
AWS » Machine Learning
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The following section of AWS features articles on Machine Learning. Amazon Web Services (AWS) is a dynamic, growing business unit within Amazon.com. Subscribe us to get articles about machine learning from Amazon Web Services.
AWS » Machine Learning
2h ago
In this post, we explore how to use Amazon Bedrock to generate synthetic training data to fine-tune an LLM. Additionally, we provide concrete evaluation results that showcase the power of synthetic data in fine-tuning when data is scarce ..read more
AWS » Machine Learning
2h ago
Researchers developed Medusa, a framework to speed up LLM inference by adding extra heads to predict multiple tokens simultaneously. This post demonstrates how to use Medusa-1, the first version of the framework, to speed up an LLM by fine-tuning it on Amazon SageMaker AI and confirms the speed up with deployment and a simple load test. Medusa-1 achieves an inference speedup of around two times without sacrificing model quality, with the exact improvement varying based on model size and data used. In this post, we demonstrate its effectiveness with a 1.8 times speedup observed on a sample data ..read more
AWS » Machine Learning
2h ago
This blog post explores LLM-as-a-judge on Amazon Bedrock Model Evaluation, providing comprehensive guidance on feature setup, evaluating job initiation through both the console and Python SDK and APIs, and demonstrating how this innovative evaluation feature can enhance generative AI applications across multiple metric categories including quality, user experience, instruction following, and safety ..read more
AWS » Machine Learning
2h ago
In this post, we explore the movement of RAG applications from their proof of concept or minimal viable product (MVP) phase to full-fledged production systems. When transitioning a RAG application from a proof of concept to a production-ready system, optimization becomes crucial to make sure the solution is reliable, cost-effective, and high-performing ..read more
AWS » Machine Learning
20h ago
We are excited to announce that Meta’s Segment Anything Model (SAM) 2.1 vision segmentation model is publicly available through Amazon SageMaker JumpStart to deploy and run inference. Meta SAM 2.1 provides state-of-the-art video and image segmentation capabilities in a single model. In this post, we explored how SageMaker JumpStart empowers data scientists and ML engineers to discover, access, and deploy a wide range of pre-trained FMs for inference, including Meta’s most advanced and capable models to date ..read more
AWS » Machine Learning
1d ago
We are excited to announce that the Falcon 3 family of models from TII are available in Amazon SageMaker JumpStart. In this post, we explore how to deploy this model efficiently on Amazon SageMaker AI ..read more
AWS » Machine Learning
1d ago
In this post, we present a streamlined approach to deploying an AI-powered agent by combining Amazon Bedrock Agents and a foundation model (FM). We guide you through the process of configuring the agent and implementing the specific logic required for the virtual meteorologist to provide accurate weather-related responses ..read more
AWS » Machine Learning
1d ago
In this post, we demonstrate how to build a knowledge base solution by integrating enterprise data with Amazon Q Business using Amazon S3. This approach helps organizations improve operational efficiency, reduce response times, and gain valuable insights from their historical data. The solution uses AWS security best practices to promote data protection while enabling teams to create a comprehensive knowledge base from various data sources ..read more
AWS » Machine Learning
1d ago
GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. In this post, we demonstrate how GraphBolt enhances GraphStorm’s performance in distributed settings. We provide a hands-on example of using GraphStorm with GraphBolt on SageMaker for distributed training. Lastly, we share how to use Amazon SageMaker Pipelines with GraphStorm ..read more
AWS » Machine Learning
2d ago
The mission of Rich Data Co (RDC) is to broaden access to sustainable credit globally. Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. In this post, we discuss how RDC uses generative AI on Amazon Bedrock to build these assistants and accelerate its overall mission of democratizing access to sustainable credit ..read more