Technology 2 min read

Google Launches AI Platform for End-to-End Model Development



During the Google Cloud Next 2019 conference in San Francisco yesterday, Google announced the release of its new end-to-end service for AI model development, the AI Platform. The new tool is reportedly part of the tech giant’s plan to democratize artificial intelligence and machine learning with the help of pre-built models and user-friendly services that developers can use.

According to Google:

“AI Platform makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively. From data engineering to “no lock-in” flexibility, AI Platform’s integrated tool chain helps you build and run your own machine learning applications.”

The new service reportedly supports Google’s open-source platform, Kubeflow. This will allow developers to build custom machine learning pipelines that they can run on-premises or even on Google Cloud without the need to make huge changes to the code.

Aside from that, AI and ML model developers will also have access to Google’s most advanced AI technology like TPUs, TensorFlow, and TFX tools as soon as the AI applications were deployed to production.

The AI Platform

The idea behind the AI Platform is to give developers and data scientists end-to-end service while they build, test, and deploy their models.

Google will make this possible by putting together a number of its old and new products together for pulling and labeling data, using existing classification, recognizing objects, extracting entity models, or using AutoML and Cloud ML engine for training and deploying AI models.

Andrew Moore, Google Cloud chief AI Scientist, was quoted as saying:

“The AI Platform is this place where, if you are taking this terrifying journey from a journeyman idea of how you can use AI in your enterprise, all the way through launch and a safe, reliable deployment, the AI Platform help you move between each of these stages in a safe way so that you can start with exploratory data analysis, start to build models using your data scientists, decide that you want to use this specific model, and then with essentially one click be able to deploy it.”

The AI Platform will operate in the Cloud Console and will be able to handle both batch and streaming data. Developers can also use Google Cloud’s BigQuery to import data.

Read More: ENDGAME: How Google Stadia Will Transform 5 Industries

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Chelle Fuertes

Chelle is the Product Management Lead at INK. She's an experienced SEO professional as well as UX researcher and designer. She enjoys traveling and spending time anywhere near the sea with her family and friends.

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    Lisa Gaillard April 13 at 1:14 am GMT

    Generally simplify everything, impressive!

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