AWS Machine Learning Blog This post was co-written with Varun Kumar from Tealium Retrieval Augmented Generation (RAG) pipelines are popular for generating domain-specific outputs based on external data that’s fed in as part of the context. However, there are challenges with evaluating and improving such systems. Two open-source libraries, Ragas (a library for RAG evaluation) […]Continue reading

AWS Machine Learning Blog EBSCOlearning offers corporate learning and educational and career development products and services for businesses, educational institutions, and workforce development organizations. As a division of EBSCO Information Services, EBSCOlearning is committed to enhancing professional development and educational skills. In this post, we illustrate how EBSCOlearning partnered with AWS Generative AI Innovation Center […]Continue reading

AWS Machine Learning Blog Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon SageMaker JumpStart. You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access […]Continue reading

AWS Machine Learning Blog In this post, we demonstrate the potential of large language model (LLM) debates using a supervised dataset with ground truth. In this LLM debate, we have two debater LLMs, each one taking one side of an argument and defending it based on the previous arguments for N(=3) rounds. The arguments are […]Continue reading

AWS Machine Learning Blog Microsoft Teams is an enterprise collaboration tool that allows you to build a unified workspace for real-time collaboration and communication, meetings, and file and application sharing. You can exchange and store valuable organizational knowledge within Microsoft Teams. Microsoft Teams data is often siloed across different teams, channels, and chats, making it […]Continue reading

AWS Machine Learning Blog Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Evaluation, on […]Continue reading

AWS Machine Learning Blog Professionals in a wide variety of industries have adopted digital video conferencing tools as part of their regular meetings with suppliers, colleagues, and customers. These meetings often involve exchanging information and discussing actions that one or more parties must take after the session. The traditional way to make sure information and […]Continue reading

AWS Machine Learning Blog Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications […]Continue reading

AWS Machine Learning Blog Enterprises in industries like manufacturing, finance, and healthcare are inundated with a constant flow of documents—from financial reports and contracts to patient records and supply chain documents. Historically, processing and extracting insights from these unstructured data sources has been a manual, time-consuming, and error-prone task. However, the rise of intelligent document […]Continue reading

AWS Machine Learning Blog This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. A multi-account strategy is essential not only for improving governance […]Continue reading