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Favorite Posted by Edith Cohen and Uri Stemmer, Research Scientists, Google Research Differential privacy (DP) is a rigorous mathematical definition of privacy. DP algorithms are randomized to protect user data by ensuring that the probability of any particular output is nearly unchanged when a data point is added or removed.
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Shared by Google AI Technology September 8, 2023
Favorite This post is co-written with Travis Bronson, and Brian L Wilkerson from Duke Energy Machine learning (ML) is transforming every industry, process, and business, but the path to success is not always straightforward. In this blog post, we demonstrate how Duke Energy, a Fortune 150 company headquartered in Charlotte,
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Shared by AWS Machine Learning September 8, 2023
Favorite Digital publishers are continuously looking for ways to streamline and automate their media workflows in order to generate and publish new content as rapidly as they can. Publishers can have repositories containing millions of images and in order to save money, they need to be able to reuse these
Read More Shared by AWS Machine Learning September 8, 2023
Favorite For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. However, traditional methods of storing and searching for documents can be time-consuming and often result in a large effort
Read More Shared by AWS Machine Learning September 8, 2023
Favorite Posted by Shantanu Shahane, Software Engineer, and Matthias Ihme, Research Scientist, Athena Team Turbulence is ubiquitous in environmental and engineering fluid flows, and is encountered routinely in everyday life. A better understanding of these turbulent processes could provide valuable insights across a variety of research areas — improving the
Read More Shared by Google AI Technology September 7, 2023
Favorite Amazon SageMaker Pipelines is a fully managed AWS service for building and orchestrating machine learning (ML) workflows. SageMaker Pipelines offers ML application developers the ability to orchestrate different steps of the ML workflow, including data loading, data transformation, training, tuning, and deployment. You can use SageMaker Pipelines to orchestrate
Read More Shared by AWS Machine Learning September 7, 2023
Favorite In February 2022, Amazon Web Services added support for NVIDIA GPU metrics in Amazon CloudWatch, making it possible to push metrics from the Amazon CloudWatch Agent to Amazon CloudWatch and monitor your code for optimal GPU utilization. Since then, this feature has been integrated into many of our managed
Read More Shared by AWS Machine Learning September 7, 2023
Favorite Efficient control policies enable industrial companies to increase their profitability by maximizing productivity while reducing unscheduled downtime and energy consumption. Finding optimal control policies is a complex task because physical systems, such as chemical reactors and wind turbines, are often hard to model and because drift in process dynamics
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Favorite A license-review project has been underway with the goal of creating a systematic and well-ordered database of all the licenses that have been submitted to OSI for approval since the time of the organization’s founding. Giulia Dellanoce was brought on as an intern to complete this Approval Registry project,
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Shared by voicesofopensource September 7, 2023
Favorite Multi-model endpoints (MMEs) are a powerful feature of Amazon SageMaker designed to simplify the deployment and operation of machine learning (ML) models. With MMEs, you can host multiple models on a single serving container and host all the models behind a single endpoint. The SageMaker platform automatically manages the
Read More Shared by AWS Machine Learning September 6, 2023