OpenAI GPT-next Solves 80-Year-Old Erdős Planar Unit Distance Problem for Under $1000
A Latent Space AINews digest reports that OpenAI's GPT-next model disproved the Erdős planar unit distance conjecture, an 80-year-old open problem in combinatorial geometry, at a compute cost under $1000. The item is framed as a notable AI-assisted mathematics result. The brief characterizes it as a quiet day overall but highlights this as a meaningful capability demonstration at the intersection of AI and formal mathematics.
Related guides (3)
Related events (8)
An OpenAI model has disproved a central conjecture in discrete geometry
An OpenAI model has disproved a major conjecture in discrete geometry by solving the 80-year-old unit distance problem. This represents a milestone in AI-driven mathematical reasoning, demonstrating that frontier AI systems can produce novel, verifiable mathematical results rather than merely verifying or assisting with known proofs. The announcement comes from OpenAI's official blog, indicating a significant capability demonstration.
An OpenAI Model Disproves a Central Conjecture in Discrete Geometry
An OpenAI model has reportedly disproved a long-standing conjecture in discrete geometry, representing a significant AI-assisted mathematical discovery. This is a notable capability demonstration of AI systems contributing to frontier mathematical research. The announcement comes directly from OpenAI and has generated substantial community discussion on Hacker News with 462 points and 298 comments.
GPT-5 and the future of mathematical discovery
UCLA Professor Ernest Ryu collaborated with GPT-5 to solve an open problem in optimization theory, representing a concrete example of AI-assisted mathematical research. The announcement highlights GPT-5's capability in formal reasoning and scientific discovery beyond standard benchmarks. This is an OpenAI blog post showcasing a real-world research outcome involving a frontier model.
Advancing science and math with GPT-5.2
OpenAI has released GPT-5.2, described as its strongest model for mathematics and science, achieving state-of-the-art results on GPQA Diamond and FrontierMath benchmarks. The announcement highlights practical research applications including solving an open theoretical problem and generating verified mathematical proofs. The post positions GPT-5.2 as a meaningful step toward AI-assisted scientific discovery.
OpenAI Trains System Solving Grade School Math Problems at ~55% Accuracy
OpenAI released a system for solving grade school math word problems that achieves roughly twice the accuracy of a fine-tuned GPT-3 model. The system scored 55% on a sample test where 9-12 year olds scored 60%, suggesting near-human performance on elementary math. This work represents an early milestone in neural network mathematical reasoning capabilities.
Google's Aletheia agent uses Gemini 3 Deep Think to generate novel solutions to unsolved Erdős problems
Google researchers introduced Aletheia, an agentic workflow using Gemini 3 Deep Think that generates, verifies, and revises solutions to previously unsolved mathematical problems. Applied to Erdős problems, Aletheia produced 13 correct solutions out of 200 evaluated, with 4 being genuinely novel contributions not found in existing literature. The announcement also reveals Gemini 3 Deep Think's benchmark performance: 48.4% on HLE, 84.6% on ARC-AGI-2, and 93.8% on GPQA Diamond. The system demonstrates both the promise and current limitations of AI-assisted mathematical research, with a 6.5% correct-under-intended-interpretation rate on a hard problem set.
Resolving digital threats 100x faster with OpenAI
Outtake, a cybersecurity company, uses GPT-4.1 and OpenAI o3 to build AI agents that detect and resolve digital threats. The company claims a 100x speed improvement over previous approaches. This is a brief case study published on the OpenAI blog highlighting enterprise deployment of frontier models in security workflows.
Early experiments in accelerating science with GPT-5
OpenAI has published initial research cases demonstrating GPT-5's application to scientific discovery across mathematics, physics, biology, and computer science. The examples highlight human-AI collaboration in generating mathematical proofs and uncovering novel insights. This represents OpenAI's first public documentation of GPT-5's scientific research capabilities beyond general benchmarks.