Last Updated on March 15, 2023 by Mavia

GPT-4, the long-awaited replacement for GPT-3, is eagerly anticipated as ChatGPT is still widely used and has already had one million downloads in the first few days since its debut. GPT-4, which will build on GPT-3 and the recently released ChatGPT, will have a number of new features and improvements that will give it an edge over its GPT predecessors.

Contents hide

1 What is GPT and what applications does it have?

2 GPT-3 vs Data-to-Text: What is the distinction?

3 What Is GPT-4 and When Will It Be Available?

4 What Will Differ Between GPT-4 And GPT-3, Its Forerunner?

4.1 Conclusion

What is GPT and what applications does it have?

Generative Pre-trained Transformer, or GPT, is a deep learning model that generates language that is similar to human speech. OpenAI, a research facility established in 2015 by Elon Musk and Sam Altman, created the NLP (natural language processing) architecture.

GPT and what applications To produce language representations that are human-like, GPT makes use of a vast corpus of data. A variety of sentence endings can be offered by this language model, which learns from previously written text. Hundreds of billions of words, or a sizable percentage of the internet, have been used to train it. These words include the entirety of the English Wikipedia corpus, many books, and an overwhelming amount of webpages.

GPT is useful for many different jobs and real-world situations, like summarising, answering questions, translating, analysing markets, and many other things.

The GPT-3 is the most recent model in the GPT series. Data-to-text, however, is a significant language model that also produces texts on demand. But how do these two models differ from one another, and in what situations do they apply?

GPT-3 vs Data-to-Text: What is the distinction?

Data-to-text and GPT-3 are both NLG technologies. Natural language text is automatically generated and is referred to as “NLG” (Natural Language Generation). They could appear pretty similar at first, yet they operate extremely differently.

Data-to-text is utilised in e-commerce, the financial and pharmaceutical industries, as well as in the media and publishing industries.

GPT-3 can be useful for inspiration and brainstorming, for instance, if the user is experiencing writer’s block. It is also very helpful to employ GPT-3 in chatbots to respond to frequently asked questions from customers, as having people produce the text output is wasteful and unfeasible.

What Is GPT-4 and When Will It Be Available?

The most recent GPT iteration, GPT-4, was created by OpenAI. The GPT-4 is being trained on an enormous quantity of data, just like the other GPTs, and will be able to produce text that resembles human speech for a variety of applications. It is anticipated that it will be able to create blog posts, reports, and news stories of the highest calibre.

The GPT-4 will be released the week of March 13, 2023, according to Andreas Braun, CTO of Microsoft Germany, at a recent Event, despite the fact that developer OpenAI has not publicly confirmed a release date. On March 16, Microsoft CEO Satya Nadella will appear at a Microsoft event titled “The Future of Work with AI,” leading some to believe that GPT-4 may be unveiled at that time. Microsoft and OpenAI work closely together, and Microsoft also has exclusive GPT-3 rights.

What Will Differ Between GPT-4 And GPT-3, Its Forerunner?

Expectations for GPT-4 are high because GPT-3 has already made a significant impact with its capabilities since its debut in 2020. A lot of the information has been kept a secret by OpenAI, but some information has gotten out. In short, processing more complicated tasks with greater accuracy, scalability, and alignment are said to be the benefits of GPT-4 over GPT-3 and ChatGPT. This will make a greater variety of applications possible.

Conclusion

The number of parameters it has been trained with is where GPT-3 and GPT-4 most significantly diverge. The largest language model ever constructed up to this point, GPT-3 has been trained with 175 billion parameters. GPT-4, in contrast, is probably going to have 100 trillion parameters in its training process. In terms of language and logic, some contend that this will bring the language model closer to how the human brain functions.