What is GPT?

GPT, which stands for Generative Pre-trained Transformer, is a series of large language models developed by OpenAI that have been central to the public breakthrough of AI into mainstream consciousness. GPT-2 (2019) demonstrated surprisingly capable text generation. GPT-3 (2020) stunned researchers with its few-shot learning abilities. GPT-4 (2023) introduced multimodal capabilities and achieved near-human performance on professional examinations.

The GPT architecture is a decoder-only transformer. It is trained to predict the next token in a sequence, processing text from left to right. Through this deceptively simple training objective on internet-scale data, GPT models develop broad knowledge of language, facts, coding, reasoning, and much more. The pre-training phase uses unsupervised learning on hundreds of billions of words.

Raw pre-trained GPT models are then refined through additional training to make them useful and safe products. Fine-tuning on human-written examples of helpful responses shapes the model's style and knowledge. Reinforcement learning from human feedback (RLHF) trains the model to produce outputs that human raters prefer, making it more helpful, less likely to generate harmful content, and better at following instructions. This is how ChatGPT is built on top of GPT-4.

GPT's API has enabled thousands of products to be built on top of OpenAI's models. Application developers can send prompts to the API and receive generated text, powering everything from customer service bots to coding assistants to creative writing tools. The rise of the GPT API ecosystem represents a new era in software development, where AI language capabilities are a commodity that can be accessed and integrated like any other API.

Understanding GPT's capabilities and limitations is valuable for any professional using AI tools. GPT models are excellent at drafting, explaining, summarizing, translating, and reasoning through problems - but they can hallucinate facts, have a knowledge cutoff date, and should not be trusted for high-stakes tasks without human verification. Effective use combines GPT's generative power with human expertise and critical judgment.