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February 6, 2024

GPT-4: A complete Guide to understanding its functionalities

GPT-4 is a tremendously useful tool for businesses and software developers due to its ability to improve natural language processing and code generation.

We analyze its benefits, use cases, and latest updates and give you tips on how to get the most out of it for your business.

What is GPT-4?

GPT-4 is the latest model in the GPT (Generative Pre-trained Transformer) family. And what is a GPT? It is an LLM (Large Language Model), i.e., a type of artificial intelligence that uses Deep Learning to imitate human language. The aim is to generate meaningful data by predicting the next word that will follow the previous one in a text.

They are a new way to create a customized version of ChatGPT to make life easier for your users. No coding is required to create your own GPT easily. In fact, creating one is as easy as starting a conversation, giving it additional instructions and knowledge, and choosing what it can do.

It has a higher learning capacity thanks to the inclusion of more data for training and an architecture with a larger number of parameters. The model can compose songs, write scripts, develop software, or learn the user’s writing style with much higher accuracy and quality than previous versions. In addition, thanks to its multimodal nature, it also accepts images as input, which greatly extends its capabilities.

How does GPT-4 work?

GPT-4 is an LVM that processes images and text as input and generates text as output. It uses an architecture based on Transformer, a model consisting of blocks of stacked decoders that use different neural networks and incorporate the attention mechanism.

The training and alignment process of the model consists of two steps:

  1. The model is trained on a large amount of multimodal data, including images and text from different domains and sources. This data is obtained from various public repositories, and the objective is to predict the next token in a document, given a sequence of previous tokens and optional images.
  2. After training, the model is aligned with a manually labeled dataset containing verifiable facts and desired behaviors. These data are obtained from reliable sources, such as encyclopedias, textbooks, and professional guides. This alignment aims to adjust the model’s parameters so that its outputs are more factual and adherent to the desired behaviors.

GPT-3 vs. GPT-4 | Diferences

The main difference between one version and the other is that GPT-4 is a model that processes images and text as input, something that previous versions could only do with text.

Also, the new version has gone from sending 4096 tokens to the API to 32,000 tokens. This is a major step forward, as it facilitates the creation of increasingly complex and specialized texts and conversations.

GPT-4 has a larger training set volume than GPT-3, from a training set with 17 GB of data to 45 GB.

In addition, problem-solving capabilities have been improved by offering greater responsiveness with solutions and text generation that mimics the style and tone of the context.

GPT-4 Updates


This is an LVM (Large-scale Visual linguistic Model) that allows the user to upload an image as input and converse with the model. Instructions or questions can be given to direct the model to perform tasks based on the information provided in the form of the image.

It builds on the existing capabilities of GPT-4 and provides visual analysis in addition to the existing text interaction functions.

Its main capabilities are:

  • Visual input: accepts visual content such as photographs, screenshots, and documents.
  • Object detection and analysis: can identify and provide information about objects within images.
  • Data analysis: proficient in interpreting and analyzing data presented in visual formats such as graphs, tables, and other data visualizations.
  • Text decoding: is able to read and interpret handwritten notes and text within images.

It is a model that can be applied to numerous use cases, such as in academic research involving historical manuscripts, where it is time-consuming for expert palaeographers and historians to decipher them.

It is also very useful when writing code for a website from an image with the required layout. It can even be applied to the interpretation of data through graphical images, from which it can extract the underlying data and provide key information.

GPT-4 Turbo

GPT-4 Turbo takes generative AI a step further for several reasons:

  • New knowledge limit: the message that the information collected by ChatGPT has a cut-off date of September 2021 is coming to an end. The new model includes information up to April 2023, providing a much more current query context.
  • Longer indications: Long and detailed indications will no longer be a problem, as it now supports up to 128,000 context tokens. This would correspond to about 300 pages of a book, which opens up the paradigm even further.
  • Better instruction tracking: This model works better than previous models for tasks that require careful tracking of instructions, such as generating specific formats.
  • Multiple tools in a chat: the updated GPT-4 chatbot chooses the appropriate tools from the drop-down menu.

How to get the most out of GPT-4?

One of the main advantages of GPT-4 and ChatGPT is that the model is already trained, so it helps you to search for information in business documents and systems in an agile and efficient way. This translates into reduced costs, less time spent searching for information in different documents, and improved process efficiency and employee productivity.

However, there are certain more complex use cases that will require fine-tuning of the model that involves training, where a specialized partner will have to come into action. At Plain Concepts, we offer you a unique OpenAI adoption solution, where you will have access to a program that will help you incorporate and leverage the benefits of generative AI in your organization.

From training, ideation, development, and deployment of use cases based on GPT models, we will help you design and implement the strategy and roadmap of use cases that bring value to your business and are aligned with your goals. If you want to exploit the full potential of generative AI in your business, don’t wait any longer to contact us!

Elena Canorea
Elena Canorea
Communications Lead