In the drive to remain competitive, businesses today are turning to AI to help them minimize cost and maximize efficiency. It’s incumbent on them to find the most suitable AI model—the one that will help them achieve more while spending less. For many businesses, the migration from OpenAI’s model family to Amazon Nova represents not … Read more
Organizations deploying generative AI applications need robust ways to evaluate their performance and reliability. When we launched LLM-as-a-judge (LLMaJ) and Retrieval Augmented Generation (RAG) evaluation capabilities in public preview at AWS re:Invent 2024, customers used them to assess their foundation models (FMs) and generative AI applications, but asked for more flexibility beyond Amazon Bedrock models … Read more
Large language models (LLMs) can be used to perform natural language processing (NLP) tasks ranging from simple dialogues and information retrieval tasks, to more complex reasoning tasks such as summarization and decision-making. Prompt engineering and supervised fine-tuning, which use instructions and examples demonstrating the desired task, can make LLMs better at following human intents, in … Read more
This post is co-written with Paul Pagnan from Lumi. Lumi is a leading Australian fintech lender empowering small businesses with fast, flexible, and transparent funding solutions. They use real-time data and machine learning (ML) to offer customized loans that fuel sustainable growth and solve the challenges of accessing capital. Their goal is to provide fast … Read more
Every year, AWS Sales personnel draft in-depth, forward looking strategy documents for established AWS customers. These documents help the AWS Sales team to align with our customer growth strategy and to collaborate with the entire sales team on long-term growth ideas for AWS customers. These documents are internally called account plans (APs). In 2024, this … Read more
This post is co-written with Emrah Kaya and Xinyi Zhou from Omron Europe. Data is one of the most critical assets of many organizations. They’re constantly seeking ways to use their vast amounts of information to gain competitive advantages. OMRON Corporation is a leading technology provider in industrial automation, healthcare, and electronic components. In their … Read more
Inspecting wind turbines, power lines, 5G towers, and pipelines is a tough job. It’s often dangerous, time-consuming, and prone to human error. That’s why we at Amazon Web Services (AWS) are working on AI Workforce—a system that uses drones and AI to make these inspections safer, faster, and more accurate. This post is the first … Read more
Foundation model (FM) training and inference has led to a significant increase in computational needs across the industry. These models require massive amounts of accelerated compute to train and operate effectively, pushing the boundaries of traditional computing infrastructure. They require efficient systems for distributing workloads across multiple GPU accelerated servers, and optimizing developer velocity as … Read more
The goal of this blog post is to show you how a large language model (LLM) can be used to perform tasks that require multi-step dynamic reasoning and execution. Examples of tasks that require dynamic reasoning and execution are answering questions of the form “What is the average length of stay for patients with [specific … Read more
We’re excited to announce the open source release of AWS MCP Servers for code assistants — a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. Our specialized AWS MCP servers combine deep AWS knowledge with agentic AI capabilities to accelerate development across … Read more
AI agents extend large language models (LLMs) by interacting with external systems, executing complex workflows, and maintaining contextual awareness across operations. Amazon Bedrock Agents enables this functionality by orchestrating foundation models (FMs) with data sources, applications, and user inputs to complete goal-oriented tasks through API integration and knowledge base augmentation. However, in the past, connecting … Read more
Generative AI has emerged as a powerful tool for content creation, offering several key benefits that can significantly enhance the efficiency and effectiveness of content production processes such as creating marketing materials, image generation, content moderation etc. Constitutional AI and LangGraph‘s reflection mechanisms represent two complementary approaches to ensuring AI systems behave ethically – with … Read more
Foundation models (FMs) and generative AI are transforming enterprise operations across industries. McKinsey & Company’s recent research estimates generative AI could contribute up to $4.4 trillion annually to the global economy through enhanced operational efficiency, productivity growth of 0.1% to 0.6% annually, improved customer experience through personalized interactions, and accelerated digital transformation. Today, organizations struggle … Read more
AWS App Studio is a generative AI-powered service that uses natural language to build business applications, empowering a new set of builders to create applications in minutes. With App Studio, technical professionals such as IT project managers, data engineers, enterprise architects, and solution architects can quickly develop applications tailored to their organization’s needs—without requiring deep … Read more
This post is co-authored with Joao Moura and Tony Kipkemboi from CrewAI. The enterprise AI landscape is undergoing a seismic shift as agentic systems transition from experimental tools to mission-critical business assets. In 2025, AI agents are expected to become integral to business operations, with Deloitte predicting that 25% of enterprises using generative AI will … Read more
