Pattern recognition: Through this training, the model learns to predict likely sequences of words and concepts based on context.
Statistical correlations: The model develops a complex web of statistical relationships between words, phrases, and concepts.
Emergent abilities: As the model grows in size and is exposed to more data, it can start to exhibit behaviors that resemble reasoning, such as:
- Answering questions by synthesizing relevant information
- Following multi-step instructions
- Generating logically structured text
Limitations: However, LLMs don't truly understand or reason in a human sense. They're essentially very sophisticated pattern matching systems.
This is a simplified explanation of a complex topic.