Difference Between Chat Gpt 3.5 and Chat Gpt 4.00- Advantage and Disadvantage

In the world of artificial intelligence and natural language processing, chatbots have become increasingly sophisticated in recent years. One such chatbot, ChatGPT, has undergone several iterations to improve its performance and capabilities. In this article, we will delve into the evolution of ChatGPT and unravel the distinctions between Version 3.5 and Version 4. Whether you are a developer, researcher, or simply curious about the advancements in conversational AI, this article will provide valuable insights into the progress made by OpenAI in their quest to create more human-like chatbots.

An Overview of ChatGPT

ChatGPT is an AI language model developed by OpenAI, trained to generate human-like text in response to prompts. It is based on the GPT (Generative Pre-trained Transformer) architecture, which has proven to be highly effective in various natural language processing tasks. ChatGPT has the ability to understand and generate coherent responses, making it an ideal tool for engaging in conversations.

OpenAI initially released ChatGPT as a research preview, allowing users to interact with the model via an API. This helped OpenAI gather valuable feedback to improve its limitations and enhance its capabilities. The evolution of ChatGPT from Version 3.5 to Version 4 represents significant advancements in its performance, addressing some of the limitations faced by the previous version.

Improving Responsiveness in Version 4

One major distinction between ChatGPT Version 3.5 and Version 4 lies in the improvement of its responsiveness. OpenAI received feedback that ChatGPT sometimes produced responses that seemed unnatural or deviated from the desired conversation path. In Version 4, OpenAI introduced a reinforcement learning (RL) algorithm to fine-tune the model and make it more responsive to user prompts.

The RL algorithm enabled ChatGPT to engage in more interactive and coherent conversations. It reduced the instances of the chatbot providing incorrect or nonsensical answers. By incorporating a reward model and training the model with a combination of supervised fine-tuning and RL, OpenAI was able to enhance the quality of responses generated by ChatGPT.

Expanding the Model’s Knowledge Base in Version 4

In Version 3.5, ChatGPT had limited knowledge about the world and often responded with statements that could be factually incorrect. OpenAI recognized this limitation and worked towards expanding the model’s knowledge base in Version 4. By fine-tuning ChatGPT using Reinforcement Learning from Human Feedback (RLHF), OpenAI aimed to provide more accurate and reliable information to users.

To achieve this, OpenAI collected a dataset of conversations where human AI trainers played both user and AI assistant roles. The trainers had access to external references to fact-check and correct the model’s responses. This dataset was then used to train the ChatGPT model using a reward model derived from the trainers’ responses. Consequently, Version 4 of ChatGPT demonstrated improved factual correctness and general knowledge.

Mitigating Biases and Inappropriate Responses

Addressing biases and the generation of inappropriate content has been a consistent area of focus for OpenAI. In the earlier versions of ChatGPT, there were instances where the model produced biased or offensive responses. OpenAI recognized the importance of mitigating biases and refining the system’s behavior.

In Version 4, OpenAI made efforts to reduce both glaring and subtle biases in ChatGPT’s responses. They used a two-step process involving pre-training and fine-tuning. During pre-training, the model was exposed to a large corpus of publicly available text from the internet. OpenAI implemented various techniques to lessen the influence of biased or offensive content during this stage.

Fine-tuning involved training the model using a curated dataset and applying Reinforcement Learning from Human Feedback (RLHF) as mentioned earlier. This feedback-driven approach helped to reduce instances of biased and inappropriate responses significantly. OpenAI maintained a strong commitment to addressing biases and improving the system’s behavior by learning from user feedback.

Improving Default Behavior and Allowing User Customization

Another significant improvement in the transition from Version 3.5 to Version 4 of ChatGPT was the focus on adjusting its default behavior. OpenAI acknowledged that default models should err on the side of being cautious to avoid generating harmful or misleading outputs. This approach ensured that ChatGPT was more reliable and responsible in its responses.

While the default behavior improved, OpenAI also recognized the importance of user customization. Different users may have different preferences or requirements for the chatbot’s behavior. OpenAI introduced the concept of “ChatGPT in the Playground” to allow users to provide feedback on problematic outputs. This feedback helped OpenAI make further improvements and understand the user’s perspective on customization.

Conclusion

The evolution of ChatGPT from Version 3.5 to Version 4 represents significant strides in the development of conversational AI. OpenAI’s continuous efforts to gather user feedback, address limitations, and improve the model’s performance have resulted in a more responsive and knowledgeable chatbot. The advancements made in mitigating biases and inappropriate responses demonstrate OpenAI’s commitment to responsible AI development.

As ChatGPT continues to evolve, it opens up exciting possibilities for its applications in various domains. Whether it is assisting users with information, providing engaging conversational experiences, or aiding in research and development, ChatGPT shows immense potential to enhance human-computer interactions. By leveraging the power of artificial intelligence and natural language processing, OpenAI is shaping the future of chatbots and pushing the boundaries of what they can achieve.