November 13, 2018

Google Cloud unveils AI Hub to simplify machine learning deployment

The launch seeks to simplify and speed up customer’s ability to adopt AI techniques by introducing AI Hub and Kubeflow Pipelines.

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AI Hub

Tech mogul Google Cloud have launched an AI Hub to help customers design, launch and keep track of their machine learning (ML) algorithms. With this launch, Google seeks to accelerate customer’s ability to adopt AI techniques and help them manage, compose and deploy machine learning workflows by leveraging Kubeflow Pipelines.

According to Google Cloud, enterprises leveraging AI and machine learning on the cloud need a platform to collaborate and build products. They say that such platforms need private sharing controls as well as simplified access to adapt to the platform easily.

By launching the AI Hub, Google Cloud say that they will allow both engineers and data scientists to store components like pipelines, notebooks and TensorFlow modules on a secure platform to facilitate unified collaboration. They also believe that users will be able to take help of these resources and put them into production to build products and assets for their enterprises without any hiccups.

Speaking about this in detail, Hussein Mehanna, Engineering Director for the Cloud ML Platform, commented:

Our goal is to put AI in reach of all businesses. But doing that means lowering the barriers to entry. That’s why we build all our AI offerings with three ideas in mind: make them simple, so more enterprises can adopt them, make them useful to the widest range of organisations, and make them fast, so businesses can iterate and succeed more quickly.

Google claim that they expect early adopters from various industries with sizeable AI and ML functions to step up their game with the AI Hub. They also say that with Kubeflow Pipelines, enterprises can experiment with their AI models before executing them thoroughly.

Mehanna continued:

Organisations like Cisco and NVIDIA are among the key contributors to this open source project and are collaborating with us closely to adopt Kubeflow pipelines. NVIDIA is already underway integrating RAPIDS, a new suite of open source data science libraries, into Kubeflow.

It will be interesting to see how Google Cloud makes the most of this launch, following their unveiling of an AI Lab with Atos in the U.K. last month.

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