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Artificial intelligence (AI) is rapidly transforming healthcare by leveraging machine learning techniques to analyze medical images, patient data, and genetic information with unprecedented speed and accuracy, significantly improving early disease detection and enhancing diagnostic precision.

AI-Powered Health Diagnostics

Fine-tuning large language models adapts pre-trained models to specific tasks or domains using tailored datasets, while Retrieval-Augmented Generation (RAG) combines retrieval systems with generative models to dynamically incorporate external, up-to-date knowledge into outputs.

RAG vs Fine-Tuning: Differences, Benefits, and Use Cases Explained

A team of MIT CSAIL researchers have developed a novel approach to robot training that could significantly accelerate the deployment of adaptable, intelligent machines in real-world environments.

Can robots learn from machine dreams?

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