Machine learning is notorious for reinforcing existing bias, but it can also be used to counteract it. Primer developed an ML system called Quicksilver that identifies and describes notable women of science who are missing from Wikipedia. It takes millions of news documents as input and generates first-draft biographical articles.
Kubeflow made it far easier to scale and maintain this system. Come learn how Primer partnered with Google to migrate to GCP in order to:
* Deploy the same code to multiple physical environments
* Affordably scale an existing ML app using Kubeflow with auto-provisioning
* Continuously train hundreds of thousands of models using Kubeflow pipelines
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Speaker(s): John Bohannon, Michelle Casbon
Session ID: MLAI206
Publisher: Google Cloud
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