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Using task-specific models from AI21 Labs on AWS

AWS Machine Learning Blog

In this blog post, we will show you how to leverage AI21 Labs’ Task-Specific Models (TSMs) on AWS to enhance your business operations. You will learn the steps to subscribe to AI21 Labs in the AWS Marketplace, set up a domain in Amazon SageMaker, and utilize AI21 TSMs via SageMaker JumpStart. Limits are account and resource specific.

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Amazon Web Services (AWS) Benefits of Cloud-Based Enterprises

Smart Data Collective

Gartner conducted a survey of nearly 270 tech company leaders, which showed that cloud technology was the biggest investment for innovation in 2021. One of the best known options is Amazon Web Services (AWS). What is Amazon Web Services (AWS)? AWS is a collection of remote computing services (or web services). AWS Lambda.

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Unlocking Innovation: AWS and Anthropic push the boundaries of generative AI together

AWS Machine Learning Blog

Looking back to 2021, when Anthropic first started building on AWS, no one could have envisioned how transformative the Claude family of models would be. In addition, proprietary data is never exposed to the public internet, never leaves the AWS network, is securely transferred through VPC, and is encrypted in transit and at rest.

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Accelerating query performance with watsonx.data Presto C++ and Intel Sapphire Rapid Processor on AWS

IBM Journey to AI blog

The long-standing partnership between IBM and Intel has led to significant advancements in database performance over the past 25 years. Try IBM watsonx.data to experience the future of data * Note: This claim is based on IBM internal testing of Presto C++ v0.286 on a AWS r7iz.4xlarge TB Memory, Up to 12.5 TB Memory, 528.2

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Connecting AWS SageMaker to SnowFlake

Mlearning.ai

We may use AWS SageMaker to preprocess data, train model and make inferences. In this tutorial, I would like to show you a step-by-step method on how to connect AWS SageMaker with the Snowflake environment. But it’s good practice to have a service account that we can store in AWS either in secret key or parameter store.

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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

This post dives deep into Amazon Bedrock Knowledge Bases , which helps with the storage and retrieval of data in vector databases for RAG-based workflows, with the objective to improve large language model (LLM) responses for inference involving an organization’s datasets.

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ISO 42001: A new foundational global standard to advance responsible AI

AWS Machine Learning Blog

At AWS, we remain committed to harnessing AI responsibly, working hand in hand with our customers to develop and use AI systems with safety, fairness, and security at the forefront. About the authors Swami Sivasubramanian is Vice President of Data and Machine Learning at AWS.

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