Favorite The EU AI Act requires organizations fine-tuning large language models (LLMs) to track computational resources measured in floating-point operations (FLOPs) to determine compliance obligations. As customers increasingly fine-tune LLMs for domain-specific use cases, we hear a common question: how do I know if my training job triggers new regulatory
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Shared by AWS Machine Learning May 12, 2026
Favorite Before you can extract information from documents using intelligent document processing (IDP) techniques, you need a schema for each document class that defines what to extract. But how do you create schemas when you have thousands of documents and don’t know what classes exist? Doing this at scale can
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Shared by AWS Machine Learning May 12, 2026
Favorite Amazon’s Finance Technology (FinTech) teams build and operate systems for Amazon teams to manage regulatory inquiries in compliance with different jurisdictions. These teams process regulatory inquiries from authorities, each presenting different requirements, document formats, and complexity levels. Processing these regulatory inquiries involves reviewing documentation, extracting relevant information, retrieving supporting
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Shared by AWS Machine Learning May 12, 2026
Favorite Enterprise data with tens of millions of rows, row-level and column-level security, and dozens of datasets spanning multiple business domains need AI-generated answers that are trustworthy, reproducible, and fast, while respecting governance rules consistently. With foundation models (FMs), organizations can build systems that work well for small datasets where
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Shared by AWS Machine Learning May 11, 2026
Favorite This post is co-authored with Philipp Pavlov, Dmytro Romantsov, Evgeny Mironenko, and Gowri Suryanarayana from Miro. Miro is an AI-powered innovation workspace that serves over 95 million users globally, helping teams transform unstructured ideas into organized workflows. To support this scale and continue enhancing their system, Miro’s developer experience
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Shared by AWS Machine Learning May 11, 2026
Favorite If you work in aerospace, automotive, or heavy industry manufacturing, your organization likely maintains vast repositories of technical documents. These documents combine written specifications with engineering diagrams, CAD drawings, inspection photographs, thermal analysis plots, and fatigue curves. A text query about maximum wall temperature at the nozzle throat might
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Shared by AWS Machine Learning May 11, 2026
Favorite Today, we’re excited to announce the general availability of Claude Platform on AWS. Claude Platform on AWS is a new service that gives customers direct access to Anthropic’s native Claude Platform experience through their AWS account, with no separate credentials, contracts, or billing relationships required. AWS is the first
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Shared by AWS Machine Learning May 11, 2026
Favorite This post is co written by Ishan Goswami and Nitya Sridhar from Exa. If you are building web search-enabled AI agents for research, fact-checking, or competitive intelligence, access to current and reliable information is critical. Most general-purpose search APIs are not designed for agent workflows. They return HTML-heavy pages
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Shared by AWS Machine Learning May 11, 2026
Favorite This week, the new, AI-powered Google Finance is launching across Europe, with full local language support. This reimagined experience offers a suite of powerful capabil… View Original Source (blog.google/technology/ai/) Here.
Favorite Seismic data analysis is an essential component of energy exploration, but configuring complex processing workflows has traditionally been a time-consuming and error-prone challenge. Halliburton’s Seismic Engine, a cloud-native application for seismic data processing, is a powerful tool that previously required manual configuration of approximately 100 specialized tools to create
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Shared by AWS Machine Learning May 8, 2026
Shared by AWS Machine Learning May 12, 2026
