MarkTechPost@AI 2024年07月27日
Google DeepMind’s AlphaProof and AlphaGeometry-2 Solves Advanced Reasoning Problems in Mathematics
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

Google DeepMind开发的AI系统AlphaProof和AlphaGeometry 2在2024年国际数学奥林匹克竞赛(IMO)中取得了银牌级别的成绩,成功解决了六道复杂数学题中的四道,得分28分,位列609名参赛者中的前58名。

🎉 AlphaProof是一种基于强化学习的新系统,专为形式化数学推理而设计。它结合了经过微调的Gemini语言模型和AlphaZero强化学习算法,此前该算法在掌握国际象棋、将棋和围棋等游戏方面表现出色。AlphaProof将自然语言问题陈述转换为形式化数学语言,创建了一个庞大的形式化问题库。然后,它使用一个求解器网络在Lean形式化语言中搜索证明或反证,通过持续学习不断训练自己解决更复杂的问题。

🤖 AlphaGeometry 2是早期AlphaGeometry系统的增强版本,是一个基于Gemini语言模型的神经符号混合模型。它在合成数据上进行了大量训练,使其能够解决更具挑战性的几何问题。AlphaGeometry 2采用了一个比其前身快得多的符号引擎,并利用知识共享机制来解决更高级的问题。

🏆 在IMO 2024中,AlphaProof和AlphaGeometry 2的共同努力成功解决了两个代数问题、一个数论问题和一个几何问题。值得注意的是,AlphaProof解决了比赛中最难的问题,只有五位人类参赛者能够解决。然而,两个组合问题仍然需要解决。

💡 AlphaProof的形式推理方法使其能够生成和验证解决方案候选者,并通过每个已证明的解决方案强化其语言模型。这种迭代学习过程使该系统能够解决越来越困难的问题,最终在比赛中取得成功。另一方面,AlphaGeometry 2在将几何问题形式化后仅19秒就解决了问题,突出了其快速解决问题的能力。

🚀 这一成就标志着将AI应用于复杂问题解决和数学推理方面的一个重要里程碑。AlphaProof和AlphaGeometry 2的成功证明了将LLM与强大的搜索机制(如强化学习)相结合以解决复杂数学问题的潜力。AI系统能够与世界上一些最优秀年轻数学家相媲美的能力,预示着人工智能在探索新假设、解决长期存在的问题以及简化数学证明过程方面具有光明的前景。

🚀 研究和开发团队正在继续改进他们的模型,探索新的方法,以进一步增强AI的数学推理能力。随着这些系统变得更加先进,它们可以彻底改变数学家和科学家解决问题和发现问题的方式。AlphaProof和AlphaGeometry 2在IMO 2024中的成功证明了AI的快速发展及其在数学等复杂领域中日益重要的作用。这一成就为人工智能与人类专家之间的未来创新和合作铺平了道路,推动着科学和技术的进步。

In a groundbreaking achievement, AI systems developed by Google DeepMind have attained a silver medal-level score in the 2024 International Mathematical Olympiad (IMO), a prestigious global competition for young mathematicians. The AI models, named AlphaProof and AlphaGeometry 2, successfully solved four out of six complex math problems, scoring 28 out of 42 points. This places them among the top 58 out of 609 contestants, demonstrating a remarkable advancement in mathematical reasoning and AI capabilities.

AlphaProof is a new reinforcement-learning-based system designed for formal mathematical reasoning. It combines a fine-tuned version of the Gemini language model with the AlphaZero reinforcement learning algorithm, which has previously excelled in mastering games like chess, shogi, and Go. AlphaProof translates natural language problem statements into formal mathematical language, creating a vast library of formal problems. It then uses a solver network to search for proofs or disproofs in the Lean formal language, progressively training itself to solve more complex issues through continuous learning.

AlphaGeometry 2, an enhanced version of the earlier AlphaGeometry system, is a neurosymbolic hybrid model based on the Gemini language model. It has been trained extensively on synthetic data, enabling it to tackle more challenging geometry problems. AlphaGeometry 2 employs a symbolic engine significantly faster than its predecessor and utilizes a knowledge-sharing mechanism for advanced problem-solving.

During the IMO 2024, the combined efforts of AlphaProof and AlphaGeometry 2 resulted in solving two algebra problems, one number theory problem, and one geometry problem. Notably, AlphaProof solved the hardest problem in the competition, which only five human contestants could solve. However, the two combinatorics problems still needed to be solved.

AlphaProof’s formal approach to reasoning allowed it to generate and verify solution candidates, reinforcing its language model with each proven solution. This iterative learning process enabled the system to tackle increasingly difficult problems, leading to its success in the competition. On the other hand, AlphaGeometry 2’s rapid problem-solving capability was highlighted when it solved a geometry problem just 19 seconds after its formalization.

This achievement marks a significant milestone in applying AI to complex problem-solving and mathematical reasoning. The success of AlphaProof and AlphaGeometry 2 demonstrates the potential of combining LLMs with powerful search mechanisms, such as reinforcement learning, to solve intricate mathematical problems. The ability of AI systems to perform at a level comparable to some of the world’s best young mathematicians suggests a promising future where AI can assist in exploring new hypotheses, solving long-standing problems, and streamlining the proof process in mathematics.

The research and development teams behind AlphaProof and AlphaGeometry 2 continue to refine their models and explore new approaches to enhance AI’s mathematical reasoning capabilities further. As these systems become more advanced, they can revolutionize how mathematicians and scientists approach problem-solving and discovery. The success of AlphaProof and AlphaGeometry 2 at the IMO 2024 is a testament to the rapid advancements in AI and its growing role in complex domains such as mathematics. This achievement paves the way for future innovations and collaborations between AI and human experts, driving progress in science and technology.


Check out the Details. All credit for this research goes to the researchers of this project. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Group. If you like our work, you will love our newsletter..

Don’t Forget to join our 47k+ ML SubReddit

Find Upcoming AI Webinars here

The post Google DeepMind’s AlphaProof and AlphaGeometry-2 Solves Advanced Reasoning Problems in Mathematics appeared first on MarkTechPost.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

人工智能 数学 奥林匹克 AlphaProof AlphaGeometry
相关文章