A Neural Network Solves and Generates Mathematics Problems by Program Synthesis - Paper Explained

Explore a comprehensive analysis of a groundbreaking paper demonstrating how OpenAI's davinci Codex model, combined with prompt engineering, can solve university-level mathematics problems. Delve into the background of OpenAI Codex, examine prompt modification techniques, and witness the model's performance on unseen math courses. Learn about problem generation capabilities, comparing human-generated problems to those created by Codex. Gain insights into quantifying problem statement modification levels and understand the implications of this research for the future of AI in mathematics education and problem-solving.

High level overview of the paper
OpenAI Codex background
Prompt modifications high level
Testing on unseen maths course, problem examples
Prompt modifications in depth
Problem generation: humans vs Codex
Quantifying the problem statement modification levels
Outro