Google launches ML Hub to help AI developers train and deploy their models


At its I/O developers conference, Google today announced its new ML Hub, a one-stop destination for developers who want to get more guidance on how to train and deploy their ML models, no matter whether they are in the early stages of their AI career or seasoned professionals.

“We talk about this concept of democratizing machine learning and really making it more accessible, so something that we’re pretty excited about is Google has a bit of a sprawling set of open-source technologies that cover many different assets […] We want to make it much, much easier to understand how they fit together and actually help folks get up and running,” said Alex Spinelli, Google’s VP  of product management for machine learning. The idea here, he said, is to give developers a landing page where they can basically look at what kind of model they want to generate, based on the data they have, and then get step-by-step directions for how to think about deploying those models.

The company is launching this platform with an initial set of toolkits that covers a set of common use cases, with plans to regularly update these and launch new ones in a steady cadence. Some of the early toolkits, for example, can help developers build text classifiers using Keras or take large language models and run them on Android with Keras and TensorFlow Lite.

As Spinelli rightly noted, generative AI may be getting all of the hype right now, but machine learning is a large space that covers a wide range of types of models and technology.

“There’s amazing things going on in computer vision and facial recognition and recommendation systems and relevance ranking of content and those kinds of things — clustering content — all this stuff. We really don’t want to leave anything behind and want to make sure we can actually help developers and researchers have the right set of tools and technologies for their particular use case,” Spinelli noted.

He noted that a lot of the focus here is on open source — and while developers can take these technologies and run them on-premises or in any cloud, these new toolkits will also provide what he called a “glide path into the Google cloud.” But as Spinelli stressed, there is no lock-in here. “There is a fundamental commitment that this is open source that you can use anywhere,” he said.



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