Amazon Bedrock Guardrails announces the general availability of image content filters, enabling you to moderate both image and text content in your generative AI applications. Previously limited to text-only filtering, this enhancement now provides comprehensive content moderation across both modalities. This new capability removes the heavy lifting required to build your own image safeguards or … Read more
When implementing machine learning (ML) workflows in Amazon SageMaker Canvas, organizations might need to consider external dependencies required for their specific use cases. Although SageMaker Canvas provides powerful no-code and low-code capabilities for rapid experimentation, some projects might require specialized dependencies and libraries that aren’t included by default in SageMaker Canvas. This post provides an … Read more
In this post, we explore how you can use Amazon Bedrock to generate high-quality categorical ground truth data, which is crucial for training machine learning (ML) models in a cost-sensitive environment. Generative AI solutions can play an invaluable role during the model development phase by simplifying training and test data creation for multiclass classification supervised … Read more
Amazon Bedrock cross-Region inference capability that provides organizations with flexibility to access foundation models (FMs) across AWS Regions while maintaining optimal performance and availability. However, some enterprises implement strict Regional access controls through service control policies (SCPs) or AWS Control Tower to adhere to compliance requirements, inadvertently blocking cross-Region inference functionality in Amazon Bedrock. This … Read more
Amazon SageMaker JumpStart is a machine learning (ML) hub that provides pre-trained models, solution templates, and algorithms to help developers quickly get started with machine learning. Within SageMaker JumpStart, the private model hub feature allows organizations to create their own internal repository of ML models, enabling teams to share and manage models securely within their … Read more
In the competitive world of game development, staying ahead of technological advancements is crucial. Generative AI has emerged as a game changer, offering unprecedented opportunities for game designers to push boundaries and create immersive virtual worlds. At the forefront of this revolution is Stability AI’s cutting-edge text-to-image AI model, Stable Diffusion 3.5 Large (SD3.5 Large), … Read more
Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Session Management APIs provide an out-of-the-box solution that enables developers to securely manage state and conversation context across … Read more
Deploying models efficiently, reliably, and cost-effectively is a critical challenge for organizations of all sizes. As organizations increasingly deploy foundation models (FMs) and other machine learning (ML) models to production, they face challenges related to resource utilization, cost-efficiency, and maintaining high availability during updates. Amazon SageMaker AI introduced inference component functionality that can help organizations … Read more
Amazon Bedrock Knowledge Bases is a fully managed capability that helps implement entire Retrieval Augmented Generation (RAG) workflows from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows. There is no single way to optimize knowledge base performance: each use case is impacted differently by … Read more
Since Amazon Q Business became generally available in 2024, customers have used this fully managed, generative AI-powered assistant to enhance their productivity and efficiency. The assistant enables users to answer questions, generate summaries, create content, and complete tasks using enterprise data. Today’s workforce faces significant application overload. According to Gartner, the average desk worker now … Read more
Today’s organizations face a critical challenge with the fragmentation of vital information across multiple environments. As businesses increasingly rely on diverse project management and IT service management (ITSM) tools such as ServiceNow, Atlassian Jira and Confluence, employees find themselves navigating a complex web of systems to access crucial data. This isolated approach leads to several … Read more
Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data. However, by using Anthropic’s Claude on Amazon Bedrock, researchers and engineers can … Read more
IT operations teams face the challenge of providing smooth functioning of critical systems while managing a high volume of incidents filed by end-users. Manual intervention in incident management can be time-consuming and error prone because it relies on repetitive tasks, human judgment, and potential communication gaps. Using generative AI for IT operations offers a transformative … Read more
As AWS environments grow in complexity, troubleshooting issues with resources can become a daunting task. Manually investigating and resolving problems can be time-consuming and error-prone, especially when dealing with intricate systems. Fortunately, AWS provides a powerful tool called AWS Support Automation Workflows, which is a collection of curated AWS Systems Manager self-service automation runbooks. These … Read more
Today we are announcing that general availability of Amazon Bedrock in Amazon SageMaker Unified Studio. Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. Manual processes and fragmented information sources can create bottlenecks and slow decision-making, limiting teams from focusing on higher-value work. … Read more