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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

Overall, implementing a modern data architecture and generative AI techniques with AWS is a promising approach for gleaning and disseminating key insights from diverse, expansive data at an enterprise scale. AWS also offers foundation models through Amazon SageMaker JumpStart as Amazon SageMaker endpoints.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

FL doesn’t require moving or sharing data across sites or with a centralized server during the model training process. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. Participants can either choose to maintain their data in their on-premises systems or in an AWS account that they control.

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Accelerate development of ML workflows with Amazon Q Developer in Amazon SageMaker Studio

AWS Machine Learning Blog

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value.

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Customizing coding companions for organizations

AWS Machine Learning Blog

In these two studies, commissioned by AWS, developers were asked to create a medical software application in Java that required use of their internal libraries. About the authors Qing Sun is a Senior Applied Scientist in AWS AI Labs and work on AWS CodeWhisperer, a generative AI-powered coding assistant.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. The AWS P5 EC2 instance type range is based on the NVIDIA H100 chip, which uses the Hopper architecture. In November 2023, AWS announced the next generation Trainium2 chip.

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Zero-shot prompting for the Flan-T5 foundation model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

We also demonstrate how you can engineer prompts for Flan-T5 models to perform various natural language processing (NLP) tasks. Task Prompt (template in bold) Model output Summarization Briefly summarize this paragraph: Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

” Advances in neural information processing systems 32 (2019). He helps AWS customers identify and build ML solutions to address their business challenges in areas such as logistics, personalization and recommendations, computer vision, fraud prevention, forecasting and supply chain optimization. Visualizing data using t-SNE.”

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