AI (Artificial Intelligence), Machine Learning, Deep Learning, Generative AI (GenAI)

Category What Method Use Case
Artificial Intelligence The ability of machines to mimic intelligent human behavior. Utilizing advanced algorithms and models to achieve broad understanding and adaptability. Systems capable of performing intellectual tasks similar to humans (theoretical), adaptive learning systems, and multi-purpose robots.
Machine Learning AI applications that allow systems to automatically learn and improve from experience. Using statistical techniques to help machines improve through experience. Email spam filtering, product recommendations (e.g., Netflix, Amazon), predictive business analytics (e.g., sales forecasting).
Deep Learning Machine learning that uses complex algorithms and deep neural networks to train models. Leveraging multi-layer neural networks to learn from large datasets. Image recognition (e.g., medical imaging), speech recognition (e.g., Google Assistant), natural language processing (e.g., ChatGPT).
Generative AI A subset of AI that can generate new content based on training data. Using deep learning techniques to generate new data such as text, images, and music. Text generation (e.g., ChatGPT), image generation (e.g., DALL·E), music composition (e.g., OpenAI MuseNet).



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