A Technology Broker and Management Company Specializing in KM Systems
Favorite As companies are increasingly adopting machine learning (ML) for their mainstream enterprise applications, more of their business decisions are influenced by ML models. As a result of this, having simplified access control and enhanced transparency across all your ML models makes it easier to validate that your models are
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Shared by AWS Machine Learning December 1, 2022
Favorite Amazon SageMaker now allows you to compare the performance of a new version of a model serving stack with the currently deployed version prior to a full production rollout using a deployment safety practice known as shadow testing. Shadow testing can help you identify potential configuration errors and performance
Read More Shared by AWS Machine Learning December 1, 2022
Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). It provides a single, web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models. Within an Amazon SageMaker Domain, users can provision a personal
Read More Shared by AWS Machine Learning December 1, 2022
Favorite Recently, the Amazon SageMaker Studio launched an easy way to run notebooks as batch jobs that can run on a recurring schedule. Amazon SageMaker Studio Lab also supports this feature, enabling you to run notebooks that you develop in SageMaker Studio Lab in your AWS account. This enables you
Read More Shared by AWS Machine Learning December 1, 2022
Favorite Artificial intelligence (AI) and machine learning (ML) are some of the most transformative technologies we will encounter in our generation—to tackle business and societal problems, improve customer experiences, and spur innovation. Along with the widespread use and growing scale of AI comes the recognition that we must all build
Read More Shared by AWS Machine Learning November 30, 2022
Favorite Today we are excited to announce that AI21 Jurassic-1 (J1) foundation models are available for customers using Amazon SageMaker. Jurassic-1 models are highly versatile, capable of both human-like text generation, as well as solving complex tasks such as question answering, text classification, and many others. You can easily try
Read More Shared by AWS Machine Learning November 30, 2022
Favorite Amazon SageMaker Autopilot, a low-code machine learning (ML) service that automatically builds, trains, and tunes the best ML models based on tabular data, is now integrated with Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for ML. This enables the automation of an end-to-end
Read More Shared by AWS Machine Learning November 30, 2022
Favorite We’re thrilled to announce that Stability AI has selected AWS as its preferred cloud provider to power its state-of-the-art AI models for image, language, audio, video, and 3D content generation. Stability AI is a community-driven, open-source artificial intelligence (AI) company developing breakthrough technologies. With Amazon SageMaker, Stability AI will
Read More Shared by AWS Machine Learning November 30, 2022
Favorite Over the last 5 years, artificial intelligence (AI) and machine learning (ML) have evolved from a niche activity to a rapidly growing mainstream endeavor. Today, more than 100,000 customers across numerous industries rely on AWS for ML and AI initiatives that infuse AI into a broad range of business
Read More Shared by AWS Machine Learning November 29, 2022
Favorite Amazon Rekognition offers pre-trained and customizable computer vision capabilities to extract information and insights from images and videos. One such capability is Amazon Rekognition Labels, which detects objects, scenes, actions, and concepts in images. Customers such as Synchronoss, Shutterstock, and Nomad Media use Amazon Rekognition Labels to automatically add
Read More Shared by AWS Machine Learning November 28, 2022