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Building web search-enabled agents with Strands and Exa

Building web search-enabled agents with Strands and Exa

This post is co written by Ishan Goswami and Nitya Sridhar from Exa. If you are building web search-enabled AI agents for research, fact-checking, or competitive intelligence, access to current and reliable information is critical. Most general-purpose search APIs are not designed for agent workflows. They return HTML-heavy pages and short snippets optimized for human …

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Introducing Claude Platform on AWS: Anthropic’s native platform, through your AWS account

Introducing Claude Platform on AWS: Anthropic’s native platform, through your AWS account

Today, we’re excited to announce the general availability of Claude Platform on AWS. Claude Platform on AWS is a new service that gives customers direct access to Anthropic’s native Claude Platform experience through their AWS account, with no separate credentials, contracts, or billing relationships required. AWS is the first cloud provider to offer access to …

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Manufacturing intelligence with Amazon Nova Multimodal Embeddings

Manufacturing intelligence with Amazon Nova Multimodal Embeddings

If you work in aerospace, automotive, or heavy industry manufacturing, your organization likely maintains vast repositories of technical documents. These documents combine written specifications with engineering diagrams, CAD drawings, inspection photographs, thermal analysis plots, and fatigue curves. A text query about maximum wall temperature at the nozzle throat might have its answer locked inside a …

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How Miro uses Amazon Bedrock to boost software bug routing accuracy and improve time-to-resolution from days to hours

How Miro uses Amazon Bedrock to boost software bug routing accuracy and improve time-to-resolution from days to hours

This post is co-authored with Philipp Pavlov, Dmytro Romantsov, Evgeny Mironenko, and Gowri Suryanarayana from Miro. Miro is an AI-powered innovation workspace that serves over 95 million users globally, helping teams transform unstructured ideas into organized workflows. To support this scale and continue enhancing their system, Miro’s developer experience team decided to create an innovation …

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Amazon Quick: Accelerating the path from enterprise data to AI-powered decisions

Amazon Quick: Accelerating the path from enterprise data to AI-powered decisions

Enterprise data with tens of millions of rows, row-level and column-level security, and dozens of datasets spanning multiple business domains need AI-generated answers that are trustworthy, reproducible, and fast, while respecting governance rules consistently. With foundation models (FMs), organizations can build systems that work well for small datasets where a business user asks a question …

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Halliburton enhances seismic workflow creation with Amazon Bedrock and Generative AI

Halliburton enhances seismic workflow creation with Amazon Bedrock and Generative AI

Seismic data analysis is an essential component of energy exploration, but configuring complex processing workflows has traditionally been a time-consuming and error-prone challenge. Halliburton’s Seismic Engine, a cloud-native application for seismic data processing, is a powerful tool that previously required manual configuration of approximately 100 specialized tools to create workflows. This process was not only …

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Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

As companies of various sizes adopt graphic processing units (GPU)-based machine learning (ML) training, fine-tuning and inference workloads, the demand for GPU capacity has outpaced industry-wide supply. This imbalance has made GPUs a scarce resource, creating a challenge for customers who need reliable access to GPU compute resources for their ML workloads. When you encounter …

Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans Read More »

Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI

Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI

Training large language models requires accurate feedback signals, but traditional reinforcement learning (RL) often struggles with reward signal reliability. The quality of these signals directly influences how models learn and make decisions. However, creating robust feedback mechanisms can be complex and error prone. Real-world training scenarios often introduce hidden biases, unintended incentives, and ambiguous success …

Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI Read More »

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