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

Favorite Generative AI has emerged as a transformative technology in healthcare, driving digital transformation in essential areas such as patient engagement and care management. It has shown potential to revolutionize how clinicians provide improved care through automated systems with diagnostic support tools that provide timely, personalized suggestions, ultimately leading to

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Shared by AWS Machine Learning October 24, 2025

Favorite Many enterprises are burdened with mission-critical systems built on outdated technologies that have become increasingly difficult to maintain and extend. This post demonstrates how you can use the Amazon Bedrock Converse API with Amazon Nova Premier within an agentic workflow to systematically migrate legacy C code to modern Java/Spring

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Shared by AWS Machine Learning October 23, 2025

Favorite As organizations embrace generative AI powered by Amazon Bedrock, they face the challenge of managing costs associated with the token-based pricing model. Amazon Bedrock offers a pay-as-you-go pricing structure that can potentially lead to unexpected and excessive bills if usage is not carefully monitored. Traditional methods of cost monitoring,

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Shared by AWS Machine Learning October 23, 2025