Learn about the differences between ChatGPT models

21 de November de 2023

The evolution of OpenAI’s Generative Pretrained Transformer (GPT) language models has marked a significant milestone in the field of artificial intelligence and natural language processing. These models represent a revolution in the way machines understand and generate human language, offering capabilities ranging from generating coherent text to interacting in complex conversations and solving specific language-based tasks.

ChatGPT is not the same as GPT

There is often a common perception that GPT and ChatGPT are interchangeable or fundamentally the same, due to their shared origins in OpenAI technology. However, this assumption fails to recognise the significant differences and the specific purposes for which each is designed.

  • GPT: GPT models are artificial intelligence systems that have been trained in a general way to understand and generate text based on a wide range of data. They are not specifically designed to interact in conversations, but can be adapted for this purpose.
  • ChatGPT: ChatGPT, on the other hand, is a variant of GPT models optimised specifically for conversations. It uses additional training and adjustments to improve on aspects such as consistency of responses, context maintenance, relevance and the ability to follow instructions given in a dialogue. ChatGPT is effectively a specialised application of GPT technology to create a more fluid and human chat experience.

Differences between GPT models

Capabilities and limitations

  • GPT-3 and GPT-3.5: These models are primarily text-based natural language processing systems.
  • GPT-4: Introduces multimodal capabilities, processing text and images, and generating responses of over 25,000 words.
  • GPT-4 Turbo: Launched in November 2023, this model is an advanced version of GPT-4. It offers a 128K token context window (equivalent to over 300 pages of text), allowing text, image and text-to-speech input. It is trained with data up to April 2023, providing more up-to-date and accurate responses.

Creativity and content generation

  • GPT-3 and GPT-3.5: These models were innovative in their ability to generate text, but with limitations in terms of creativity and bias detection.
  • GPT-4: Presents significant improvements in creativity and text generation in prose and verse.
  • GPT-4 Turbo: Further optimises these capabilities, providing precise function parameters and allowing responses in specific formats such as JSON and XML.

Reduction of toxic and biased responses

  • GPT-4: Significantly reduces the generation of toxic and biased responses compared to GPT-3.5.
  • GPT-4 Turbo: Expected to continue this trend of reducing bias and improving information accuracy.

Technical and performance improvements

  • GPT-4: Although it outperforms GPT-3, the improvement is more focused on the quality of the architecture and data used in training.
  • GPT-4 Turbo: Offers improved performance at a lower cost, being three times cheaper for input tokens and twice cheaper for output tokens compared to GPT-4.

Hallucination and inaccurate data handling

  • GPT-3 and GPT-3.5: These models, although advanced, were still susceptible to false or inaccurate information.
  • GPT-4: Significantly improved in reducing AI “hallucinations” and information accuracy.
  • GPT-4 Turbo: These improvements are expected to continue, especially in handling more up-to-date information and generating long document summaries.

Integration and versatility

GPT-4 Turbo: Introduces tighter integration with other tools, such as the ability to generate images with DALL-E 3, and automatically selects the right tools for the user. In addition, a Copyright Shield has been announced to protect companies using these products.

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We also participate in the Microsoft partnership programme. In which we seek the development of models within the Azure OpenAI environment and the joint research of new use cases for the application of ChatGPT, Codex and DALL-E in private environments.