Favorite Financial institutions today face an increasingly complex regulatory world that demands robust, efficient compliance mechanisms. Although organizations traditionally invest countless hours reviewing regulations such as the Anti-Money Laundering (AML) rules and the Bank Secrecy Act (BSA), modern AI solutions offer a transformative approach to this challenge. By using Amazon

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Shared by AWS Machine Learning April 11, 2025

Favorite Today, businesses are using AI and generative models to improve productivity in their teams and provide better experiences to their customers. Personalized outbound communication can be a powerful tool to increase user engagement and conversion. For instance, as a marketing manager for a video-on-demand company, you might want to

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Shared by AWS Machine Learning April 11, 2025

Favorite As businesses and developers increasingly seek to optimize their language models for specific tasks, the decision between model customization and Retrieval Augmented Generation (RAG) becomes critical. In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each

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Shared by AWS Machine Learning April 11, 2025

Favorite As businesses and developers increasingly seek to optimize their language models for specific tasks, the decision between model customization and Retrieval Augmented Generation (RAG) becomes critical. In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each

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Shared by AWS Machine Learning April 11, 2025

Favorite Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On

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Shared by AWS Machine Learning April 11, 2025

Favorite Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On

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Shared by AWS Machine Learning April 11, 2025

Favorite Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements. The multi-LLM approach enables organizations to effectively choose the right model

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Shared by AWS Machine Learning April 10, 2025

Favorite Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements. The multi-LLM approach enables organizations to effectively choose the right model

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Shared by AWS Machine Learning April 10, 2025

Favorite Employee productivity is a critical factor in maintaining a competitive advantage. Amazon Q Business offers a unique opportunity to enhance workforce efficiency by providing AI-powered assistance that can significantly reduce the time spent searching for information, generating content, and completing routine tasks. Amazon Q Business is a fully managed,

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Shared by AWS Machine Learning April 10, 2025

Favorite Employee productivity is a critical factor in maintaining a competitive advantage. Amazon Q Business offers a unique opportunity to enhance workforce efficiency by providing AI-powered assistance that can significantly reduce the time spent searching for information, generating content, and completing routine tasks. Amazon Q Business is a fully managed,

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Shared by AWS Machine Learning April 10, 2025