Deep Learning

Deep learning is a subset of machine learning that uses artificial neural networks with many layers (hence "deep") to learn complex patterns from large amounts of data. It has driven the most significant AI breakthroughs of the past decade.

Deep learning excels at tasks involving perception (images, audio, text) and generation (creating text, images, code). Key architectures include: transformers (GPT, BERT for text), convolutional neural networks (CNNs for images), recurrent neural networks (RNNs for sequences), and diffusion models (for image generation).

The transformer architecture, introduced in 2017, revolutionized the field and underlies modern large language models. Its attention mechanism enables models to process long-range dependencies in data, leading to breakthroughs in language understanding and generation.