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Amazon Redshift puts artificial intelligence (AI) at your service to optimize efficiencies and make you more productive with two new capabilities that we are launching in preview today. First, Amazon Redshift Serverless becomes smarter. It scales capacity proactively and automatically along dimensions such as the complexity of your queries, their frequency, the size of the…
I’m happy to share that you can now evaluate, compare, and select the best foundation models (FMs) for your use case in Amazon Bedrock. Model Evaluation on Amazon Bedrock is available today in preview. Amazon Bedrock offers a choice of automatic evaluation and human evaluation. You can use automatic evaluation with predefined metrics such as…
I’m happy to share that Amazon SageMaker Clarify now supports foundation model (FM) evaluation (preview). As a data scientist or machine learning (ML) engineer, you can now use SageMaker Clarify to evaluate, compare, and select FMs in minutes based on metrics such as accuracy, robustness, creativity, factual knowledge, bias, and toxicity. This new capability adds…
I am happy to announce the general availability of Amazon Neptune Analytics, a new analytics database engine that makes it faster for data scientists and application developers to quickly analyze large amounts of graph data. With Neptune Analytics, you can now quickly load your dataset from Amazon Neptune or your data lake on Amazon Simple…
Today we are announcing a preview of Amazon OpenSearch Service zero-ETL integration with Amazon S3, a new way to query operational logs in Amazon S3 and S3-based data lakes without needing to switch between services. You can now analyze infrequently queried data in cloud object stores and simultaneously use the operational analytics and visualization capabilities…
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Today, we’re introducing AWS Clean Rooms ML (preview), a new capability of AWS Clean Rooms that helps you and your partners apply machine learning (ML) models on your collective data without copying or sharing raw data with each other. With this new capability, you can generate predictive insights using ML models while continuing to protect your sensitive…
Today, we are introducing Amazon SageMaker HyperPod, which helps reducing time to train foundation models (FMs) by providing a purpose-built infrastructure for distributed training at scale. You can now use SageMaker HyperPod to train FMs for weeks or even months while SageMaker actively monitors the cluster health and provides automated node and job resiliency by…
Today we are announcing the general availability of the vector engine for Amazon OpenSearch Serverless with new features. In July 2023, we introduced the preview release of the vector engine for Amazon OpenSearch Serverless, a simple, scalable, and high-performing similarity search capability. The vector engine makes it easy for you to build modern machine learning…
Read More “Vector engine for Amazon OpenSearch Serverless is now available” »
Today, we are announcing the general availability of vector search for Amazon DocumentDB (with MongoDB compatibility), a new built-in capability that lets you store, index, and search millions of vectors with millisecond response times within your document database. Vector search is an emerging technique used in machine learning (ML) to find similar data points to…
Today, we’re announcing the availability of Anthropic’s Claude 2.1 foundation model (FM) in Amazon Bedrock. Last week, Anthropic introduced its latest model, Claude 2.1, delivering key capabilities for enterprises such as an industry-leading 200,000 token context window (2x the context of Claude 2.0), reduced rates of hallucination, improved accuracy over long documents, system prompts, and…
Read More “Amazon Bedrock now provides access to Anthropic’s latest model, Claude 2.1” »
