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 activity and mentioned that too many of the labors offered were quiet 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 facilitate the process of edifice and deploying machine learning standards at layer and demand fewer lines of code to train a standard than other systems. The accession of Vertex AI doesnt change the Google Cloud AI edifice blocks such as the Vision API and the Cloud Natural Language API or the AI Infrastructure offerings such as Cloud GPUs and TPUs.

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Googles summary is that Vertex AI brings Google Cloud AutoML and Google Cloud AI and Machine Learning Platform unitedly into a unified API client library and user interface. AutoML allows you to train standards on image tabular text and video datasets without writing code while training in AI and Machine Learning Platform lets you run manner training code. With Vertex AI both AutoML training and manner training are useful discretions. Whichever discretion you select for training you can save standards deploy standards and request predictions with Vertex AI.

This integration of AutoML and manner training is a huge advancement over the old Google Cloud AI/ML platform. Because each labor in the old platform was developed independently there were cases where tagged data in one labor couldnt be reused by another labor. Thats all fixed in Vertex AI.