Since its general availability in 2024, Amazon Q Business (Amazon Q) has enabled independent software vendors (ISVs) to enhance their Software as a Service (SaaS) solutions through secure access to customers’ enterprise data by becoming Amazon Q Business data accessor. To find out more on data accessor, see this page.Continue Reading
This post was written with Stephen Coverdale and Alessandra Filice of Proofpoint. At the forefront of cybersecurity innovation, Proofpoint has redefined its professional services by integrating Amazon Q Business, a fully managed, generative AI powered assistant that you can configure to answer questions, provide summaries, generate content, and complete tasksContinue Reading
This post is co-written with Keith Beaudoin and Nicolas Bordeleau from Coveo. As generative AI transforms business operations, enterprises face a critical challenge: how can they help large language models (LLMs) provide accurate and trustworthy responses? Without reliable data foundations, these AI models can generate misleading or inaccurate responses, potentiallyContinue Reading
Training and deploying large AI models requires advanced distributed computing capabilities, but managing these distributed systems shouldn’t be complex for data scientists and machine learning (ML) practitioners. The newly released command line interface (CLI) and software development kit (SDK) for Amazon SageMaker HyperPod simplify how you can use the service’sContinue Reading
As organizations increasingly adopt foundation models (FMs) for their artificial intelligence and machine learning (AI/ML) workloads, managing large-scale inference operations efficiently becomes crucial. Amazon Bedrock supports two general types of large-scale inference patterns: real-time inference and batch inference for use cases that involve processing massive datasets where immediate results aren’tContinue Reading
Intelligent document processing (IDP) refers to the automated extraction, classification, and processing of data from various document formats—both structured and unstructured. Within the IDP landscape, key information extraction (KIE) serves as a fundamental component, enabling systems to identify and extract critical data points from documents with minimal human intervention. OrganizationsContinue Reading
Retrieval Augmented Generation (RAG) is a powerful approach for building generative AI applications by providing foundation models (FMs) access to additional, relevant data. This approach improves response accuracy and transparency while avoiding the potential cost and complexity of FM training or fine-tuning. Many customers use Amazon Bedrock Knowledge Bases toContinue Reading
In this post, we explore how natural language database analytics can revolutionize the way organizations interact with their structured data through the power of large language model (LLM) agents. Natural language interfaces to databases have long been a goal in data management. Agents enhance database analytics by breaking down complexContinue Reading
Today, Amazon SageMaker HyperPod is announcing a new one-click, validated cluster creation experience that accelerates setup and prevents common misconfigurations, so you can launch your distributed training and inference clusters complete with Slurm or Amazon Elastic Kubernetes Service (Amazon EKS) orchestration, Amazon Virtual Private Cloud (Amazon VPC) networking, high-performance storage,Continue Reading
This post was co-written with Nick Frichette and Vijay George from Datadog. As organizations increasingly adopt Amazon Bedrock for generative AI applications, protecting against misconfigurations that could lead to data leaks or unauthorized model access becomes critical. The AWS Generative AI Adoption Index, which surveyed 3,739 senior IT decision-makers acrossContinue Reading
