AWS

Package and deploy models faster with new tools and guided workflows in Amazon SageMaker

I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference …

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Use natural language to explore and prepare data with a new capability of Amazon SageMaker Canvas

Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, …

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Amazon SageMaker adds new inference capabilities to help reduce foundation model deployment costs and latency

Today, we are announcing new Amazon SageMaker inference capabilities that can help you optimize deployment costs and reduce latency. With the new inference capabilities, you can deploy one or more foundation models (FMs) on the same SageMaker endpoint and control how many accelerators and how much memory is reserved for each FM. This helps to …

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Leverage foundation models for business analysis at scale with Amazon SageMaker Canvas

Today, I’m excited to introduce a new capability in Amazon SageMaker Canvas to use foundation models (FMs) from Amazon Bedrock and Amazon SageMaker Jumpstart through a no-code experience. This new capability makes it easier for you to evaluate and generate responses from FMs for your specific use case with high accuracy. Every business has its …

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Introducing highly durable Amazon OpenSearch Service clusters with 30% price/performance improvement

You can use the new OR1 instances to create Amazon OpenSearch Service clusters that use Amazon Simple Storage Service (Amazon S3) for primary storage. You can ingest, store, index, and access just about any imaginable amount of data, while also enjoying a 30% price/performance improvement over existing instance types, eleven nines of data durability, and …

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Amazon SageMaker Clarify makes it easier to evaluate and select foundation models (preview)

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 …

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Evaluate, compare, and select the best foundation models for your use case in Amazon Bedrock (preview)

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 …

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Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity

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 …

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AWS Clean Rooms Differential Privacy enhances privacy protection of your users data (preview)

Starting today, you can use AWS Clean Rooms Differential Privacy (preview) to help protect the privacy of your users with mathematically backed and intuitive controls in a few steps. As a fully managed capability of AWS Clean Rooms, no prior differential privacy experience is needed to help you prevent the reidentification of your users. AWS …

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AWS Clean Rooms ML helps customers and partners apply ML models without sharing raw data (preview)

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 …

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