What will be true of the SOTA AI on the FrontierMath benchmark, before 2027?
➕
Plus
6
Ṁ251
2027
57%
Transformer-based architecture
55%
Developed by OpenAI
50%
Developed by Google Deepmind
50%
Narrow domain of knowledge. ie Does not know random facts such as when Google was founded, or who won the 1960 presidential election.
48%
Based on Symbolic AI (https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)
48%
Energy-based Model (https://en.wikipedia.org/wiki/Energy-based_model)
44%
Part of the AlphaProof family of models (AlphaProof N and variations)
44%
Part of the o1 family of models (o1, o2, etc. and variations)
34%
Developed by a non-British and non-American company
30%
Part of the GPT-N family of models (GPT-5, GPT-6, and variations)
28%
Over 1T parameters

An option resolves YES if it is true about the AI model, or program, known to be State of the Art in terms of the FrontierMath benchmark, at the end of the year 2026. It resolves NO otherwise.

You're welcome to add any interesting facts that might or might not be true about the state of the art in math problems, as defined by achieving the highest score on the FrontierMath benchmarks.

I reserve the right to cancel any option that is too vague, too improbable, etc.

See also:
/Bayesian/what-will-true-of-the-sota-ai-on-th-y0LE5uE9n9
/Bayesian/what-will-true-of-the-sota-ai-on-th-ROldIhZZgt (this market)
/Bayesian/what-will-true-of-the-sota-ai-on-th-RQptyR5uO8

/Bayesian/will-an-ai-achieve-85-performance-o-hyPtIE98qZ
/MatthewBarnett/will-an-ai-achieve-85-performance-o

/Bayesian/will-an-ai-achieve-30-performance-o

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#AI
#Technical AI Timelines
#Math
#IMO Grand Challenge
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