<ul><li>Artificial Intelligence (AI) is a broad concept enabling machines to perform human-like tasks such as decision-making and learning.</li><li>AI includes technologies like smart assistants, chatbots, and facial recognition systems.</li><li>Machine Learning (ML) is a subset of AI that allows machines to learn patterns from data without explicit programming.</li><li>ML involves data collection, model training, and making predictions based on learned patterns.</li><li>Types of ML include Supervised, Unsupervised, and Reinforcement Learning.</li><li>Deep Learning (DL) is an advanced form of ML that uses artificial neural networks to process complex patterns.</li><li>DL is used in image recognition, speech processing, self-driving cars, and AI-generated art.</li><li>AI = Systems mimicking human intelligence, ML = Technique for learning from data, DL = Advanced ML using neural networks.</li><li>Deep Learning is driving AI advancements, making machines appear more intelligent.</li><li>The future dominance of AI, ML, and DL is interconnected, with DL leading modern AI advancements.</li></ul>

Artificial Intelligence vs. Machine Learning vs. Deep Learning: What’s the Real Difference?

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