AI Agents Ported Tao's 27-Year-Old Math Code in Hours and Found Two Bugs He Had Missed - Tech Times
AI agents successfully ported Terence Tao's 27-year-old mathematical code in a matter of hours, identifying two bugs that the mathematician had originally missed.
- AI agents ported 27-year-old math code in hours.
- Two bugs were found in the original code.
- Demonstrates AI utility in legacy system modernization.
Terence Tao, a Fields Medalist, allowed AI agents to port his 27-year-old mathematical code. The process was completed in just a few hours, showcasing the speed of modern AI in handling legacy systems.
During the porting process, the agents discovered two bugs in the original code that Tao had overlooked for decades. This finding highlights the potential for AI to act as a rigorous verification tool in scientific research.
The experiment serves as a significant proof of concept for using AI in software maintenance. It suggests that AI agents can reliably modernize old codebases while improving code quality through debugging.
Shows potential for AI in automated refactoring and debugging.
Indicates cost-effective methods for updating legacy software.
Illustrates AI surpassing human experts in specific detail-oriented tasks.
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DOOMQL
<p><strong><a href="https://github.com/petergpt/doomql">DOOMQL</a></strong></p> Peter Gostev built this using GPT-5.6 Sol. This is a <em>lot</em> of fun: </p> <blockquote> <p>DOOMQL started with a deliberately unreasonable question: what if SQLite were the game engine, not merely the place where a game stores data?</p> <p>The result is a small, original Doom-like game in which SQL owns movement, collision, enemies, combat, progression and every RGB pixel on screen.</p> </blockquote> <p>It's implemented as a Python terminal script - I tried it out like this:</p> <pre><code>cd /tmp git clo
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