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Mathematician Timothy Gowers recounts how ChatGPT 5.5 Pro produced PhD-level mathematical research in about an hour with minimal human input, solving open problems from a combinatorics/additive number theory paper and prompting him to significantly revise his assessment of LLMs' mathematical capabilities.
An educational essay explaining the Birthday Paradox math and its application to hash collisions in cryptography, covering probability calculations for matching birthdays and the historical context of Richard von Mises' contributions.
This interactive tool visualizes the mathematical underpinnings of transformer models through dataflow graphs, covering architectures from GPT-2 to Qwen 3.6 and various attention mechanisms.
This paper introduces the AI Co-Mathematician, a workbench that uses agentic AI to support mathematicians in open-ended research tasks like ideation and theorem proving. Early tests show the system achieving state-of-the-art results on hard problem-solving benchmarks, including a 48% score on FrontierMath Tier 4.
Zyphra released ZAYA1-8B, an 8.4B parameter Mixture-of-Experts model with 760M active parameters, demonstrating high efficiency and strong performance in mathematical and coding reasoning tasks.
A Scientific American article recounts how a 17th-century gambling puzzle, the “problem of points,” led Pascal and Fermat to invent modern probability theory.
Maryna Viazovska was awarded the 2022 Fields Medal for proving the E8 lattice provides the densest sphere packing in 8D and advancing Fourier analysis.
DeepMind announces Gemini Deep Think's ability to solve professional research problems in mathematics, physics, and computer science, highlighted by a new agent 'Aletheia' that iteratively verifies and revises solutions.
GPT-5 helped mathematician Ernest Ryu solve a 40-year-old open problem in optimization theory regarding the Nesterov Accelerated Gradient method's stability properties. The breakthrough demonstrates LLMs' capability to assist in significant mathematical discovery by surfacing relevant techniques and ideas from across mathematical literature.
Google DeepMind and Google launched the AI for Math Initiative, partnering with five prestigious research institutions to use AI tools like Gemini Deep Think and AlphaProof to accelerate mathematical discoveries.
This article explains the fundamentals of Markov Decision Processes (MDPs), a core framework in deep reinforcement learning, using an educational example of a student's daily decisions.
A mathematician used the Gemini model to review a forthcoming math paper. The model successfully identified a logical error in Proposition 4.2 and provided three irrefutable reasons, assisting the author in correcting the conclusion. This case demonstrates that AI can perform deep reasoning like a trained mathematician, even in cutting-edge fields.