Term
Foundation Model
Definition
A Foundation Model is a type of artificial intelligence that has been taught using huge amounts of data. It is versatile and adapts to a variety of tasks.
Where you’ll find it
This model is commonly integrated into the core systems of AI platforms. Depending on the platform, it might be available across all user plans or restricted to premium versions.
Common use cases
- Adapting the model to perform specific tasks like speech recognition or text translation.
- Using it as a base to develop more specialized AI models for particular industries or needs.
- Enhancing existing applications with AI capabilities without starting from scratch.
Things to watch out for
- May require additional fine-tuning to handle very specialized or uncommon tasks effectively.
- Its adaptability can vary based on how it was originally trained and the quality of the data used.
- There might be limitations in accessing this model on lower-tier plans of some AI platforms.
Related terms
- Machine Learning
- Neural Networks
- Pre-trained Models
- Data Training
- Model Fine-tuning
Pixelhaze Tip: To get the most out of a Foundation Model, start by identifying the areas where your task overlaps with the training data of the model. This helps in leveraging its strengths while minimizing the need for extensive retraining.