What is a foundation model used for?#
Foundation models provide a powerful, pre-built starting point. This allows a company to significantly reduce development time and cost by fine-tuning the general model for their specific purpose, rather than starting from zero.
How does a foundation model work?#
A foundation model is first trained on a huge, diverse dataset, such as vast portions of the internet and digital books. This initial "pre-training" phase teaches the model general patterns, language, reasoning ability, and broad knowledge about the world, without being aimed at any single task. Think of this as giving the AI a comprehensive, general education.
After this core training is complete, the model can then be specialised for a particular business need through a process called "fine-tuning." This involves giving it additional, focused training on a much smaller dataset relevant to your goal, such as your company's internal support documents or past marketing copy. This second step adapts the model's general knowledge to excel at your specific application.
How is a foundation model different from traditional AI?#
A foundation model is a general-purpose tool that can be adapted for many jobs, much like a versatile software platform that can be configured for different business functions. In contrast, traditional AI models were single-purpose; they were built from the ground up to do only one specific thing, like identifying spam email or forecasting sales for a single product line. Creating a traditional model was like commissioning custom software that could only ever perform one, unchangeable task.