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Reinforcement fine-tuning with LLM-as-a-judge

Reinforcement fine-tuning with LLM-as-a-judge

Large language models (LLMs) now drive the most advanced conversational agents, creative tools, and decision-support systems. However, their raw output often contains inaccuracies, policy misalignments, or unhelpful phrasing—issues that undermine trust and limit real-world utility. Reinforcement Fine‑Tuning (RFT) has emerged as the preferred method to align these models efficiently, using automated reward signals to replace …

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AWS Generative AI Model Agility Solution: A comprehensive guide to migrating LLMs for generative AI production

AWS Generative AI Model Agility Solution: A comprehensive guide to migrating LLMs for generative AI production

Maintaining model agility is crucial for organizations to adapt to technological advancements and optimize their artificial intelligence (AI) solutions. Whether transitioning between different large language model (LLM) families or upgrading to newer versions within the same family, a structured migration approach and a standardized process are essential for facilitating continuous performance improvement while minimizing operational …

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Sun Finance automates ID extraction and fraud detection with generative AI on AWS

Sun Finance automates ID extraction and fraud detection with generative AI on AWS

This post was co-authored with Krišjānis Kočāns, Kaspars Magaznieks, Sergei Kiriasov from Sun Finance Group If you process identity documents at scale—loan applications, account openings, compliance checks—you’ve likely hit the same wall: traditional optical character recognition (OCR) gets you partway there, but extraction errors still push a large share of applications into manual review queues. …

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Unleashing Agentic AI Analytics on Amazon SageMaker with Amazon Athena and Amazon Quick

Unleashing Agentic AI Analytics on Amazon SageMaker with Amazon Athena and Amazon Quick

Modern enterprises face mounting challenges in extracting actionable insights from vast data lakes and lakehouses spanning petabytes of structured and unstructured data. Traditional analytics require specialized technical expertise in SQL, data modeling, and business intelligence tools, creating bottlenecks that slow decision-making across retail, financial services, healthcare, Travel & Hospitality, manufacturing and many more industries. This …

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Configuring Amazon Bedrock AgentCore Gateway for secure access to private resources

Configuring Amazon Bedrock AgentCore Gateway for secure access to private resources

AI agents in production environments often need to reach internal APIs, databases, and private resources that sit behind Amazon Virtual Private Cloud (Amazon VPC) boundaries. Managing private connectivity for each agent-to-tool path adds operational overhead and slows deployment. Amazon Bedrock AgentCore VPC connectivity is designed to deploy AI agents and Model Context Protocol (MCP) servers …

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Extracting contract insights with PwC’s AI-driven annotation on AWS

Extracting contract insights with PwC’s AI-driven annotation on AWS

This post was co-written with Yash Munsadwala, Adam Hood, Justin Guse, and Hector Hernandez from PwC. Contract analysis often consumes significant time for legal, compliance, and procurement teams, especially when important insights are buried in lengthy, unstructured agreements. As contract volumes grow, finding specific clauses and assessing extracted terms can become increasingly difficult to scale. …

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Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory

Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory

When building AI agents, developers struggle with organizing memory across sessions, which leads to irrelevant context retrieval and security vulnerabilities. AI agents that remember context across sessions need more than only storage. They need organized, retrievable, and secure memory. In Amazon Bedrock AgentCore Memory, namespaces determine how long-term memory records are organized, retrieved, and who …

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Building AI-ready data: Vanguard’s Virtual Analyst journey

Building AI-ready data: Vanguard’s Virtual Analyst journey

Vanguard is a global investment management firm, offering a broad selection of investments, advice, retirement services, and insights to individual investors, institutions, and financial professionals. We operate under a unique, investor-owned structure and adhere to a straightforward purpose: To take a stand for all investors, to treat them fairly, and to give them the best …

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Run custom MCP proxies serverless on Amazon Bedrock AgentCore Runtime

Run custom MCP proxies serverless on Amazon Bedrock AgentCore Runtime

When AI agents connect to tools through the Model Context Protocol (MCP), they gain access to capabilities that range from database queries and API calls to file operations and third-party service integrations. In production, these interactions need proper governance, controls, and observability aligned with an organization’s security policies. This includes sanitizing tool inputs before they …

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Migrating a text agent to a voice assistant with Amazon Nova 2 Sonic

Migrating a text agent to a voice assistant with Amazon Nova 2 Sonic

Migrating a text agent to a voice assistant is increasingly important because users expect faster, more natural interactions. Instead of typing, customers want to speak and understand in real time. Industries like finance, healthcare, education, social media, and retail are exploring solutions with Amazon Nova 2 Sonic to enable natural, real-time speech interactions at scale. …

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