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How Q4 Inc. used Amazon Bedrock, RAG, and SQLDatabaseChain to address numerical and structured dataset challenges building their Q&A chatbot

Flipboard

We discuss model selection and prompt engineering and optimization later in this post, but it’s worth noting that for the query generation stage, we noticed that Claude Instant was able to produce comparable results, especially when the user question is well phrased and not as sophisticated.

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Training Sessions Coming to ODSC APAC 2023

ODSC - Open Data Science

More confirmed sessions include Introduction to Large Lange Models (LLMs) | ODSC Instructor Introduction to Data Course | Sheamus McGovern | CEO and Software Architect, Data Engineer, and AI expert | ODSC Advanced NLP: Deep Learning and Transfer Learning for Natural Language Processing | Dipanjan (DJ) Sarkar | Lead Data Scientist | Google Developer (..)

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Educating a New Generation of Workers

O'Reilly Media

Examples of these skills are artificial intelligence (prompt engineering, GPT, and PyTorch), cloud (Amazon EC2, AWS Lambda, and Microsoft’s Azure AZ-900 certification), Rust, and MLOps. A higher completion rate could indicate that the course teaches an emerging skill that is required in industry.

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Exploring data using AI chat at Domo with Amazon Bedrock

AWS Machine Learning Blog

This enables Domo to optimize model performance through prompt engineering, preprocessing, and postprocessing, and provide contextual information and examples to the AI system. In the following video, Joe Clark, Software Architect at Domo, shares how AWS has been instrumental for Domo in the generative AI space.