Frontier Models
The terms "Frontier Model" and "Foundation Model" are actually quite similar, and sometimes even used interchangeably. They both refer to advanced AI models with some key distinctions:
Foundation Model:
This is the broader term. Foundation models are designed to be a general purpose base for various AI applications.
They can handle tasks involving text, images, or even a combination of both (multimodal).
Think of them as a powerful learning tool that can be adapted to many uses.
Examples of foundation models include large language models (LLMs) that focus on text, or large vision models (LVMs) that excel at image recognition.
Frontier Model:
This term emphasizes how advanced the model is. It refers to a subset of foundation models that are at the cutting edge of AI research.
These models are particularly powerful and capable.
There's no strict definition of what makes a model "frontier" but it often implies it has the potential for significant impact, positive or negative.
Here's an analogy: Imagine a toolbox. Foundation models are a set of very versatile tools you can use for many jobs. Frontier models are the top-of-the-line wrenches and screwdrivers in that toolbox - powerful for the right task, but potentially dangerous if misused.
In short:
All Frontier Models are Foundation Models, but not all Foundation Models are Frontier Models.
Foundation Model - Broad term for powerful, adaptable AI.
Frontier Model - A particularly advanced and powerful type of Foundation Model.