Scaling Laws For Large Language Models
The relationship between a large language model’s (LLM) performance and the resources used during training, including the size of the model, amount of data, and computation.
Areas of application
- Natural Language Processing
- Machine Learning
- Artificial Intelligence
- Computer Science
- Data Science
Example
A study on the scaling laws of a state-of-the-art LLM shows that as the model size increases, its performance on a given task improves exponentially, but at an increasing cost in terms of training time and computational resources.