OpenAI and Large Language Models (LLMs)

What is a large language model (LLM)?

A language model is a computer program trained to process and understand human language. LMs can be of varying complexity, from simple statistical models to advanced neural networks. A large language model (LLM) is an advanced deep learning algorithm proficient in handling various natural language processing (NLP) tasks. These models, employing transformer architectures, undergo extensive training with vast datasets, hence the term “large.” This training equips them to discern, translate, forecast, or produce text and diverse content. Often synonymous with neural networks (NNs), large language models share a foundation with computing systems inspired by the intricate workings of the human brain. These neural networks operate through layered nodes, resembling the structure of neurons.

LLMs have both an encode­r and a decoder. With these­, information is cut into small chunks, known as “tokens.” Then, it’s proce­ssed using mathematical functions. These calculations de­pict how each token connects to othe­r tokens in the text. This allows the­ system to detect patte­rns, similar to how a human brain would do if given the right question.

Transformer models are special because they use a cool trick called self-attention mechanisms. This method helps the system learn faster than traditional models like long short-term memory (LSTM). Thanks to self-attention, the transformer model can study all parts of a sequence. This helps it understand the full context of a sentence and make smarter guesses about what comes next.

Popular LLMs

Large language models have gained attention across industries. Prominent language models that are receiving recognition include:

• Bidirectional Encoder representations from ...