## Tags - Part of: - Related: - Includes: - Additional: ## Definitions - [[Mathematics]] x [[Artificial Intelligence]] x [[Machine learning]] x [[Data science]] x [[Statistics]] ## Main resources - [Artificial intelligence Mathematics section - Wikipedia](https://en.wikipedia.org/wiki/Artificial_intelligence#Mathematics) <iframe src="https://en.wikipedia.org/wiki/Artificial_intelligence#Mathematics" allow="fullscreen" allowfullscreen="" style="height:100%;width:100%; aspect-ratio: 16 / 5; "></iframe> ## Landscapes - [FunSearch: Making new discoveries in mathematical sciences using Large Language Models - Google DeepMind](https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/) - [AI achieves silver-medal standard solving International Mathematical Olympiad problems - Google DeepMind](https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/) - [\[2404.06405\] Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry](https://arxiv.org/abs/2404.06405) - OpenAI [[o1]] - [8 Best AI for Math Tools (September 2024)](https://www.unite.ai/best-ai-for-math-tools/) - [GitHub - lean-dojo/LeanCopilot: LLMs as Copilots for Theorem Proving in Lean](https://github.com/lean-dojo/LeanCopilot) - [\[2312.07622\] Mathematical Language Models: A Survey](https://arxiv.org/abs/2312.07622) - WolframAlpha - [AIMO Prize](https://aimoprize.com/) - [\[2408.15240\] Generative Verifiers: Reward Modeling as Next-Token Prediction](https://arxiv.org/abs/2408.15240) [x.com/agarwl\_/status/1842609385287348712](https://x.com/agarwl_/status/1842609385287348712) ## Resources [[Links AI math]] ## Landscapes written by AI (may include factually incorrect information) Artificial Intelligence (AI) has made significant contributions to solving various mathematical problems and advancing the field in several ways: ## Problem-Solving Capabilities AI systems have demonstrated impressive abilities in tackling complex mathematical challenges: - Google DeepMind's AlphaProof and AlphaGeometry 2 recently achieved a breakthrough by solving four out of six problems from the International Mathematical Olympiad (IMO), earning the equivalent of a silver medal[6]. This is a significant accomplishment as IMO problems involve advanced reasoning and are designed to challenge top high school students globally. - AlphaGeometry 2 showed remarkable improvement over its predecessor, solving 83% of IMO geometry problems compared to 53% previously[8]. In one instance, it solved a highly complex geometry problem in just 19 seconds. - These AI systems can handle various types of mathematical problems, including geometry, algebra, and proofs, demonstrating a level of versatility previously unseen in AI math solvers[8]. ## Advancements in Mathematical Research AI is contributing to mathematical research in several ways: - AI tools are helping mathematicians discover new insights, novel algorithms, and answers to open problems[6]. - By automating the process of translating informal mathematical language into formal statements, AI is creating large libraries of formal math problems, which is a significant step forward for the mathematics community[4]. ## Educational Applications AI is revolutionizing mathematics education: - AI-powered tools like Julius offer features such as scan-and-solve capabilities for equations, step-by-step explanations, and the ability to convert and solve word problems[7]. - These tools can provide personalized instruction, adaptive assessment, and interactive learning environments, enhancing students' understanding of mathematical concepts[4]. ## Theoretical Advancements AI is also contributing to theoretical aspects of mathematics: - AI systems like DeepMind's AlphaTensor have made advancements in areas such as tensor decomposition, which has applications in numerical analysis and machine learning[3]. - AI is being used to generate new insights and relationships among mathematical concepts, offering fresh perspectives on proving theorems[1]. ## Interdisciplinary Applications The mathematical problem-solving capabilities of AI are being integrated into various fields: - AI's ability to solve complex mathematical problems is being applied in areas such as biology, physics, and engineering, leading to new insights and innovations[3]. While these advancements are impressive, it's important to note that AI still has limitations. For instance, some systems may struggle with explaining their reasoning or lack creativity in problem-solving[4]. Additionally, there are ongoing discussions about the ethical implications and potential overreliance on AI in mathematics education and research[4]. Nonetheless, the integration of AI into mathematics continues to push the boundaries of what's possible in problem-solving and mathematical discovery. Citations: [1] https://alls-academy.com/index.php/as-proceedings/article/view/248 [2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525744/ [3] https://www.hotbot.com/answers/which-ai-can-solve-math-problems [4] https://www.ijopr.com/download/artificial-intelligence-in-mathematics-education-the-good-the-bad-and-the-ugly-14735.pdf [5] https://www.technologyreview.com/2024/07/25/1095315/google-deepminds-ai-systems-can-now-solve-complex-math-problems/ [6] https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/ [7] https://julius.ai/home/ai-math [8] https://fortune.com/2024/07/25/google-researchers-claim-new-breakthrough-in-getting-ai-to-solve-tough-high-school-math-problems/