This repo contains evaluation code for MM-IQ benchmark.
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Updated
May 18, 2025 - Jupyter Notebook
This repo contains evaluation code for MM-IQ benchmark.
Neuroca, Inc's official public authorized repository for a physics grounded approach to modeling real time divergent / convergent intelligence. It contains works in the multi-objective real-time zero-shot learning and cross domain reasoning model. Lineage: AMN (Adaptive Modular Network)->FUM (Fully Unified Model)->VDM (Void Dynamics Model
Innovating solutions to problems world (in general) to make life or things a bit easier.
A short, cheap benchmark that measures difficult capabilities: 42 generated items, 75 points across 8 categories. 60 points graded deterministically, 15 by a pinned open-weight judge. Answers are computed from a seed rather than stored, so the repository is the whole artifact.
A Kotlin application designed to help users practice specific task types from the Thomas General Intelligence Assessment (GIA) test
The specification behind ESAC, a program of compact benchmarks that measure difficult capabilities without measuring budget. ESAC-GI is released and runnable; ESAC-AG has a harness and one of its seven categories. Items are generators rather than stored questions, and every score carries the version tag of the instrument that produced it.
Updatable Meta-Weights Architecture: A Unified Path from Probabilistic Correlation to General Intelligence
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