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Core AI and ML concepts, theory, and evolution
Unsupervised learning is a machine learning technique where algorithms find patterns in data without being told what to look for. You don’t label examples. You don’t define categories upfront. You point the algorithm at your data and let it figure…
Supervised learning is a machine learning technique where you train a model using data that already has the right answers attached. Think of it as teaching by example. You show the algorithm input data paired with correct outputs, and it…
Narrow AI is artificial intelligence designed to handle specific tasks. It powers the AI applications you interact with every day, from email spam filters to streaming recommendations to voice assistants. Unlike hypothetical general AI that could match human intelligence across…
Responsible AI refers to the practice of designing, deploying, and managing artificial intelligence systems in a way that is ethical, transparent, accountable, and aligned with human values.
Generative AI is artificial intelligence that makes things. You give it a text prompt, it writes an essay. Describe an image, it draws one. It produces code, music, videos, and more. Traditional AI analyses data or makes predictions. Generative AI…
A Large Language Model (LLM) is a type of artificial intelligence designed to understand, generate, and interact with human language. Trained on massive amounts of text data, LLMs use deep learning techniques to identify linguistic patterns, predict text sequences, and…
Latent space refers to the hidden, multidimensional representation of data that a machine learning model learns during training. It’s where complex, high-dimensional information such as images, text, or sounds is compressed into numerical vectors that capture underlying patterns, relationships, and…
Machine Learning (ML) is a branch of artificial intelligence that enables systems to automatically learn from data and improve their performance over time without being explicitly programmed. Instead of following fixed rules, ML algorithms identify patterns, make predictions, and adapt…
Natural Language Processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language. It bridges the gap between human communication and machine understanding, powering everything from chatbots and virtual assistants to sentiment analysis…
Deep Learning (DL) is a subset of machine learning that uses artificial neural networks to model complex patterns and representations in large datasets. It powers many of today’s most advanced AI systems, including image recognition, natural language processing, and speech…