Deep Learning

Deep learning is based on neural networks with many layers that progressively refine patterns in data (image, audio, text). It powers computer vision, NLP, and generative systems.

The Transformer architecture is central to modern LLM systems. Training is compute-intensive and often runs on GPU or TPU. Compare with fine-tuning when adapting an existing model.

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Key characteristics

• Uses many neural-network layers to learn representations directly from large datasets.
• Is the foundation of modern progress in image, audio, language, and generative models.
• Often requires large datasets and significant compute for training, especially for larger models.