AI

Enhanced metrics for Amazon SageMaker AI endpoints: deeper visibility for better performance

Running machine learning (ML) models in production requires more than just infrastructure resilience and scaling efficiency. You need nearly continuous visibility into performance and resource utilization. When latency increases, invocations fail, or resources become constrained, you need immediate insight to diagnose and resolve issues before they impact your customers. Until now, Amazon SageMaker AI provided

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Enforce data residency with Amazon Quick extensions for Microsoft Teams

Organizations with users in multiple geographies face data residency requirements such as General Data Protection Regulation (GDPR) in Europe, country-specific data sovereignty laws, and internal compliance policies. Amazon Quick with Microsoft 365 extensions supports Regional routing to meet these requirements. Amazon Quick supports multi-Region deployments so you can route users to AWS Region-specific Amazon Quick

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A better method for identifying overconfident large language models

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the same answer. But this method measures self-confidence, and even the most impressive LLM might be

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Generative AI improves a wireless vision system that sees through obstructions

MIT researchers have spent more than a decade studying techniques that enable robots to find and manipulate hidden objects by “seeing” through obstacles. Their methods utilize surface-penetrating wireless signals that reflect off concealed items. Now, the researchers are leveraging generative artificial intelligence models to overcome a longstanding bottleneck that limited the precision of prior approaches.

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