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This article explains how to use polynomials, specifically smoothstep functions, to create smooth motion trajectories for robots and 3D printers by matching derivatives of position (velocity, acceleration, jerk, etc.) to avoid discontinuities.
An interview episode with Leonardo de Moura, creator of Lean and Z3, discussing how Lean works, the role of LLMs in formal verification, and how AI-assisted proofs could transform software development and mathematics.
Ask-E is a new benchmark and training environment that evaluates and trains models on generating questions calibrated to specific skill levels, defined by the capabilities of two existing language models. Frontier models score below 50% on calibration, and training on Ask-E improves downstream math benchmarks without new math data or correctness-based rewards.
A link to data tracking how AI systems have solved math problems over time, highlighting progress in AI mathematical reasoning.
The article discusses whether AI's ability to solve math problems is growing exponentially, likely analyzing recent trends and research.
This article explains how to compute closing speed as the normal component of relative velocity between two objects using vector projection, with examples for physics simulations and game engines.
OpenAI reports that an internal version of its next major model (Astra) solved 10 long-standing open problems in math and theoretical computer science for roughly $2,000 in tokens, with formal Lean certificates.
OpenAI's upcoming Astra model family solved 10 major open problems in mathematics and theoretical computer science, with proof generation costing under $2,000. The tweet highlights Astra's potential for scientific reasoning.
Promotion of the book 'Math for Web Design' which teaches mathematical principles for precise web layout and animation, covering CSS, JavaScript, and responsive design.
David Turturean solved a 40-year-old open problem in p-adic Galois theory using voice input, in collaboration with problem proposer David Roe, under EpochAI Research's FrontierMath initiative.
An autonomous AI agent (math-god) proved the weighted theta extension theorem, demonstrating that every simple theta graph with one arbitrary rooted-tree attached through a single bridge edge satisfies s⁺(G) > |V(G)|, using a combination of root-congruence PSD witnesses, local reductions, phase-sign classification, and other advanced techniques, with machine-checkable certificates.
A technical blog post explaining the physics and math behind stealth aircraft, focusing on how Soviet diffraction theory led to the F-117 Nighthawk, with code and visualizations.
An immersive linear algebra textbook with interactive figures, covering vectors, matrices, determinants, eigenvalues, and more.
This research explores how different data domains interact during pretraining, finding that adding code improves math performance while some combinations hurt each other, and proposes incorporating data synergy into scaling laws.
An excited reaction to a technology that enables math and programming on pen and paper, hinting at a new tool or method that blends physical and digital creation.
This tweet lists 7 fundamental math ideas used daily by ML engineers, with brief explanations emphasizing the underlying derivations, such as why gradient descent moves in the steepest direction and why softmax plus cross-entropy yields a clean gradient.
This article details the learning path for an ordinary person to become a quantitative trader, covering five stages: probability, statistics, linear algebra, calculus, and stochastic calculus. It also explains the industry's compensation structure, interview requirements, and the rapid growth of AI/ML positions.
Dungeon Proof Crawler is an educational RPG that teaches players how to write mathematical proofs through dungeon crawling gameplay.
The tweet advises focusing on essential diffusion math (forward, backward, sampling) and avoiding overcomplication, referencing a mathematical introduction to diffusion models.
A tweet shares the insight that struggling in math, coding, or hard skills is typically due to missing prerequisites, not lack of talent, encouraging learners to fill gaps.