13 Oct Applications of Retrieval Augmented Generation (RAG)

RAG is a powerful tool across various domains. It is used not only for content but also for customer support, chatbots, etc. Let us see the applications of RAG:

1. Accurate Answers RAG can provide detailed and accurate answers to complex questions by retrieving relevant information and
   generating a coherent response.
2. Chatbots: Enhances the ability of chatbots to provide more contextually accurate and informative responses.
3. Creating content: Assists in generating articles, summaries, and reports by retrieving relevant content and synthesizing it into
   new, coherent text.
4. Customer Support Systems: Assists customer support systems in fetching relevant troubleshooting steps and providing personalized solutions to users’ issues.
5. Diagnosis and treatment options: Combines patient symptoms with medical literature to provide potential diagnoses and treatment options.
6. Legal Documents: Retrieves and summarizes legal documents, case laws, and statutes relevant to a particular query.
7. Educational Material: Generates detailed explanations and study guides by retrieving and synthesizing information from
   educational resources.
8. E-commerce recommendations: Enhances product recommendations by retrieving and generating detailed descriptions based on user
   preferences and queries.

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• What is Machine Learning
• What is a Machine Learning Model
• Types of Machine Learning
• Supervised vs Unsupervised vs Reinforcement Machine Learning
• What is Deep Learning
• Feedforward Neural Networks (FNN)
• Convolutional Neural Network (CNN)
• Recurrent Neural Networks (RNN)
• Long short-term memory (LSTM)
• Generative Adversarial Networks (GANs)