Favorite In high-volume healthcare contact centers, every patient conversation carries both clinical and operational significance, making accurate real-time transcription necessary for automated workflows. Accurate, instant transcription enables intelligent automation without sacrificing clarity or care, so that teams can automate electronic medical record (EMR) record matching, streamline workflows, and eliminate manual

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Shared by AWS Machine Learning November 3, 2025

Favorite Enterprises in regulated industries often need mathematical certainty that every AI response complies with established policies and domain knowledge. Regulated industries can’t use traditional quality assurance methods that test only a statistical sample of AI outputs and make probabilistic assertions about compliance. When we launched Automated Reasoning checks in

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Shared by AWS Machine Learning November 1, 2025

Favorite AI agents need to browse the web on your behalf. When your agent visits a website to gather information, complete a form, or verify data, it encounters the same defenses designed to stop unwanted bots: CAPTCHAs, rate limits, and outright blocks. Today, we are excited to share that AWS

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Shared by AWS Machine Learning October 31, 2025

Favorite こんにちは, G’day. The recent launch of Anthropic’s Claude Sonnet 4.5 and Claude Haiku 4.5, now available on Amazon Bedrock, marks a significant leap forward in generative AI models. These state-of-the-art models excel at complex agentic tasks, coding, and enterprise workloads, offering enhanced capabilities to developers. Along with the new

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Shared by AWS Machine Learning October 31, 2025

Favorite This post was co-written with Kim Nguyen and Shyam Banuprakash from Clario. Clario is a leading provider of endpoint data solutions for systematic collection, management, and analysis of specific, predefined outcomes (endpoints) to evaluate a treatment’s safety and effectiveness in the clinical trials industry, generating high-quality clinical evidence for

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Shared by AWS Machine Learning October 31, 2025

Favorite In 2024, we launched the Custom Model Program within the AWS Generative AI Innovation Center to provide comprehensive support throughout every stage of model customization and optimization. Over the past two years, this program has delivered exceptional results by partnering with global enterprises and startups across diverse industries—including legal,

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Shared by AWS Machine Learning October 31, 2025

Favorite This post was written with NVIDIA and the authors would like to thank Adi Margolin, Eliuth Triana, and Maryam Motamedi for their collaboration. Organizations today face the challenge of processing large volumes of audio data–from customer calls and meeting recordings to podcasts and voice messages–to unlock valuable insights. Automatic

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Shared by AWS Machine Learning October 28, 2025

Favorite Over the past two years, companies have seen an increasing need to develop a project prioritization methodology for generative AI. There is no shortage of generative AI use cases to consider. Rather, companies want to evaluate the business value against the cost, level of effort, and other concerns, for

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Shared by AWS Machine Learning October 24, 2025

Favorite Graph databases have revolutionized how organizations manage complex, interconnected data. However, specialized query languages such as Gremlin often create a barrier for teams looking to extract insights efficiently. Unlike traditional relational databases with well-defined schemas, graph databases lack a centralized schema, requiring deep technical expertise for effective querying. To

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Shared by AWS Machine Learning October 24, 2025

Favorite The era of perpetual AI pilots is over. This year, 65% of AWS Generative AI Innovation Center customer projects moved from concept to production—some launching in just 45 days, as AWS VP Swami Sivasubramanian shared on LinkedIn. These results come from insights gained across more than one thousand customer

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Shared by AWS Machine Learning October 24, 2025