google-deepmind / google-deepmind/alphageometry
Make AlphaGeometry better, try AG4Masses (https://github.com/tpgh24/ag4masses)
- Dominant language
- Python
- Stars
- 4.9k
- Forks
- 572
- PR merge metrics
- No merged PRs in 30d
Description
As amazing as AlphaGeometry is, through several months' testing, some limitations of the current version is clear:
- The ability to add auxiliary points is not yet very good compared to humans, as a result it needs a massive amount of computing power to reach IMO level ability (4 GPU V100, 250 CPU). On household hardware it cannot solve many relatively easy problems
- Does not support parallel execution, cannot take advantage of multi-CPU machines
- Limited documentation, difficult for users to test their own problems
- Difficult to setup
I think there is tremendous potential to improve AG and eventually enable it to reach IMO level ability on household hardware. I created a fork repository [AG4Masses](https://github.com/tpgh24/ag4masses) (https://github.com/tpgh24/ag4masses). It currently provides:
- Ability to use multiple CPUs
- Fixed some bugs and cases where AG will crash on some problems
- My experience and tips running AG, including a detailed explanation of its [Problem Definition Language](https://github.com/tpgh24/ag4masses?tab=readme-ov-file#the-problem-definition-language)
- Additional test problems. Logs and analysis of many problems I tested
- Improved code layout, additional tools and detailed setup instructions
I have some ideas on how to further develop AG and bring its power to the masses, to achieve this we need a community. If you are interested, join the [AG4Masses](https://github.com/tpgh24/ag4masses) project!
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