How Does ChatGPT Work and Answer the Relevant Questions?
This article covers the following aspect of ChatGPT:
How Does ChatGPT Work?
ChatGPT is powered by the OpenAI model known as GPT-3 or Generative Pre-trained Transformer 3 model. OpenAI Has also introduced ChatGPT Plus which is powered by the GPT-4 model. ChatGPT requires its user to log in and register before using its functionality. To learn more about the register and login procedure of ChatGPT, refer to this article “ “How to Login to ChatGPT”.
Large Language Model (LLM)
GPT-3 is a large language model (LLM) that lays the foundation of many text-generator AI systems. Whenever a prompt is entered, the ChatGPT will first understand the context and text of the prompt to provide the best available solution for it.
Tokens and Tokenization
The GPT-3 model was trained on 500 billion tokens which enabled it to understand and answer the text. The GPT-3 model used a process called tokenization in which each word is mapped on single tokens and complex words are further broken down to be mapped on multiple tokens easily.
These tokens are generated by massive datasets of articles, documents, book topics, genres, Wikipedia, etc, and content that is available on the Internet. GPT-3 is fed a huge amount of data to increase its knowledge capacity.
Stages of Training
GPT-3 model does not only work on one layer i.e., tokenization but its complex training includes several layers which utilize the concept of Machine learning and Artificial intelligence. The training of the GPT-3 model involves two steps.
- Supervised learning
- Reinforcement Learning
Training With Supervised Learning
During supervised learning, the system learns to apply its existing knowledge to various tasks and each task has a probability or score that is calculated. This calculated score together forms a batch which in turn helps the model to train more.
Training With Reinforcement Learning
This type of training is done through human feedback. The model is trained and given input by the human operator. The model will provide an answer for it and this answer will have some score. If the answer does not satisfy the operator, then a new score is assigned to the answer which will help it to improve its abilities and skills.
How Does ChatGPT Answer the Relevant Questions?
ChatGPT does not also provide responses with certainty. Instead, it works on the mechanism of predictability. Here the word “predictability” refers to the ability to predict the most accurate response to any query based on the diverse data on which it is trained.
Based on the existing knowledge it is trained on, it stores neural connections of original data. These patterns are like those experiences that a sportsman has which will help him to predict when to strike. These patterns help ChatGPT to craft the most accurate answers. Let explore an example to answer the relevant question as seen in below figure:
Here, we have asked ChatGPT to write a code in C++ that adds 100 numbers. ChatGPT has provided an accurate response and its Machine Learning algorithms are efficient and smart enough to write correct syntax to minimize the occurrence of errors.
That is all from the guide about working with ChatGPT.
Conclusion
ChatGPT is the achievement of mankind that is based on complex algorithms of Machine learning, the concept of tokenization, extensive training, and feedback from its operators to further improve its working. The underlying architecture of ChatGPT is complex and has been under construction since 2020. Its ability to provide accurate responses to its users has amazed the Internet. However, there is still room for error and as ChatGPT is trained on man-made data, it is only natural that in some cases, it will provide erroneous responses too.
Source: linuxhint.com