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Codex and ChatGPT are language models developed by OpenAI, each serving a distinct purpose with its own unique capabilities. Codex, which is also called GitHub Copilot, is made to help coders with their coding projects. Codex has been trained on a large amount of freely available code, so it can make code suggestions, finish code snippets, and give context information to help software developers do their jobs better. Its main goal is to speed up coding by cutting down on the time spent on boring or repeated tasks.
On the other hand, ChatGPT is a language model that was made for talking. Its training data includes a wide range of text from the internet, which lets it take part in discussions on a variety of issues. ChatGPT does a great job of coming up with answers that sound like they came from a person, answering questions, giving explanations, and fostering creative or informative exchanges across different fields.
Codex vs Chatgpt Comparison Table
Specification | Codex | ChatGPT |
---|---|---|
Purpose | Assisting with code-related tasks | General conversational interactions |
Training Data | Publicly available code | Wide range of internet text |
Use Case | Software development, code generation, code completion | Answering questions, engaging in discussions |
Domain | Code-related tasks | Various topics and domains |
What is Codex ?
![codex vs chatgpt](https://www.compsmag.com/wp-content/uploads/2023/05/Capture-710.jpg)
Codex, which is also called GitHub Copilot, is a language model driven by AI that was made by OpenAI. It was made especially to help writers write code. Codex has been trained on a huge amount of code that is available to the public. It can offer code ideas, full code snippets, and information about the context to help software developers do their jobs. Its main goal is to help coders be more productive and spend less time on boring or repetitive jobs by giving them intelligent code generation and help.
What is Chatgpt ?
![codex vs chatgpt](https://www.compsmag.com/wp-content/uploads/2023/05/Capture-709.jpg)
An AI language model called ChatGPT was made by OpenAI. It is meant to be used in conversation and can talk about a wide range of things. ChatGPT has been trained on a wide range of internet text, so it can respond like a person, answer questions, explain things, and help people have creative or informative conversations. Its flexibility means that it can be used in many different kinds of conversations and to help and teach people in many different areas. You can visit its official website
Which is better ?
Both Codex and ChatGPT have different strengths and uses, so which one is better relies on the situation. Codex is the better choice if you want help with jobs related to code, such as making code suggestions, completing code snippets, and getting contextual information for software development. Codex is made to help developers write code, and it can make a big difference in how quickly devs write code.
On the other hand, ChatGPT would be a better choice if you need a language model for general conversational reasons, such as answering questions, having conversations, and explaining things in many different areas. ChatGPT is made to help people have conversations with each other, and it can make answers that look like they came from a person.
Codex: The good and The bad
The Good
- Helps developers code.
- Trained on lots of public code
The Bad
- Only good at programming, not conversation.
Chatgpt: The good and The bad
The Good
- For general discourse.
- Internet text-trained
The Bad
- Cannot help with software development or coding.
FAQS
Copilot is made to help programmers write code that is clear, quick, and free of mistakes. It looks at the code and makes ideas for how to make it better by using machine learning. Codex, on the other hand, is mostly an autocomplete tool that helps coders save time by suggesting code snippets.
We updated the core Codex model to improve the quality of GitHub Copilot’s code suggestions. This made a big difference in the quality of the code suggestions and cut down on the time it took to give them to users.