AI

Accelerate AI development with Amazon Bedrock API keys

Today, we’re excited to announce a significant improvement to the developer experience of Amazon Bedrock: API keys. API keys provide quick access to the Amazon Bedrock APIs, streamlining the authentication process so that developers can focus on building rather than configuration. CamelAI is an open-source, modular framework for building intelligent multi-agent systems for data generation, […]

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Accelerating data science innovation: How Bayer Crop Science used AWS AI/ML services to build their next-generation MLOps service

The world’s population is expanding at a rapid rate. The growing global population requires innovative solutions to produce food, fiber, and fuel, while restoring natural resources like soil and water and addressing climate change. Bayer Crop Science estimates farmers need to increase crop production by 50% by 2050 to meet these demands. To support their

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Combat financial fraud with GraphRAG on Amazon Bedrock Knowledge Bases

Financial fraud detection isn’t just important to banks—it’s essential. With global fraud losses surpassing $40 billion annually and sophisticated criminal networks constantly evolving their tactics, financial institutions face an increasingly complex threat landscape. Today’s fraud schemes operate across multiple accounts, institutions, and channels, creating intricate webs designed specifically to evade detection systems. Financial institutions have

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Classify call center conversations with Amazon Bedrock batch inference

In this post, we demonstrate how to build an end-to-end solution for text classification using the Amazon Bedrock batch inference capability with the Anthropic’s Claude Haiku model. Amazon Bedrock batch inference offers a 50% discount compared to the on-demand price, which is an important factor when dealing with a large number of requests. We walk

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Effective cross-lingual LLM evaluation with Amazon Bedrock

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

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

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

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Study could lead to LLMs that are better at complex reasoning

For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex reasoning skills. While an accounting firm’s LLM might excel at summarizing financial reports, that same model could fail unexpectedly if tasked with predicting market trends or identifying fraudulent transactions. To make LLMs more adaptable, MIT

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How INRIX accelerates transportation planning with Amazon Bedrock

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,

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

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

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