AWSML

Organizations today deal with vast amounts of unstructured data in various formats including documents, images, audio files, and video files. Often these documents are quite large, creating significant challenges such as slower processing times and increased storage costs. Extracting meaningful insights from these diverse formats in the past required complex processing pipelines and significant development … Read more

Foundation models (FMs) have revolutionised AI capabilities, but adopting them for specific business needs can be challenging. Organizations often struggle with balancing model performance, cost-efficiency, and the need for domain-specific knowledge. This blog post explores three powerful techniques for tailoring FMs to your unique requirements: Retrieval Augmented Generation (RAG), fine-tuning, and a hybrid approach combining … Read more

Large language models (LLMs) have revolutionized the way we interact with technology, but their widespread adoption has been blocked by high inference latency, limited throughput, and high costs associated with text generation. These inefficiencies are particularly pronounced during high-demand events like Amazon Prime Day, where systems like Rufus—the Amazon AI-powered shopping assistant—must handle massive scale … Read more

Organizations across a wide range of industries are struggling to process massive amounts of unstructured video and audio content to support their core business applications and organizational priorities. Amazon Bedrock Data Automation helps them meet this challenge by streamlining application development and automating workflows that use content from documents, images, audio, and video. Recently, we … Read more

This blog post is co-written with Heidi Vogel Brockmann and Ronald Brockmann from GuardianGamer. Millions of families face a common challenge: how to keep children safe in online gaming without sacrificing the joy and social connection these games provide. In this post, we share how GuardianGamer—a member of the AWS Activate startup community—has built a … Read more

This post was cowritten by Mulay Ahmed, Assistant Director of Engineering, and Ruby Donald, Assistant Director of Engineering at Principal Financial Group. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post. Principal Financial Group® is an integrated global … Read more

Improving response quality for user queries is essential for AI-driven applications, especially those focusing on user satisfaction. For example, an HR chat-based assistant should strictly follow company policies and respond using a certain tone. A deviation from that can be corrected by feedback from users. This post demonstrates how Amazon Bedrock, combined with a user … Read more

Amazon Q Business, with its enterprise grade security, seamless integration with multiple diverse data sources, and sophisticated natural language understanding, represents the next generation of AI business assistants. What sets Amazon Q Business apart is its support of enterprise requirements from its ability to integrate with company documentation to its adaptability with specific business terminology … Read more

As companies increasingly adopt generative AI applications, AI agents capable of delivering tangible business value have emerged as a crucial component. In this context, integrating custom-built AI agents within chat services such as Slack can be transformative, providing businesses with seamless access to AI assistants powered by sophisticated foundation models (FMs). After an AI agent … Read more

Data privacy is a critical issue for software companies that provide services in the data management space. If they want customers to trust them with their data, software companies need to show and prove that their customers’ data will remain confidential and within controlled environments. Some companies go to great lengths to maintain confidentiality, sometimes … Read more

Enterprises—especially in the insurance industry—face increasing challenges in processing vast amounts of unstructured data from diverse formats, including PDFs, spreadsheets, images, videos, and audio files. These might include claims document packages, crash event videos, chat transcripts, or policy documents. All contain critical information across the claims processing lifecycle. Traditional data preprocessing methods, though functional, might … Read more

In the mortgage servicing industry, efficient document processing can mean the difference between business growth and missed opportunities. This post explores how Onity Group, a financial services company specializing in mortgage servicing and origination, used Amazon Bedrock and other AWS services to transform their document processing capabilities. Onity Group, founded in 1988, is headquartered in … Read more

This blog post is co-written with Jonas Neuman from HERE Technologies.  HERE Technologies, a 40-year pioneer in mapping and location technology, collaborated with the AWS Generative AI Innovation Center (GenAIIC) to enhance developer productivity with a generative AI-powered coding assistant. This innovative tool is designed to enhance the onboarding experience for HERE’s self-service Maps API … Read more

Businesses are constantly evolving, and leaders are challenged every day to meet new requirements and are seeking ways to optimize their operations and gain a competitive edge. One of the key challenges they face is managing the complexity of disparate business systems and workflows, which leads to inefficiencies, data silos, and missed opportunities. Generative AI … Read more

With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing the accuracy and reliability of AI-generated responses. RAG is as a way to incorporate additional data that the large language model (LLM) was not trained on. This can also help reduce generation … Read more

