AI-based bots Generative Pre-trained Transformers use artificial neural networks and are capable of simulating text and speech of human beings, responding to queries, generating content and translating from one language to another-language.

GPT-1 was discussed as a natural language understanding model in a paper by OpenAI in 2018 and was just ‘a proof of concept’ never released for the masses. GPT-2 was released in 2018 by OpenAI to ML-community, and had limited application in text generation. In 2020, OpenAI released GPT-3, with 100 times more parameters than GPT-2 and used a vast data base for its training. There were additional changes that led to GPT-3.5 which now powers ChatGPT. GPT-4 is the latest. It is more creative and collaborative. It can tackle difficult problems with greater accuracy. It can edit and iterate with users. It responds not only to text but also to images. Though better than previous versions, it is not perfect. Its results of factual accuracy are better. It could be steered well, and does not cross the guard-rails. GPT-4 is capable of generating captions, classifications and analysis for images. It can handle thousands of words of text from the user. Thus it better understands the context. It can ferret out documents and analyse them.

It has limitations of biases and responds to adversarial prompts. There is still more work to be done.

It is a big leap from GPT-3.5 as it is iterative in conversation. In complex tasks, the difference between GPT-3.5 and GPT-4 can be noticed.

Microsoft Azure trained the model. The new Bing-AI already uses GPT-4. It will soon be available for paying users. It could be integrated to participating organisations’ products.