Open Source AI Definition – Weekly update April 8

Favorite Seeking document reviewers for OpenCV This is your final opportunity to register for the review of licenses provided by OpenCV. Join us for our upcoming phase, where we meticulously compare various systems’ documentation against our latest definition to test compatibility. For more information, check the forum Action on the

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Shared by voicesofopensource April 8, 2024

OSI’s Response to NTIA ‘Dual Use’ RFC 3.27.2024

Favorite March 27, 2024 Mr. Bertram LeeNational Telecommunications and Information Administration (NTIA)U.S. Department of Commerce1401 Constitution Avenue NWWashington, DC 20230 RE: [Docket Number 240216-0052] Dual Use Foundation Artificial Intelligence Models with Widely Available Model Weights Dear Mr. Lee: The Open Source Initiative (“OSI”) appreciates the opportunity to provide our views

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Shared by voicesofopensource April 2, 2024

Open Source AI Definition – Weekly update April 2

Favorite Seeking document reviewers for Pythia and OpenCV We are now in the process of reviewing legal documents to check the compatibility with the version 0.0.6 definition of open-source AI, specifically for Pythia and OpenCV. Click here to see the past activities of the four working groups To get involved,

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Shared by voicesofopensource April 1, 2024

Generative AI to quantify uncertainty in weather forecasting

Favorite Posted by Lizao (Larry) Li, Software Engineer, and Rob Carver, Research Scientist, Google Research Accurate weather forecasts can have a direct impact on people’s lives, from helping make routine decisions, like what to pack for a day’s activities, to informing urgent actions, for example, protecting people in the face

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Shared by Google AI Technology March 29, 2024

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