As one of the fastest sports in the world, almost everything is a race in Formula 1® (F1), even the pit stops. F1 drivers need to stop to change tires or make repairs to damage sustained during a race. Each precious tenth of a second the car is in the pit is lost time in … Read more

This post is co-authored by Manuel Lopez Roldan, SiMa.ai, and Jason Westra, AWS Senior Solutions Architect. Are you looking to deploy machine learning (ML) models at the edge? With Amazon SageMaker AI and SiMa.ai’s Palette Edgematic platform, you can efficiently build, train, and deploy optimized ML models at the edge for a variety of use … Read more

This post is co-written with Ken Tsui, Edward Tsoi and Mickey Yip from Apoidea Group. The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. These tasks, which require significant human resources, slow down critical operations such as Know Your Customer (KYC) procedures, loan … Read more

This post is co-authored by Jay Kshirsagar and Ronald Quan from Qualtrics. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post. Qualtrics, founded in 2002, is a pioneering software company that has spent over two decades creating exceptional … Read more

Vxceed delivers SaaS solutions across industries such as consumer packaged goods (CPG), transportation, and logistics. Its modular environments include Lighthouse for CPG demand and supply chains, GroundCentric247 for airline and airport operations, and LimoConnect247 and FleetConnect247 for passenger transport. These solutions support a wide range of customers, including government agencies in Australia and New Zealand. … Read more

PixArt-Sigma is a diffusion transformer model that is capable of image generation at 4k resolution. This model shows significant improvements over previous generation PixArt models like Pixart-Alpha and other diffusion models through dataset and architectural improvements. AWS Trainium and AWS Inferentia are purpose-built AI chips to accelerate machine learning (ML) workloads, making them ideal for … Read more

This post is the second part of the DeepSeek series focusing on model customization with Amazon SageMaker HyperPod recipes (or recipes for brevity). In Part 1, we demonstrated the performance and ease of fine-tuning DeepSeek-R1 distilled models using these recipes. In this post, we use the recipes to fine-tune the original DeepSeek-R1 671b parameter model. … Read more

According to a Gartner survey in 2024, 58% of finance functions have adopted generative AI, marking a significant rise in adoption. Among these, four primary use cases have emerged as especially prominent: intelligent process automation, anomaly detection, analytics, and operational assistance. In this post, we show you how Amazon Q Business can help augment your … Read more

Generative AI tools have transformed how we work, create, and process information. At Amazon Web Services (AWS), security is our top priority. Therefore, Amazon Bedrock provides comprehensive security controls and best practices to help protect your applications and data. In this post, we explore the security measures and practical strategies provided by Amazon Bedrock Agents … Read more

Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training. This data is used to enrich the generative AI prompt to deliver more context-specific and accurate responses without continuously retraining the FM, while also improving … Read more

This post was co-written with Julio P. Roque Hexagon ALI. Recognizing the transformative benefits of generative AI for enterprises, we at Hexagon’s Asset Lifecycle Intelligence division sought to enhance how users interact with our Enterprise Asset Management (EAM) products. Understanding these advantages, we partnered with AWS to embark on a journey to develop HxGN Alix, … Read more

In the era of AI and machine learning (ML), there is a growing emphasis on enhancing security— especially in IT contexts. In this post, we demonstrate how your organization can reduce the end-to-end burden of resolving regular challenges experienced by your IT support teams—from understanding errors and reviewing diagnoses, remediation steps, and relevant documentation, to … Read more

In the media and entertainment industry, understanding and predicting the effectiveness of marketing campaigns is crucial for success. Marketing campaigns are the driving force behind successful businesses, playing a pivotal role in attracting new customers, retaining existing ones, and ultimately boosting revenue. However, launching a campaign isn’t enough; to maximize their impact and help achieve … Read more

This post is co-written with Kilian Zimmerer and Daniel Ringler from Deutsche Bahn. Every day, Deutsche Bahn (DB) moves over 6.6 million passengers across Germany, requiring precise time series forecasting for a wide range of purposes. However, building accurate forecasting models traditionally required significant expertise and weeks of development time. Today, we’re excited to explore … Read more

With Amazon Bedrock Evaluations, you can evaluate foundation models (FMs) and Retrieval Augmented Generation (RAG) systems, whether hosted on Amazon Bedrock or another model or RAG system hosted elsewhere, including Amazon Bedrock Knowledge Bases or multi-cloud and on-premises deployments. We recently announced the general availability of the large language model (LLM)-as-a-judge technique in model evaluation … Read more