Abekek Notes

This is so cool. Especially using Kahneman’s thinking fast, and slow idea is so neat. I even remember expressing a similar idea in one of my SOPs for PhD programs (that I never submitted).

AlphaGeometry is a neuro-symbolic system made up of a neural language model and a symbolic deduction engine, which work together to find proofs for complex geometry theorems. Akin to the idea of “thinking, fast and slow”, one system provides fast, “intuitive” ideas, and the other, more deliberate, rational decision-making.

Because language models excel at identifying general patterns and relationships in data, they can quickly predict potentially useful constructs, but often lack the ability to reason rigorously or explain their decisions. Symbolic deduction engines, on the other hand, are based on formal logic and use clear rules to arrive at conclusions. They are rational and explainable, but they can be “slow” and inflexible - especially when dealing with large, complex problems on their own.

https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry/

Google DeepMind

AlphaGeometry: An Olympiad-level AI system for geometry

Our AI system surpasses the state-of-the-art approach for geometry problems, advancing AI reasoning in mathematics

❤10

www.tgoop.com/abekek_notes/871

1.66K viewsJan 17, 2024 at 19:48

This is so cool. Especially using Kahneman’s thinking fast, and slow idea is so neat. I even remember expressing a similar idea in one of my SOPs for PhD programs (that I never submitted).

AlphaGeometry is a neuro-symbolic system made up of a neural language model and a symbolic deduction engine, which work together to find proofs for complex geometry theorems. Akin to the idea of “thinking, fast and slow”, one system provides fast, “intuitive” ideas, and the other, more deliberate, rational decision-making.

Because language models excel at identifying general patterns and relationships in data, they can quickly predict potentially useful constructs, but often lack the ability to reason rigorously or explain their decisions. Symbolic deduction engines, on the other hand, are based on formal logic and use clear rules to arrive at conclusions. They are rational and explainable, but they can be “slow” and inflexible - especially when dealing with large, complex problems on their own.

https://deepmind.google/discover/blog/alphageometry-an-olympiad-level-ai-system-for-geometry/

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