Understanding foundation models and the rise of LLMs
AI has undergone a fundamental transformation thanks to the emergence of foundation models—versatile, general-purpose models that can be adapted across a wide range of tasks. Among them, LLMs have taken center stage, redefining how we interact with machines through natural language.
From narrow AI to foundation models
Before the rise of foundation models, the field of AI was dominated by narrow AI—systems built to perform one specific task and nothing else. Each use case required a custom pipeline: a unique dataset, a dedicated model architecture, and a specialized training routine. If you wanted to classify emails as spam or not spam, you'd build a spam filter. If you needed to extract names and places from documents, you'd create a named entity recognizer. Want to summarize a news article? That would mean yet another bespoke model.This fragmented approach had several drawbacks. Models were brittle—performing...
