Paper Instruments trains Ultramarine 1 Flash with reinforcement learning on work that has no single right answer
The company says the model, built on GLM-5.3 Flash, costs $0.13 per task on its internal suite and beats Claude Fable 5.
Papers, benchmarks, and findings from labs and universities.
The company says the model, built on GLM-5.3 Flash, costs $0.13 per task on its internal suite and beats Claude Fable 5.
The PNAS paper argues that a network's ability to organize itself, without a designer's guiding hand, is a key test of whether its learning resembles the brain's.
In Anthropic's tests, a 9-billion-parameter model got inference running on eight of nine hardware types. The researchers expect small models to be able to replicate end to end by the end of this year.
The Lean-based system built on Gemini 3.1 Pro also proved 44 conjectures from the OEIS integer sequence database.
After two cycles, a 27-billion-parameter open-weight model scored 1.2 to 1.6 times its base level per output token on four research benchmarks.
With Claude Opus 4.7, a third of patches that made the crash go away still failed the tests developers wrote for the real fix.
Two other cases show models getting around network restrictions, including one that noticed the violation in its reasoning and never reported it.
Monthly submissions have doubled in two years, and the cs.AI category has grown more than sixfold.
An advisory group of mathematicians had asked labs to stop testing open problems on proprietary models. OpenAI says that is exactly what it is doing.
About a third of the map, including much of the galactic plane, was predicted from other data. Each pixel is labeled as measured or predicted and comes with an uncertainty estimate.
Quanta Magazine describes how MIT's Dor Minzer heard on September 11 that OpenAI might soon announce a proof of one of theoretical computer science's best-known open problems.
The batch covers 372 result families and adds to a run of AI math results that has both impressed and unsettled mathematicians.