Definition
Generative Pre-trained Transformers, or GPT, are a family of neural network models that use the transformer architecture and is a key advancement in artificial intelligence (AI) powering generative AI applications such as ChatGPT. GPT models enable applications to create human-like text and content (images, music, and more), and answer questions in a conversational manner. Industries leverage GPT models and generative AI for Q&A bots, text summarization, content generation, and search [1].
For instance,
imagine a scenario of a seasoned trader at Onitsha Main Market who has spent 20
years observing thousands of customer interactions, bargaining conversations,
product descriptions, and market gossip. This trader wasn't taught a formal
script but absorbed patterns from countless daily transactions—learning how
customers ask for discounts ("Abeg, reduce the price small"), how
successful sales pitches sound, and how to predict what a customer wants next
based on their first few words. When a new customer approaches saying "I
need ankara fabric for...", the trader can intelligently complete the
sentence with "...wedding aso ebi?" or "...children's
clothing?" because they've seen similar patterns thousands of times.
Just like the above scenario, GPT was pre-trained on massive amounts of text from the internet, learning language patterns, context, and how humans communicate, so when you start typing a sentence, it predicts what should come next based on patterns it learned during training.
Origin
OpenAI Research
gave birth to the first GPT model called GPT-1 in 2018. Ever since then, they
have been several releases of the GPT line of AI models. The most recent GPT
model is GPT-4, which was released in early 2023. In May 2024, OpenAI announced
the multilingual and multimodal GPT-4o1, capable of processing audio, visual
and text inputs in real time [3].
Context and
Usage
The applications
of GPT models cuts across several domains including the following:
- Content Creation: GPT helps with creative works such as articles, stories and poetry.
- Customer Support: GPT are the drivers of Automated chatbots and virtual assistants that provide efficient and human-like customer service interactions.
- Education: GPT models can create personalized tutoring systems, generate educational content and assist with language learning.
- Healthcare: GPT play significant roles in tasks that involve generating medical reports, assisting in research by summarizing scientific literature and providing conversational agents for patient support.
- Programming: GPT's ability to generate code from natural language descriptions aids developers in software development and debugging [4].
Why it Matters
Generative
pre-trained transformers represent a major breakthrough in natural language
processing. The scale of compute and data used to pre-train them allows GPT
models to develop a comprehensive understanding of language structure and
content.
This knowledge is encoded in the models' parameters, letting them achieve state-of-the-art performance on many NLP tasks with minimal task-specific fine-tuning. Because of this, GPTs excel at free-form text generation. The models can produce remarkably human-like writing for creative and conversational applications. Their few-shot learning abilities eliminate much of the need for heavily customized training on new datasets, making GPTs flexible and widely applicable across many use cases without extensive re-engineering. GPTs' technical strengths in generative language modeling and transfer learning are enabling qualitatively richer NLP applications [5].
Related AI
Models and Architectures
- Hidden Layer: Intermediate layer in a neural network between input and output that processes data
- Large Language Model: AI model trained on massive text datasets to understand and generate human language
- Latent Space: Abstract mathematical space where AI models represent data in compressed, meaningful dimensions
- Mixture of Experts: Architecture that uses multiple specialized sub-models coordinated by a gating network
- Model: Mathematical representation that learns patterns from data to make predictions or decisions
In Practice
GPT-4.o is a
good real-life case study of a Generative Pre-trained Transformer in action.
Released in 2024, it is multilingual, supporting content in numerous
non-English languages. In addition to this, it is multimodal. That is, it has
the capability to process image, audio and video prompts while generating text,
images and audio content in response.
References
- AWS. (2026). What is GPT?
- TaskUs. (2024). What are Generative Pre-trained Transformers (GPT)?
- Belcic, I., Stryker, C. (n.d). What is GPT (generative pretrained transformer)?
- Geeksforgeeks. (2025). Introduction to Generative Pre-trained Transformer (GPT).
- MoveWorks.
(2026). What is a generative pre-trained transformer?