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HomeGlobalGoogle launches fully managed cloud ML platform Vertex AI – AI-Global

Google launches fully managed cloud ML platform Vertex AI – AI-Global

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Google Cloud has launched Vertex AI, a fully managed cloud platform that simplifies the utilisation and maintenance of machine learning models.

Vertex was announced during this year’s virtual I/O developer conference and somewhat deviates from Google’s tradition of using its keynote to focus more on updates to its mobile and web development solutions. Google introduced the platform during the keynote shows how important the company believes it to be for a wide range of developers.

According to Google,  using Vertex enables models to be trained with up to 80 percent fewer lines of code when compared to competing platforms.

Bradley Shimmin, Chief Analyst for AI Platforms, Analytics, and Data Management at Omdia, said: Data science practitioners hoping to put AI to work across the enterprise aren’t looking to wrangle tooling. Rather, they want tooling that can tame the ML lifecycle. Unfortunately, that is no small order.

It takes a supportive infrastructure capable of unifying the user experience, plying AI itself as a supportive guide, and putting data at the very heart of the process — all while encouraging the flexible adoption of diverse technologies.”

Vertex brings together Google Cloud’s AI solutions into a single environment where models can go from experimentation to production.

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

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.”

Vertex provides access to Google’s MLOps toolkit which it uses internally for workloads involving computer vision, conversation, and language.

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