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It will take several weeks for the Link spacecraft to rendezvous with NASA's Swift observatory.
In this post, we walk through how to get started with MiniMax models on Amazon Bedrock, including the capabilities supported by these models, the service tiers available, how on-demand inference scales to handle your workloads, and the different APIs you can use to access them. Using these models, customers can build agentic applications, long-context document analysis pipelines, and software engineering workflows, all backed by the security and operational guarantees of AWS.
The primary storage solutions for EC2 Windows instances, Amazon EC2 Instance Store and Amazon Elastic Block Store (Amazon EBS) , now provide detailed performance statistics for real-time monitoring. Real-time monitoring enables you to gain visibility into key performance metrics, such as latency, throughput, and IOPS, allowing you to detect and address potential bottlenecks or issues […]
HTTP methods in REST API design are more than technical details; they communicate intent between clients and servers. A GET request instructs the server to retrieve a resource. A POST request typically indicates that data should be processed, often creating a new resource. PUT indicates replacement or update, while DELETE signals removal. These methods are well-established and fundamental to the Web. Despite this, API design has long faced a notable gap.
In this post, you deploy a two-phase infrastructure for multi-turn RL using Amazon Nova Forge on Amazon SageMaker HyperPod. By the end, you have an event-driven pipeline that starts training when you upload data to Amazon Simple Storage Service (Amazon S3). The training job teaches the model to play Wordle, a placeholder for your own RL task.
In this post, we present a multi-step pipeline directed by Amazon Nova, which uses its contextual vision reasoning to coordinate complementary tools, including Meta’s open-source Segment Anything Model (SAM 3) deployed on Amazon SageMaker AI for pixel-level segmentation, and Amazon Textract for optical character recognition (OCR). This pipeline is designed to provide comprehensive and compliant PII redaction even for challenging edge cases such as fingerprints, ID cards, or license plates in arb
In this post, you learn how to use the new MLflow integration with Amazon SageMaker AI optimized inference recommendation jobs and Amazon SageMaker AI benchmark jobs to automatically stream experiment data into a unified tracking interface. This integration streams metrics, parameters, and charts into your serverless Amazon SageMaker MLflow App in real time and you get a unified experiment tracking experience.
If you’re building multi-agent AI systems, you need to prevent authorization scope from silently expanding as agents delegate tasks through multi-hop chains. Without proper controls, an agent can potentially act beyond what the originating user authorized, even when role-based access control (RBAC) policies are in place. The OWASP Top 10 for Agentic Applications classifies this […]
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