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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

Virginia) AWS Region. Prerequisites To try the Llama 4 models in SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker AI. Access to accelerated instances (GPUs) for hosting the LLMs.

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Customize Amazon Nova models to improve tool usage

AWS Machine Learning Blog

Amazon Nova models and Amazon Bedrock Amazon Nova models , unveiled at AWS re:Invent in December 2024, are optimized to deliver exceptional price-performance value, offering state-of-the-art performance on key text-understanding benchmarks at low cost. Choose us-east-1 as the AWS Region. gpus 2'] Ground truth pattern: python(3?)

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Announcing new Jupyter contributions by AWS to democratize generative AI and scale ML workloads

AWS Machine Learning Blog

Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter. In parallel to these open-source contributions, we have AWS product teams who are working to integrate Jupyter with products such as Amazon SageMaker.

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AWS performs fine-tuning on a Large Language Model (LLM) to classify toxic speech for a large gaming company

AWS Machine Learning Blog

In an effort to create and maintain a socially responsible gaming environment, AWS Professional Services was asked to build a mechanism that detects inappropriate language (toxic speech) within online gaming player interactions. Unfortunately, as in the real world, not all players communicate appropriately and respectfully.

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Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

In late 2023, Planet announced a partnership with AWS to make its geospatial data available through Amazon SageMaker. Our results reveal that the classification from the KNN model is more accurately representative of the state of the current crop field in 2017 than the ground truth classification data from 2015.

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How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps

AWS Machine Learning Blog

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

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This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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