This post is co-written with Samit Verma, Eusha Rizvi, Manmeet Singh, Troy Smith, and Corey Finley from Verisk. Verisk Rating Insights as a feature of ISO Electronic Rating Content (ERC) is a powerful tool designed to provide summaries of ISO Rating changes between two releases. Traditionally, extracting specific filing information or identifying differences across multiple … Read more
Organizations gain competitive advantage by deploying and integrating new generative AI models quickly through Generative AI Gateway architectures. This unified interface approach simplifies access to multiple foundation models (FMs), addressing a critical challenge: the proliferation of specialized AI models, each with unique capabilities, API specifications, and operational requirements. Rather than building and maintaining separate integration … Read more
Today, we are excited to announce a new capability of Amazon SageMaker HyperPod task governance to help you optimize training efficiency and network latency of your AI workloads. SageMaker HyperPod task governance streamlines resource allocation and facilitates efficient compute resource utilization across teams and projects on Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Administrators can … Read more
This post is co-written with Stefan Walter from msg. With more than 10,000 experts in 34 countries, msg is both an independent software vendor and a system integrator operating in highly regulated industries, with over 40 years of domain-specific expertise. msg.ProfileMap is a software as a service (SaaS) solution for skill and competency management. It’s … Read more
Retrieval Augmented Generation (RAG) is a fundamental approach for building advanced generative AI applications that connect large language models (LLMs) to enterprise knowledge. However, crafting a reliable RAG pipeline is rarely a one-shot process. Teams often need to test dozens of configurations (varying chunking strategies, embedding models, retrieval techniques, and prompt designs) before arriving at … Read more
You can use Amazon Bedrock Custom Model Import to seamlessly integrate your customized models—such as Llama, Mistral, and Qwen—that you have fine-tuned elsewhere into Amazon Bedrock. The experience is completely serverless, minimizing infrastructure management while providing your imported models with the same unified API access as native Amazon Bedrock models. Your custom models benefit from … Read more
This post is co-written with Gareth Jones from Anthropic. Anthropic’s Claude 4 Sonnet model has launched on Amazon Bedrock, marking a significant advancement in foundation model capabilities. Consequently, the deprecation timeline for Anthropic’s Claude 3.5 Sonnet (v1 and v2) was announced. This evolution creates a dual imperative for production AI applications: the opportunity to harness … Read more
In real-world video and image analysis, businesses often face the challenge of detecting objects that weren’t part of a model’s original training set. This becomes especially difficult in dynamic environments where new, unknown, or user-defined objects frequently appear. For example, media publishers might want to track emerging brands or products in user-generated content; advertisers need … Read more
This is a guest post co-written with Skello. Skello is a leading human resources (HR) software as a service (SaaS) solution focusing on employee scheduling and workforce management. Catering to diverse sectors such as hospitality, retail, healthcare, construction, and industry, Skello offers features including schedule creation, time tracking, and payroll preparation. With approximately 20,000 customers … Read more
Private workforces for Amazon SageMaker Ground Truth and Amazon Augmented AI (Amazon A2I) help organizations build proprietary, high-quality datasets while keeping high standards of security and privacy. The AWS Management Console provides a fast and intuitive way to create a private workforce, but many organizations need to automate their infrastructure deployment through infrastructure as code … Read more
This post was co-authored with Jingwei Zuo from TII. We are excited to announce the availability of the Technology Innovation Institute (TII)’s Falcon-H1 models on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, developers and data scientists can now use six instruction-tuned Falcon-H1 models (0.5B, 1.5B, 1.5B-Deep, 3B, 7B, and 34B) on AWS, and have access … Read more
This post was written with Avdhesh Paliwal of Oldcastle APG. Oldcastle APG, one of the largest global networks of manufacturers in the architectural products industry, was grappling with an inefficient and labor-intensive process for handling proof of delivery (POD) documents, known as ship tickets. The company was processing 100,000–300,000 ship tickets per month across more … Read more
London Stock Exchange Group (LSEG) is a global provider of financial markets data and infrastructure. It operates the London Stock Exchange and manages international equity, fixed income, and derivative markets. The group also develops capital markets software, offers real-time and reference data products, and provides extensive post-trade services. This post was co-authored with Charles Kellaway … Read more
