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

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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

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Shared by AWS Machine Learning September 8, 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

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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

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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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Shared by AWS Machine Learning 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

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Shared by AWS Machine Learning September 6, 2023

Favorite Today, we are excited to announce the capability to fine-tune Llama 2 models by Meta using Amazon SageMaker JumpStart. The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. Fine-tuned

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Shared by AWS Machine Learning September 6, 2023

Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). With Amazon Kendra, you can easily aggregate content from a variety of content repositories into an index that lets you quickly search all your enterprise data and find the most accurate answer. Adobe Experience Manager (AEM) is

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Shared by AWS Machine Learning September 6, 2023

Favorite Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. It’s powered by large language models (LLMs) that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). With the advent of these

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Shared by AWS Machine Learning September 6, 2023

Favorite The success of generative AI applications across a wide range of industries has attracted the attention and interest of companies worldwide who are looking to reproduce and surpass the achievements of competitors or solve new and exciting use cases. These customers are looking into foundation models, such as TII

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Shared by AWS Machine Learning September 5, 2023