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Favorite This post serves as a step-by-step guide on how to set up lifecycle configurations for your Amazon SageMaker Studio domains. With lifecycle configurations, system administrators can apply automated controls to their SageMaker Studio domains and their users. We cover core concepts of SageMaker Studio and provide code examples of
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Shared by AWS Machine Learning November 27, 2024
Favorite Stock technical analysis questions can be as unique as the individual stock analyst themselves. Queries often have multiple technical indicators like Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Strength Index (RSI), and others. Answering these varied questions would mean writing complex business logic to unpack the query
Read More Shared by AWS Machine Learning November 27, 2024
Favorite This post is co-written with Curtis Maher and Anjali Thatte from Datadog. This post walks you through Datadog’s new integration with AWS Neuron, which helps you monitor your AWS Trainium and AWS Inferentia instances by providing deep observability into resource utilization, model execution performance, latency, and real-time infrastructure health,
Read More Shared by AWS Machine Learning November 27, 2024
Favorite This post is co-written with Adarsh Kyadige and Salma Taoufiq from Sophos. As a leader in cutting-edge cybersecurity, Sophos is dedicated to safeguarding over 500,000 organizations and millions of customers across more than 150 countries. By harnessing the power of threat intelligence, machine learning (ML), and artificial intelligence (AI),
Read More Shared by AWS Machine Learning November 27, 2024
Favorite The use of large language models (LLMs) and generative AI has exploded over the last year. With the release of powerful publicly available foundation models, tools for training, fine tuning and hosting your own LLM have also become democratized. Using vLLM on AWS Trainium and Inferentia makes it possible
Read More Shared by AWS Machine Learning November 27, 2024
Favorite With the rise of large language models (LLMs) like Meta Llama 3.1, there is an increasing need for scalable, reliable, and cost-effective solutions to deploy and serve these models. AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low
Read More Shared by AWS Machine Learning November 27, 2024
Favorite Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. This can occur when the model’s training data lacks the necessary information or when the model attempts to generate coherent responses by making logical inferences
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Favorite Thousands of companies worldwide use Salesforce to manage their sales, marketing, customer service, and other business operations. The Salesforce cloud-based platform centralizes customer information and interactions across the organization, providing sales reps, marketers, and support agents with a unified 360-degree view of each customer. With Salesforce at the heart
Read More Shared by AWS Machine Learning November 27, 2024
Favorite Amazon Web Services (AWS) is excited to be the first major cloud service provider to announce ISO/IEC 42001 accredited certification for AI services, covering: Amazon Bedrock, Amazon Q Business, Amazon Textract, and Amazon Transcribe. ISO/IEC 42001 is an international management system standard that outlines requirements and controls for organizations to
Read More Shared by AWS Machine Learning November 26, 2024
Favorite We’re excited to announce the availability of Meta Llama 3.1 8B and 70B inference support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. Meta Llama 3.1 multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models. Trainium and Inferentia, enabled by
Read More Shared by AWS Machine Learning November 26, 2024