guiding lights while building Vertex AI: get data scientists and engineers out of the orchestration weeds, and create a industry-wide shift that would make everyone get serious about moving AI out of pilot purgatory and into full-scale production,” said Andrew Moore, vice president and general manager of Cloud AI and Industry Solutions at Google Cloud.

“We are very proud of what we came up with in this platform, as it enables serious deployments for a new generation of AI that will empower data scientists and engineers to do fulfilling and creative work.”