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New capabilities in Amazon SageMaker AI continue to transform how organizations develop AI models

As AI models become increasingly sophisticated and specialized, the ability to quickly train and customize models can mean the difference between industry leadership and falling behind. That is why hundreds of thousands of customers use the fully managed infrastructure, tools, and workflows of Amazon SageMaker AI to scale and advance AI model development. Since launching …

Self-reflective Uncertainties: Do LLMs Know Their Internal Answer Distribution?

This paper was accepted at the Workshop on Reliable and Responsible Foundation Models (RRFMs) Workshop at ICML 2025. Uncertainty quantification plays a pivotal role when bringing large language models (LLMs) to end-users. Its primary goal is that an LLM should indicate when it is unsure about an answer it gives. While this has been revealed …

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AWS AI infrastructure with NVIDIA Blackwell: Two powerful compute solutions for the next frontier of AI

Imagine a system that can explore multiple approaches to complex problems, drawing on its understanding of vast amounts of data, from scientific datasets to source code to business documents, and reasoning through the possibilities in real time. This lightning-fast reasoning isn’t waiting on the horizon. It’s happening today in our customers’ AI production environments. The …

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How to tap into natural language AI services using the Conversational Analytics API

AI is making it easier than ever to get clear, reliable answers from your data. With intelligent tools like the Conversational Analytics API, powered by Gemini, you no longer need intricate systems to get insights. The Conversational Analytics API lets you use everyday language to ask questions of your data in BigQuery or Looker, with …