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Automate Amazon SageMaker Pipelines DAG creation

Favorite Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we present a framework for automating the creation of a directed acyclic graph (DAG) for Amazon SageMaker Pipelines based on simple configuration files. The framework code

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Shared by AWS Machine Learning February 29, 2024

Unlock personalized experiences powered by AI using Amazon Personalize and Amazon OpenSearch Service

Favorite OpenSearch is a scalable, flexible, and extensible open source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 license. Amazon OpenSearch Service is a fully managed service that makes it straightforward to deploy, scale, and operate OpenSearch in the AWS Cloud. OpenSearch uses

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Shared by AWS Machine Learning February 29, 2024

Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources

Favorite Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL. The

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Shared by AWS Machine Learning February 28, 2024

NTIA engages civil society on questions of open foundation models for AI, hears benefits of openness in the public interest

Favorite The recent US Executive Order on AI directs action for numerous federal agencies. This includes directing the National Telecommunications and Information Agency (NTIA*) to discuss benefits, risks and policy choices associated with dual-use foundation models, which are powerful models that can be fine-tuned and used for multiple purposes, with

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Shared by voicesofopensource February 28, 2024

Techniques and approaches for monitoring large language models on AWS

Favorite Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. However, as these models continue to grow in size and complexity, monitoring their performance and behavior has become increasingly challenging. Monitoring the performance and behavior

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Shared by AWS Machine Learning February 26, 2024