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{{TaleHeader|'''AI in healthcare}} | {{TaleHeader|'''AI in healthcare}} | ||
[[File:Department_of_the_Air_Force_launches_NIPRGPT_(240607-F-AF000-1002).jpg|thumb|GEN AI]] | [[File:Department_of_the_Air_Force_launches_NIPRGPT_(240607-F-AF000-1002).jpg|thumb|GEN AI]] | ||
[[Artificial intelligence]] (AI) has made transformative impacts across various sectors, with tools like [[ChatGPT]] and [[Google Gemini]] enabling the generation of human-like text and images. These advancements have enhanced industries such as [[customer service]] and [[content creation]]. However, AI models face a growing concern known as [[model collapse]] | [[Artificial intelligence]] (AI) has made transformative impacts across various sectors, with tools like [[ChatGPT]] and [[Google Gemini]] enabling the generation of human-like text and images. These advancements have enhanced industries such as [[customer service]] and [[content creation]]. However, AI models face a growing concern known as [[model collapse]] as outlined in the following [https://www.forbes.com/sites/bernardmarr/2024/08/19/why-ai-models-are-collapsing-and-what-it-means-for-the-future-of-technology/ Forbes article]. AI model collapse refers to the gradual degradation of model performance, resulting in increasingly unreliable outputs. To combat this, novel approaches such as [[Retrieval-Augmented Generation]] ([[RAG]]) have been introduced using human moderated content platforms such as [[WikiMD]], enhancing AI's ability to generate more accurate and relevant responses by integrating information retrieval techniques. | ||
==Retrieval-Augmented Generation (RAG) Model in Healthcare== | ==Retrieval-Augmented Generation (RAG) Model in Healthcare== | ||
Revision as of 05:17, 24 February 2025
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Use of AI in healthcare
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Artificial intelligence (AI) has made transformative impacts across various sectors, with tools like ChatGPT and Google Gemini enabling the generation of human-like text and images. These advancements have enhanced industries such as customer service and content creation. However, AI models face a growing concern known as model collapse as outlined in the following Forbes article. AI model collapse refers to the gradual degradation of model performance, resulting in increasingly unreliable outputs. To combat this, novel approaches such as Retrieval-Augmented Generation (RAG) have been introduced using human moderated content platforms such as WikiMD, enhancing AI's ability to generate more accurate and relevant responses by integrating information retrieval techniques.
Retrieval-Augmented Generation (RAG) Model in Healthcare
The Retrieval-Augmented Generation (RAG) model is an advanced artificial intelligence (AI) framework designed to enhance the performance of large language models (LLMs) by combining them with an information retrieval (IR) system. This hybrid model enables LLMs to search and retrieve relevant information from an external corpus or knowledge base, enhancing the quality and relevance of their responses. Learn more
