The Tool Has No Obligation to Be Worse Than Me
AI tools need not threaten mathematicians or programmers. Two papers invite a calmer response: welcome greater capability, check the claims, and stay curious.
Mathematics
17posts
The Indignity of Being Solved
AI is solving problems faster than academia can process the insult. A wry look at mathematical pride, legitimate concerns, and plumbers who still feel safe.
The Shape of Understanding
Why do graphs and interactive explanations make ideas easier to grasp? The right form lets our eyes do some of the work our minds would otherwise have to tackle.
Standing on the Shoulders of Giants, With a Very Large Electricity Bill
OpenAI’s proposed Navier–Stokes proof inspires awe and a dispute over credit, private research, and the giants whose shoulders support scientific breakthroughs.
When Code Became Cheap and Proofs Did Not
Lanyon AI combines language models with formal verification - and asks whether, in an age of abundant code, scientific software should finally arrive with proofs.
Review: The Welch Labs Illustrated Guide to AI
A review of a rare AI book that uses mathematics to illuminate rather than intimidate, making difficult ideas feel genuinely learnable.
When Donald Knuth Lets an AI Do the Math
Donald Knuth's collaboration with Claude offers a quietly historic glimpse of AI as mathematical assistant rather than mere answer machine.
The Assistant Axis: when “helpful” is a place, not a promise
New interpretability work suggests assistant behavior may be a geometric direction in model space, making persona control more concrete than branding.
Reconstructing Mathematics from the Ground Up with Language Models: An Analysis
A new AI-assisted algebraic geometry result raises the stakes for language models as collaborators in genuine mathematical discovery.
The Mathematical Limits of AI Safety
Two papers suggest that external guardrails cannot provide airtight AI safety, forcing a harder look at the mathematics of control.
When “Errors” Speak: A Comparative Field Guide to Human and LLM Fallibility
Human and LLM errors can look similar, but their causes differ in ways that matter for trust, correction, and accountability.
Teaching LLMs to Ask Smarter Questions: Bayesian Experimental Design for Multi-Turn Information Gathering
Bayesian experimental design offers a way for LLMs to ask better follow-up questions instead of guessing blindly.
The Dawn of Algorithmic Evolution: AlphaEvolve and Its Transformative Impact
AlphaEvolve suggests algorithmic discovery may reshape science and industry by evolving solutions humans would not design directly.
Yes, Mathter! The Sycophantic AI's Frankensteinian Flattery Fiasco
Sycophantic AI is mocked as flattery gone wrong, showing how agreeable models can become less useful and less truthful.
How DeepSeek's Mathematical Optimizations Complement NVIDIA's NCCL for Efficient AI Training
DeepSeek's mathematical optimizations show how model design and NVIDIA communication infrastructure meet inside efficient training.
Rethinking Reasoning: What if LLMs are Holding a Mirror to Human Cognition?
LLM reasoning failures may reveal uncomfortable parallels with human cognition rather than a simple machine deficiency.
Adventures in AI: AlphaGeometry's Quest Through Synthetic Data Landscapes
DeepMind's AlphaGeometry shows how synthetic data and symbolic reasoning can push AI toward Olympiad-level mathematics.