GPT in Plain English

GPT stands for Generative Pre-trained Transformer.

• Generative: The term “generative” refers to the model’s ability to create new content, such as articles, stories, or even code, based on the input it receives. Unlike models that only analyse existing data, GPT can generate human-like text that mimics natural language.
• Pre-trained: The “pre-trained” aspect indicates that GPT models undergo extensive training on vast amounts of text data from the internet. This training allows them to learn language patterns, grammar, and factual information. By the time they are ready for use, these models can predict the most likely next word or phrase in a sentence based on the context provided.
• Transformer: The “transformer” architecture is what makes GPT particularly powerful. It utilises a mechanism called self-attention, which enables the model to consider the relationships between all words in a sentence simultaneously.

Understanding Self-Attention

Self-attention helps the model focus on different words in a sentence to understand their context better. For example, in the sentence “The cat sat on the mat,” when analysing the word “sat,” the model pays special attention to “cat,” recognising it as the subject performing the action. It also considers nearby words like “the” and “on” to gather more context. This mechanism allows GPT to generate coherent and relevant responses by capturing important relationships between words.

This concept was introduced in detail in the paper “Attention Is All You Need” by Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, ?., & Polosukhin, I. (2017).

Transformers are Fast

One major advantage of transformers is their ability to perform parallel processing. Unlike older models that analyze one word at a time, transformers look at all words in a sentence simultaneously. This speeds up computations and improves efficiency. By processing multiple words at once, transformers can handle large amounts of data quickly, making them faster and more scalable. This capability allows GPT to respond rapidly and effectively to prompts.

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