SageMaker

Implementing Federated learning with FedML, Amazon EKS, and Amazon SageMaker on AWS | Amazon Web Services

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Implementing Federated learning with FedML, Amazon EKS, and Amazon SageMaker on AWS | Amazon Web Services

Machine learning (ML) is being used by organizations to improve business decision-making by utilizing large datasets. However, sharing raw sensitive information poses security risks. Federated learning (FL) is a decentralized ML training technique that maintains data privacy while collaborating on model training. FL addresses data privacy concerns by training models within isolated client locations and … Read more

Private Hub Management for Amazon SageMaker JumpStart Foundation Models | Amazon Web Services

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Private Hub Management for Amazon SageMaker JumpStart Foundation Models | Amazon Web Services

Amazon SageMaker JumpStart is a machine learning hub that offers pre-trained models and solutions. It allows access to hundreds of foundation models (FMs) and includes a private hub feature for sharing models and notebooks within an organization. Enterprise admins can now configure granular access control over the FMs available in SageMaker JumpStart to restrict user … Read more

Introducing Fully Managed MLflow on Amazon SageMaker | Amazon Web Services Now Available

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Introducing Fully Managed MLflow on Amazon SageMaker | Amazon Web Services Now Available

Amazon SageMaker has officially launched a fully managed MLflow capability, making it easier for machine learning teams to manage the entire ML lifecycle. This new release allows customers to effortlessly configure and manage MLflow tracking servers, streamlining the process and increasing productivity. MLflow is a popular open-source tool that data scientists and machine learning developers … Read more

AWS Introduces Managed MLflow on Amazon SageMaker

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AWS Introduces Managed MLflow on Amazon SageMaker

Amazon SageMaker, an AWS service launched in 2017, continues to play a critical role in the world of AI. It provides customers with a managed environment and tools to build, train, and deploy machine learning models at scale. Noteworthy applications of Amazon SageMaker include training popular generative AI models like Stable Diffusion from Stability AI … Read more

Utilizing AWS Sagemaker for Quantisation in Applied LLM | Analytics.gov

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Utilizing AWS Sagemaker for Quantisation in Applied LLM | Analytics.gov

Analytics.gov, developed by GovTech Singapore, is a machine learning platform that helps government agencies implement AI projects efficiently. By leveraging open-source models through AG’s AWS Sagemaker Endpoints, agencies can deploy quantised models quickly and at a lower cost, reducing the barriers to using large language models (LLMs) for public good. Quantisation is a technique that … Read more

Improve Mixtral 8x7B pre-training speed with expert parallelism on Amazon SageMaker | Amazon Web Services

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Improve Mixtral 8x7B pre-training speed with expert parallelism on Amazon SageMaker | Amazon Web Services

Mixture of Experts (MoE) architectures are gaining popularity for large language models (LLMs) due to their ability to increase model capacity and computational efficiency compared to fully dense models. MoE models utilize sparse expert subnetworks that process different subsets of tokens, allowing for a higher number of parameters with less computation per token during training … Read more

Leveraging SageMaker and Amazon Bedrock to Refine a Vision-Language Model for Writing Fashion Product Descriptions | Amazon Web Services

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Leveraging SageMaker and Amazon Bedrock to Refine a Vision-Language Model for Writing Fashion Product Descriptions | Amazon Web Services

In the realm of online retail, generating high-quality product descriptions for numerous products is a crucial yet time-consuming task. Leveraging machine learning (ML) and natural language processing (NLP) to automate the process of creating product descriptions has the potential to streamline operations and enhance the searchability of ecommerce platforms. By using ML and NLP, ecommerce … Read more

Cost-Effective Multi-Tenant LoRA Serving Made Efficient with Amazon SageMaker on Amazon Web Services

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Cost-Effective Multi-Tenant LoRA Serving Made Efficient with Amazon SageMaker on Amazon Web Services

In the ever-evolving realm of artificial intelligence (AI), the emergence of generative AI models has paved the way for personalized and intelligent experiences. Organizations are harnessing these language models to drive innovation and enhance their services, ranging from natural language processing to content generation. To effectively leverage generative AI models in an enterprise setting, custom … Read more