Enhancing LLM Reasoning and Precision Using RAG and ReAct on AWS by Begum Firdousi Abbas
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 Published On Feb 13, 2024

Large Language Models (LLMs) are pivotal in Generative AI applications, yet they represent only one piece of the puzzle in constructing robust and comprehensive applications. However, these LLMs often face the challenge of hallucinating information, leading to inaccurate responses and necessitating more informed actions. To mitigate this, tools are being developed to augment the capabilities of LLMs for improved reasoning and more precise results. The ReAct framework, dedicated to promoting responsible AI, merges the power of reasoning and action, enabling models to achieve this objective effectively. Join this session to explore an e-commerce shopping assistant that leverages embedding and vector databases in tandem with LLMs, creating a powerful platform for elevated product discovery and customer support. This is all orchestrated by the ReAct framework, in conjunction with AWS Generative AI services, to enhance LLM capabilities, foster better decision-making, and secure a competitive market advantage

Begum Firdousi Abbas
Amazon Web Services (AWS)

Recorded at Jfokus 2024 in Stockholm 6th of february
http://www.jfokus.se

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