Foundation Model
Large AI models trained on broad data that serve as the base for many applications, like GPT-4 or Gemini.
Definition
A foundation model is a large AI model trained on vast, diverse datasets that can be adapted for many different applications. These models serve as the "foundation" upon which specific tools and applications are built, either through fine-tuning or prompt engineering.
Examples include OpenAI's GPT-4, Google's Gemini, Anthropic's Claude, and Meta's Llama. Foundation models are characterized by their scale (billions of parameters), broad capabilities, and ability to transfer learning across tasks.
Why It Matters
Foundation models are the engines powering the AI tools marketers use daily. Understanding this landscape helps in evaluating AI tools, understanding their capabilities and limitations, and anticipating future developments.
As foundation models evolve, their improved capabilities cascade to all applications built on them—making it valuable to understand the underlying technology driving AI marketing tools.
Examples in Practice
GPT-4 is a foundation model that powers ChatGPT, Microsoft Copilot, and thousands of other applications through OpenAI's API.
A company fine-tunes a foundation model on their specific industry data to create a specialized AI assistant for their customer service team.