Context

In the world of AI, context isn’t just helpful—it’s everything. Whether it’s the billions of tokens in a language model’s attention mechanism, the rapidly shifting mosaic of user intent, or the structured metadata keeping facts grounded, context defines what AI can do. 1. A Foundation Built on Attention The 2017 paper “Attention Is All You Need” introduced the Transformer model, which revolutionized deep learning by letting models process all parts of a sequence in parallel using self-attention. No more recurrences—just powerful, context-aware computation. Since then, it’s become the backbone of modern models like GPT, BERT, and beyond. 1 ...