Favorite Amazon Bedrock AgentCore Gateway provides a centralized layer for managing how AI agents connect to tools and MCP servers across your organization. It consolidates authentication, observability, and policy enforcement into a single endpoint, removing the need to configure and secure each MCP server connection individually. In this post, we
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Shared by AWS Machine Learning April 6, 2026
Favorite This post is co-written with Arad Ben Haim and Hannah Danan Moise from Windward. Windward is a leading Maritime AI company, delivering mission-grade, multi-source intelligence for maritime-based operations. By fusing Automatic Identification System (AIS) data, remote sensing signals, proprietary AI models, and generative AI, Windward provides a 360° view
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Shared by AWS Machine Learning April 6, 2026
Favorite Agentic generative AI assistants represent a significant advancement in artificial intelligence, featuring dynamic systems powered by large language models (LLMs) that engage in open-ended dialogue and tackle complex tasks. Unlike basic chatbots, these implementations possess broad intelligence, maintaining multi-step conversations while adapting to user needs and executing necessary backend
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Shared by AWS Machine Learning April 6, 2026
Favorite Agentic tool calling is what makes AI agents useful in production. It’s how they query databases, trigger workflows, retrieve real-time data, and act on a user’s behalf. But base models frequently hallucinate tools, pass bad parameters, and attempt actions when they should ask for clarification. These failures erode trust
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Shared by AWS Machine Learning April 6, 2026
Favorite Enterprises often struggle to onboard new team members at scale. Human resources (HR) teams spend time on manual tasks that delay productivity, such as processing documents to answering repeated questions about benefits and policies. For organizations with many new hires, these steps make it harder to keep onboarding consistent
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Shared by AWS Machine Learning April 6, 2026
Favorite AI agents have evolved significantly beyond chat. Writing code, persist filesystem state, execute shell commands, and managing states throughout the filesystem are some examples of things that they can do. As agentic coding assistants and development workflows have matured, the filesystem has become agents’ primary working memory, extending their
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Shared by AWS Machine Learning April 2, 2026
Favorite This post is cowritten by Jeremy Little and Chris Day from Rocket Close. Rocket Close, a Detroit-based title and appraisal management company within the Rocket Companies environment, has enhanced mortgage document processing by transforming a time-consuming manual process into an efficient automated solution. Processing approximately 2,000 abstract package files
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Shared by AWS Machine Learning April 2, 2026
Favorite AI agents that can browse the web open powerful possibilities—from research automation to real-time data gathering. However, giving an AI agent unrestricted internet access raises security and compliance concerns. What if the agent accesses unauthorized websites? What if sensitive data is exfiltrated to external domains? Amazon Bedrock AgentCore provides
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Shared by AWS Machine Learning April 2, 2026
Favorite This post is cowritten with Altay Sansal and Alejandro Valenciano from TGS. TGS, a geoscience data provider for the energy sector, supports companies’ exploration and production workflows with advanced seismic foundation models (SFMs). These models analyze complex 3D seismic data to identify geological structures vital for energy exploration. To
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Shared by AWS Machine Learning April 2, 2026
Favorite Evaluating single-turn agent interactions follows a pattern that most teams understand well. You provide an input, collect the output, and judge the result. Frameworks like Strands Evaluation SDK make this process systematic through evaluators that assess helpfulness, faithfulness, and tool usage. In a previous blog post, we covered how
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Shared by AWS Machine Learning April 2, 2026
Shared by AWS Machine Learning April 6, 2026
