About Game of Pong

The article titled “An OpenAI Codex Experiment: Coding the Game of Pong using an AI co-pilot” by Bart Theeten explores the author’s experience using OpenAI’s Codex to code the classic game of Pong. The author provides a detailed walkthrough of the process, highlighting both the strengths and limitations of the AI model.

Here are four key features of the article

  1. Detailed Experiment: The author provides a step-by-step account of using Codex to code the game of Pong. This includes the generation of code from both general descriptions and pseudocode, as well as the handling of errors and under-specifications.
  2. Strengths and Limitations of Codex: The author highlights that Codex is excellent at suggesting relevant libraries and API calls. However, it sometimes struggles with mathematical calculations and can generate different code based on slight changes in wording.
  3. Insights on AI Co-pilots: The author suggests that while AI co-pilots like Codex can be useful for building simple projects, they may not be as effective for more complex tasks. This is due to the time required to debug the subtle mistakes that the AI might make.
  4. Conclusions and Recommendations: The author concludes that while Codex can increase productivity for simple projects, it may not be as effective for more complex tasks. The author also suggests that future AI co-pilots should be able to add to and update existing code, rather than just append new code.