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AI & Machine Learning

Mathematician Revives Old Applets with AI Assistance

WireByte Staff · July 12, 2026

Renowned mathematician Terry Tao has successfully migrated his old web page and blog data to a modern repository using AI assistance, reviving his 1999 Java applets in a matter of hours. The applets, including a colorized Besicovitch set, are now functional again. This experiment demonstrates the potential of AI in maintaining and upgrading legacy code.

Key points

  • Terry Tao, a mathematician, has used AI assistance to migrate his 1999 Java applets to a modern supported language (Javascript).
  • The AI agent successfully ported the applets in a matter of hours, with minor bug fixes.
  • The revived applets include a colorized Besicovitch set and a honeycomb applet co-authored with Allen Knutson in 1999.
  • Tao's experiment highlights the potential of AI in maintaining and upgrading legacy code.
  • The success of this experiment may pave the way for similar applications in other fields.

AI-Assisted Revival of Legacy Code

Renowned mathematician Terry Tao has successfully experimented with the use of AI assistance in maintaining and upgrading legacy code. By leveraging modern AI tools, Tao was able to revive his 1999 Java applets in a matter of hours.

Background

In 1999, Tao began coding several applets in Java 1.0 to visualize mathematical objects for his complex analysis and linear algebra courses. The applets were moderately successful but eventually became non-functional due to outdated Java standards.

The Experiment

Tao recently began migrating his old web page and blog data to a more maintainable repository using modern AI assistance. As part of this process, he asked the AI agent to port his old applets to a modern supported language (Javascript). The AI successfully completed the task in a matter of hours, with minor bug fixes.

Results

The revived applets, including a colorized Besicovitch set and a honeycomb applet co-authored with Allen Knutson in 1999, are now functional again. This experiment demonstrates the potential of AI in maintaining and upgrading legacy code.

Future Implications

The success of this experiment may pave the way for similar applications in other fields. As AI technology continues to advance, it is likely that we will see more instances of AI-assisted code maintenance and upgrading in various industries.

Sources

WireByte Staff — Editorial Team

The WireByte editorial team synthesises technology news from multiple primary sources, verifies the facts, and links every source. Articles are produced with AI assistance and reviewed under our editorial policy.