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Favorite What would it be like if organisations treated their money the way they treat their knowledge? Hands counting $100 bills, by Hloom Templates on Flickr This is a simple thought experiment, which you can use with your senior managers to get them to think differently about knowledge. We know
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Shared by Nick Milton October 31, 2022
Favorite Transcript from October 11th Deep Dive: AI Business panel Stefano Maffulli: Then welcome everyone officially…. The post Exploring the business side of AI first appeared on Voices of Open Source. Click Here to View Original Source (opensource.org)
Favorite With environmental, social, and governance (ESG) initiatives becoming more important for companies, our customer, one of Greater China region’s top convenience store chains, has been seeking a solution to reduce food waste (currently over $3.5 million USD per year). Doing so will allow them to not only realize substantial
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Shared by AWS Machine Learning October 27, 2022
Favorite This post is co-written with Chaim Rand from Mobileye. Certain machine learning (ML) workloads, such as training computer vision models or reinforcement learning, often involve combining the GPU- or accelerator-intensive task of neural network model training with the CPU-intensive task of data preprocessing, like image augmentation. When both types
Read More Shared by AWS Machine Learning October 27, 2022
Favorite You can find the OSI in Downtown Raleigh, North Carolina October 31st through November 2nd… The post We are headed to All Things Open 2022 first appeared on Voices of Open Source. Click Here to View Original Source (opensource.org)
Favorite In just 5 years, tens of thousands of customers have tapped Amazon SageMaker to create millions of models, train models with billions of parameters, and generate hundreds of billions of monthly predictions. The seeds of a machine learning (ML) paradigm shift were there for decades, but with the ready
Read More Shared by AWS Machine Learning October 26, 2022
Favorite Monitoring machine learning (ML) predictions can help improve the quality of deployed models. Capturing the data from inferences made in production can enable you to monitor your deployed models and detect deviations in model quality. Early and proactive detection of these deviations enables you to take corrective actions, such
Read More Shared by AWS Machine Learning October 26, 2022
Favorite Amazon SageMaker Serverless Inference is a purpose-built inference option that makes it easy for you to deploy and scale machine learning (ML) models. It provides a pay-per-use model, which is ideal for services where endpoint invocations are infrequent and unpredictable. Unlike a real-time hosting endpoint, which is backed by
Read More Shared by AWS Machine Learning October 26, 2022
Favorite Today Amazon SageMaker announced the support of Grid search for automatic model tuning, providing users with an additional strategy to find the best hyperparameter configuration for your model. Amazon SageMaker automatic model tuning finds the best version of a model by running many training jobs on your dataset using
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Favorite Posted by Kedem Snir, Software Engineer, and Gal Elidan, Senior Staff Research Scientist, Google Research Whether it’s a professional honing their skills or a child learning to read, coaches and educators play a key role in assessing the learner’s answer to a question in a given context and guiding
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Shared by Google AI Technology October 26, 2022