OpenAI Codex
OpenAI Codex can understand, complete, translate, and generate code based on natural language text prompts like “add an image of XYZ” or “resize the image to 100 px”.
This is partly demonstrated in the image above, where the Codex correctly interprets vague expressions like “that person” and “his” based on what was previously said. What makes Codex truly remarkable, however, is its ability to manipulate other software using natural language commands.
Their commands can have tangible effects in the physical world, something the Codex’s predecessor, GPT-3, could never achieve.
For example, a demonstration shows that Codex can accurately generate code that instructs Microsoft Word to perform functions such as removing all leading and trailing whitespace from a document.
Features:
- A large amount of context can easily be stored and remembered with Codex.
- With the Codex API, users can essentially control computers in simple, everyday language.
- Further testing by OpenAI confirmed that Codex can also control Spotify and Google Calendar.
OpenAI Codex vs. GitHub Copilot: Which AI Assists Programmers More Effectively?
What if developing a game was as easy as writing a command like “bounce an object” in plain English?
You could manipulate digital objects in any way you wanted, without any programming knowledge whatsoever. Thanks to text-to-code models like OpenAI Codex, this dream isn’t that far away anymore. As OpenAI has already demonstrated, non-technical users can type simple natural language commands into Codex and develop games in minutes.
In this blog, we are going to give a thorough comparison of the OpenAI Codex model with GitHub Copilot. We talk about the advantages, disadvantages, cost details, characteristics, and other aspects of both OpenAI and GitHub Copilot.