Building intelligent event agents using Amazon Bedrock AgentCore and Amazon Bedrock Knowledge Bases

Favorite Large conferences and events generate overwhelming amounts of information—from hundreds of sessions and workshops to speaker profiles, venue maps, and constantly updating schedules. While basic AI assistants can answer simple questions about event logistics, most fail to deliver the personalized guidance and contextual awareness that attendees need to navigate

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Shared by AWS Machine Learning February 26, 2026

Introducing Amazon Bedrock global cross-Region inference for Anthropic’s Claude models in the Middle East Regions (UAE and Bahrain)

Favorite We’re excited to announce the availability of Anthropic’s Claude Opus 4.6, Claude Sonnet 4.6, Claude Opus 4.5, Claude Sonnet 4.5, and Claude Haiku 4.5 through Amazon Bedrock global cross-Region inference for customers operating in the Middle East. This launch supports organizations in the Middle East to access Anthropic’s latest

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Shared by AWS Machine Learning February 25, 2026

Global cross-Region inference for latest Anthropic Claude Opus, Sonnet and Haiku models on Amazon Bedrock in Thailand, Malaysia, Singapore, Indonesia, and Taiwan

Favorite Organizations across in Thailand, Malaysia, Singapore, Indonesia, and Taiwan can now access Anthropic Claude Opus 4.6, Sonnet 4.6, and Claude Haiku 4.5 through Global cross-Region inference (CRIS) on Amazon Bedrock—delivering foundation models through a globally distributed inference architecture designed for scale. Global CRIS offers three key advantages: higher quotas,

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Shared by AWS Machine Learning February 25, 2026

Train CodeFu-7B with veRL and Ray on Amazon SageMaker Training jobs

Favorite The rapid advancement of artificial intelligence (AI) has created unprecedented demand for specialized models capable of complex reasoning tasks, particularly in competitive programming where models must generate functional code through algorithmic reasoning rather than pattern memorization. Reinforcement learning (RL) enables models to learn through trial and error by receiving

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Shared by AWS Machine Learning February 25, 2026

Build an intelligent photo search using Amazon Rekognition, Amazon Neptune, and Amazon Bedrock

Favorite Managing large photo collections presents significant challenges for organizations and individuals. Traditional approaches rely on manual tagging, basic metadata, and folder-based organization, which can become impractical when dealing with thousands of images containing multiple people and complex relationships. Intelligent photo search systems address these challenges by combining computer vision,

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Shared by AWS Machine Learning February 25, 2026

Agentic AI with multi-model framework using Hugging Face smolagents on AWS

Favorite This post is cowritten by Jeff Boudier, Simon Pagezy, and Florent Gbelidji from Hugging Face. Agentic AI systems represent an evolution from conversational AI to autonomous agents capable of complex reasoning, tool usage, and code execution. Enterprise applications benefit from strategic deployment approaches tailored to specific needs. These needs include managed

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Shared by AWS Machine Learning February 24, 2026