Definition

Pretraining is when an AI model is trained on a large amount of general data before it's used for a specific job. This helps the model learn basic skills like grammar, image features, or patterns before being fine-tuned for something more focused.

Example

Models like GPT-4 are pretrained on internet text before learning to follow specific instructions.

How It’s Used in AI

Pretraining builds strong base models that can later be fine-tuned. It’s used in language models, vision models, and speech tools. Pretraining saves time because the AI already knows a lot before it starts learning your exact task.

Brief History

Pretraining became essential in the 2010s with the rise of transformer models like BERT and GPT. These models showed that general learning followed by task-specific fine-tuning worked better than training from scratch.

Key Tools or Models

Examples include GPT-3, GPT-4, BERT, and CLIP. These models are pretrained on huge datasets and then reused across many tasks in AI products and tools.

Pro Tip

Pretraining makes AI smarter out of the box. But it's the fine-tuning that helps it work well in your domain or industry.