AI

Agent-to-agent collaboration: Using Amazon Nova 2 Lite and Amazon Nova Act for multi-agent systems

My first attempt at building a travel planning agent looked exactly like most early prototypes: one big model, a few tools, and a long system prompt. It worked fine until the moment real-world complexity showed up. Flights came from a clean API, hotels lived behind a shifting web UI, and the model kept mixing instructions, […]

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Structured outputs on Amazon Bedrock: Schema-compliant AI responses

Today, we’re announcing structured outputs on Amazon Bedrock—a capability that fundamentally transforms how you can obtain validated JSON responses from foundation models through constrained decoding for schema compliance. This represents a paradigm shift in AI application development. Instead of validating JSON responses and writing fallback logic for when they fail, you can move straight to

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Manage Amazon SageMaker HyperPod clusters using the HyperPod CLI and SDK

Training and deploying large AI models requires advanced distributed computing capabilities, but managing these distributed systems shouldn’t be complex for data scientists and machine learning (ML) practitioners. The command line interface (CLI) and software development kit (SDK) for Amazon SageMaker HyperPod with Amazon Elastic Kubernetes Service (Amazon EKS) orchestration simplify how you manage cluster infrastructure and use

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“This is science!” – MIT president talks about the importance of America’s research enterprise on GBH’s Boston Public Radio

In a wide-ranging live conversation, MIT President Sally Kornbluth joined Jim Braude and Margery Eagan live in studio for GBH’s Boston Public Radio on Thursday, February 5. They talked about MIT, the pressures facing America’s research enterprise, the importance of science, that Congressional hearing on antisemitism in 2023, and more – including Sally’s experience as a

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