A large language model (LLM) is a large-scale language model notable for its ability to achieve general-purpose language understanding and generation.
As autoregressive language models, they work by taking an input text and repeatedly predicting the next token or word
LLMs acquire these abilities by using massive amounts of data to learn billions of parameters during training and consuming large computational resources during their training and operation. LLMs are artificial neural networks (mainly transformers) and are (pre)trained using self-supervised learning and semi-supervised learning.
- Scale and Complexity
- Versatility in Language Understanding
- Challenges and Ethical Considerations
Large language model bias and limitations are ongoing research in the field of natural language processing (NLP)
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