Review: Google Cloud Vertex AI irons out ML platform wrinkles


When I reviewed the Google Cloud AI and Machine Learning Platform last November, I noted a few gaps despite Google having one of the largest machine learning stacks in the industry, and mentioned that too many of the services offered were still in beta test. I went on to say that nobody ever gets fired for choosing Google AI.

This May, Google shook up its AI/ML platform by introducing Vertex AI, which it says unifies and streamlines its AI and ML offerings. Specifically, Vertex AI is supposed to simplify the process of building and deploying machine learning models at scale and require fewer lines of code to train a model than other systems. The addition of Vertex AI doesn’t change the Google Cloud AI building blocks, such as the Vision API and the Cloud Natural Language API, or the AI Infrastructure offerings, such as Cloud GPUs and TPUs.

Google’s summary is that Vertex AI brings Google Cloud AutoML and Google Cloud AI and Machine Learning Platform together into a unified API, client library, and user interface. AutoML allows you to train models on image, tabular, text, and video datasets without writing code, while training in AI and Machine Learning Platform lets you run custom training code. With Vertex AI, both AutoML training and custom training are available options. Whichever option you choose for training, you can save models, deploy models, and request predictions with Vertex AI.

This integration of AutoML and custom training is a huge improvement over the old Google Cloud AI/ML platform. Because each service in the old platform was developed independently, there were cases where tagged data in one service couldn’t be reused by another service. That’s all fixed in Vertex AI.

The Google AI team spent two years reengineering its machine learning stack from the Google Cloud AI and Machine Learning Platform to Vertex AI. Now that the plumbing is done and the various services have been rebuilt using the new system, the Google AI team can work on improving and extending the services.

In this review I’ll explore Vertex AI with an eye towards understanding how it helps data scientists, how it improves Google’s AI capabilities, and how it compares with AWS’ and Azure’s AI and ML offerings.



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