AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks

Favorite Posted by Urs Köster, Software Engineer, Google Research Time series problems are ubiquitous, from forecasting weather and traffic patterns to understanding economic trends. Bayesian approaches start with an assumption about the data’s patterns (prior probability), collecting evidence (e.g., new time series data), and continuously updating that assumption to form

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Shared by Google AI Technology March 28, 2024

Enabling large-scale health studies for the research community

Favorite Posted by Chintan Ghate, Software Engineer, and Diana Mincu, Research Engineer, Google Research As consumer technologies like fitness trackers and mobile phones become more widely used for health-related data collection, so does the opportunity to leverage these data pathways to study and advance our understanding of medical conditions. We

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Shared by Google AI Technology November 10, 2023

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon

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Shared by AWS Machine Learning August 3, 2023