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Generative AI

Models that create new content — text, images, audio, video, and code — rather than only classifying it.

Most computer programs sort things: is this email spam or not? Generative AI does the opposite — it makes brand-new things that never existed before: paragraphs of writing, pictures, songs, video, even working computer code.

Think of a musician who has listened to thousands of songs. They can't replay any single one perfectly, but they've soaked up the patterns — how melodies rise and fall, how choruses repeat. Ask them to improvise something new and they can, because they've learned the underlying style.

These models learn the same way. They study enormous piles of examples until they grasp the patterns inside them, then use those patterns to produce something fresh when you ask. You give a short instruction — a prompt — and the model fills in the rest, one small piece at a time, guessing what fits best.

The main ideas

  • Foundation models — Large models pre-trained on broad data and adapted to many downstream tasks.
  • Text generation — LLMs writing, summarizing, translating, and reasoning.
  • Image, audio & video generation — Diffusion and transformer models for creative and design work.
  • Code generation — Models that write and edit software from natural language.
  • Multimodal generation — Systems that mix modalities — text-to-image, image-to-text, any-to-any.

NLP & Large Language Models · Computer Vision · Speech & Audio AI · Building with AI

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