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Evaluating the quality of AI responses across multiple languages presents significant challenges for organizations deploying generative AI solutions globally. How can you maintain consistent performance when human evaluations require substantial resources, especially across diverse languages? Many companies find themselves struggling to scale their evaluation processes without compromising quality or breaking their budgets. Amazon Bedrock Evaluations …

Effective cross-lingual LLM evaluation with Amazon Bedrock Read More »

This post is co-written with Payal Singh from Cohere. The Cohere Embed 4 multimodal embeddings model is now generally available on Amazon SageMaker JumpStart. The Embed 4 model is built for multimodal business documents, has leading multilingual capabilities, and offers notable improvement over Embed 3 across key benchmarks. In this post, we discuss the benefits …

Cohere Embed 4 multimodal embeddings model is now available on Amazon SageMaker JumpStart Read More »

This post is co-written with Shashank Saraogi, Nat Gale, and Durran Kelly from INRIX. The complexity of modern traffic management extends far beyond mere road monitoring, encompassing massive amounts of data collected worldwide from connected cars, mobile devices, roadway sensors, and major event monitoring systems. For transportation authorities managing urban, suburban, and rural traffic flow, …

How INRIX accelerates transportation planning with Amazon Bedrock Read More »

Today, we are excited to announce that Qwen3, the latest generation of large language models (LLMs) in the Qwen family, is available through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, you can deploy the Qwen3 models—available in 0.6B, 4B, 8B, and 32B parameter sizes—to build, experiment, and responsibly scale your generative AI …

Qwen3 family of reasoning models now available in Amazon Bedrock Marketplace and Amazon SageMaker JumpStart Read More »

Software as a service (SaaS) companies managing multiple tenants face a critical challenge: efficiently extracting meaningful insights from vast document collections while controlling costs. Traditional approaches often lead to unnecessary spending on unused storage and processing resources, impacting both operational efficiency and profitability. Organizations need solutions that intelligently scale processing and storage resources based on …

Build a just-in-time knowledge base with Amazon Bedrock Read More »

Organizations deploying video monitoring systems face a critical challenge: processing continuous video streams while maintaining accurate situational awareness. Traditional monitoring approaches that use rule-based detection or basic computer vision frequently miss important events or generate excessive false positives, leading to operational inefficiencies and alert fatigue. In this post, we show how to build a fully …

Agents as escalators: Real-time AI video monitoring with Amazon Bedrock Agents and video streams Read More »

This field guide and investment support AI’s potential in evidence-based mental health interventions and research. ​ 

In the telecommunications industry, managing complex network infrastructures requires processing vast amounts of data from multiple sources. Network engineers often spend considerable time manually gathering and analyzing this data, taking away valuable hours that could be spent on strategic initiatives. This challenge led Swisscom, Switzerland’s leading telecommunications provider, to explore how AI can transform their …

Transforming network operations with AI: How Swisscom built a network assistant using Amazon Bedrock Read More »

Although rapid generative AI advancements are revolutionizing organizational natural language processing tasks, developers and data scientists face significant challenges customizing these large models. These hurdles include managing complex workflows, efficiently preparing large datasets for fine-tuning, implementing sophisticated fine-tuning techniques while optimizing computational resources, consistently tracking model performance, and achieving reliable, scalable deployment.The fragmented nature of …

End-to-End model training and deployment with Amazon SageMaker Unified Studio Read More »