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Story

Amateur armed with ChatGPT solves an Erdős problem

1 report

1 website

1 discussion

Latest report

Overview

Liam Price, a 23-year-old without advanced mathematics training, solved a 60-year-old problem previously unsolved by mathematicians using ChatGPT Pro. Recent advancements in artificial intelligence have led to solutions for several conjectures known as Erdős problems.

Summary from scientificamerican.com.

Reports

One report so far. Additional coverage will appear here when it is linked to this story.

  1. scientificamerican.com

    Amateur armed with ChatGPT solves an Erdős problem

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Community reactions

Each reaction summarizes sampled comments from the linked discussion.

Hacker News · scientificamerican.com

Amateur armed with ChatGPT solves an Erdős problem ↗
Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Read this discussion’s reaction

Based on 5 sampled comments from this thread. Analyzed 2026-04-26.

  • Praise: The ability of LLMs to make novel connections across different fields is a significant advancement, showcasing their potential to contribute to scientific breakthroughs.
  • Praise: The successful proof of an Erdős problem by an amateur using ChatGPT indicates that AI models are becoming increasingly capable and sophisticated in tackling complex mathematical challenges.
  • Praise: This milestone demonstrates that LLMs are not only improving in performance but also revealing new insights and connections that were previously overlooked by human mathematicians.
  • Praise: The collaborative idea of creating a GitHub repository for unsolved problems highlights the potential for community-driven AI applications to accelerate mathematical discoveries.
  • Concern: Some users experienced limitations with the free version of ChatGPT, indicating that access to advanced features may hinder broader participation in solving complex problems.
  • Concern: Concerns were raised about the depth of understanding required to evaluate the proofs generated by LLMs, suggesting that reliance on AI may not fully substitute for human expertise in mathematics.