AI agents are transforming enterprise applications across industries, from customer service to complex decision workflows. As organizations scale these deployments, they face a fundamental question: how can you improve trust in an AI application? The challenge is transparency. AI agents can make decisions on behalf of users, invoke tools dynamically, and follow reasoning paths that … Read more
As generative AI continues to transform how enterprises operate—and develop net new innovations—the infrastructure demands for training and deploying AI models have grown exponentially. Traditional infrastructure approaches are struggling to keep pace with today’s computational requirements, network demands, and resilience needs of modern AI workloads. At AWS, we’re also seeing a transformation across the technology … Read more
As organizations scale their AI infrastructure to support trillion-parameter models, they face a difficult trade-off: reduced training time with lower cost or faster training time with a higher cost. When they checkpoint frequently to speed up recovery time and minimize lost training time, they incur in substantially higher storage cost. And when they checkpoint infrequently, … Read more
We are excited to announce the general availability of fine-grained compute and memory quota allocation with HyperPod task governance. With this capability, customers can optimize Amazon SageMaker HyperPod cluster utilization on Amazon Elastic Kubernetes Service (Amazon EKS), distribute fair usage, and support efficient resource allocation across different teams or projects. For more information, see HyperPod task governance best … Read more
Basic AI chat isn’t enough for most business applications. Institutions need AI that can pull from their databases, integrate with their existing tools, handle multi-step processes, and make decisions independently. This post demonstrates how to quickly build sophisticated AI agents using Strands Agents, scale them reliably with Amazon Bedrock AgentCore, and make them accessible through … Read more
This post was written with Lior Heber and Yarden Ron of Skai. Skai (formerly Kenshoo) is an AI-driven omnichannel advertising and analytics platform designed for brands and agencies to plan, launch, optimize, and measure paid media across search, social, retail media marketplaces and other “walled-garden” channels from a single interface. By unifying data from over … Read more
This post was written with Felipe Monroy, Ana Jaime, and Nikita Gordeev from Snoonu. Managing a massive product catalog in the ecommerce space has introduced new hurdles for retailers who are trying to efficiently connect customers with the items they truly want. Traditional one-size-fits-all approaches often result in lost opportunities and reduced customer engagement. For … Read more
This post was written with Mohamed Hossam of Brightskies. Research universities engaged in large-scale AI and high-performance computing (HPC) often face significant infrastructure challenges that impede innovation and delay research outcomes. Traditional on-premises HPC clusters come with long GPU procurement cycles, rigid scaling limits, and complex maintenance requirements. These obstacles restrict researchers’ ability to iterate … Read more
This post is co-written by Jake Friedman, President + Co-founder of Wildlife. Amazon Nova is enhancing sports fan engagement through an immersive Formula 1 (F1)-inspired experience that turns traditional spectators into active participants. This post explores the Real-Time Race Track (RTRT), an interactive experience built using Amazon Nova in Amazon Bedrock, that lets fans design, … Read more
Although careful prompt crafting can yield good results, achieving professional-grade visual consistency often requires adapting the underlying model itself. Building on the prompt engineering and character development approach covered in Part 1 of this two-part series, we now push the consistency level for specific characters by fine-tuning an Amazon Nova Canvas foundation model (FM). Through … Read more
The art of storyboarding stands as the cornerstone of modern content creation, weaving its essential role through filmmaking, animation, advertising, and UX design. Though traditionally, creators have relied on hand-drawn sequential illustrations to map their narratives, today’s AI foundation models (FMs) are transforming this landscape. FMs like Amazon Nova Canvas and Amazon Nova Reel offer … Read more
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. The data accessor now supports … Read more
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 tasks based on your enterprise data. … Read more
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, potentially reducing user trust and organizational … Read more
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’s distributed training and inference capabilities. … Read more
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’t necessary. Amazon Bedrock batch inference … Read more
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 complex queries into explicit, verifiable reasoning … Read more