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Empowering students with disabilities: University Startups’ generative AI solution for personalized student pathways

Empowering students with disabilities: University Startups’ generative AI solution for personalized student pathways

This post was co-authored with Laura Lee Williams and John Jabara from University Startups. University Startups, headquartered in Bethesda, MD, was founded in 2020 to empower high school students to expand their education beyond a traditional curriculum. University Startups is focused on special education and related services in school districts throughout the US. After students …

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Citations with Amazon Nova understanding models

Citations with Amazon Nova understanding models

Large language models (LLMs) have become increasingly prevalent across both consumer and enterprise applications. However, their tendency to “hallucinate” information and deliver incorrect answers with seeming confidence has created a trust problem. Think of LLMs as you would a human expert: we typically trust experts who can back up their claims with references and walk …

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Securely launch and scale your agents and tools on Amazon Bedrock AgentCore Runtime

Securely launch and scale your agents and tools on Amazon Bedrock AgentCore Runtime

Organizations are increasingly excited about the potential of AI agents, but many find themselves stuck in what we call “proof of concept purgatory”—where promising agent prototypes struggle to make the leap to production deployment. In our conversations with customers, we’ve heard consistent challenges that block the path from experimentation to enterprise-grade deployment: “Our developers want …

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PwC and AWS Build Responsible AI with Automated Reasoning on Amazon Bedrock

PwC and AWS Build Responsible AI with Automated Reasoning on Amazon Bedrock

This is a guest post co-written with Scott Likens, Ambuj Gupta, Adam Hood, Chantal Hudson, Priyanka Mukhopadhyay, Deniz Konak Ozturk, and Kevin Paul from PwC Organizations are deploying generative AI solutions while balancing accuracy, security, and compliance. In this globally competitive environment, scale matters less, speed matters more, and innovation matters most of all, according …

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How Amazon scaled Rufus by building multi-node inference using AWS Trainium chips and vLLM

How Amazon scaled Rufus by building multi-node inference using AWS Trainium chips and vLLM

At Amazon, our team builds Rufus, a generative AI-powered shopping assistant that serves millions of customers at immense scale. However, deploying Rufus at scale introduces significant challenges that must be carefully navigated. Rufus is powered by a custom-built large language model (LLM). As the model’s complexity increased, we prioritized developing scalable multi-node inference capabilities that …

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Build an intelligent financial analysis agent with LangGraph and Strands Agents

Build an intelligent financial analysis agent with LangGraph and Strands Agents

Agentic AI is revolutionizing the financial services industry through its ability to make autonomous decisions and adapt in real time, moving well beyond traditional automation. Imagine an AI assistant that can analyze quarterly earnings reports, compare them against industry expectations, and generate insights about future performance. This seemingly straightforward task involves multiple complex steps: document …

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Amazon Bedrock AgentCore Memory: Building context-aware agents

Amazon Bedrock AgentCore Memory: Building context-aware agents

AI assistants that forget what you told them 5 minutes ago aren’t very helpful. While large language models (LLMs) excel at generating human-like responses, they are fundamentally stateless—they don’t retain information between interactions. This forces developers to build custom memory systems to track conversation history, remember user preferences, and maintain context across sessions, often solving …

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