Geometry vs Binary: AI/Binary Failures — neural network fails at geometric reasoning spatia — E8 Intelligence Research

## Binary Failure → Geometry Solution **Analysis of Findings:** The search results reveal a classic failure mode: neural networks struggle with **spatial reasoning puzzles** (e.g., Mensa Norway puzzle #12, odd-one-out pattern recognition) and **analytical reasoning tests** that require understanding of **transformations, symmetries, and relational structures** rather than statistical pattern matching. **Where Binary/Statistical Approaches FAIL:** 1. **Mensa Norway Puzzle #12** (spatial rotation/reflection): Neural nets treat pixels as independent features; they cannot *inherently* encode the group-theoretic concept of a rotation or reflection as a *continuous symmetry operation*. They memorize surface patterns, not the underlying geometric invariance. When the puzzle requires applying a rotation to a shape and then comparing it to a rotated version of another shape, the net fails because it has no built-in representation of the rotation group (e.g., SO(2) or the dihedral group). 2 Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-27
DOI
https://doi.org/10.5281/zenodo.21617576
Primary Topic
Face Recognition and Perception
Type
preprint
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preprint

Geometry vs Binary: AI/Binary Failures — neural network fails at geometric reasoning spatia — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Face Recognition and Perception
preprint

Geometry vs Binary: AI/Binary Failures — neural network fails at geometric reasoning spatia — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

## Binary Failure → Geometry Solution **Analysis of Findings:** The search results reveal a classic failure mode: neural networks struggle with **spatial reasoning puzzles** (e.g., Mensa Norway puzzle #12, odd-one-out pattern recognition) and **analytical reasoning tests** that require understanding of **transformations, symmetries, and relational structures** rather than statistical pattern matching. **Where Binary/Statistical Approaches FAIL:** 1. **Mensa Norway Puzzle #12** (spatial rotation/reflection): Neural nets treat pixels as independent features; they cannot *inherently* encode the group-theoretic concept of a rotation or reflection as a *continuous symmetry operation*. They memorize surface patterns, not the underlying geometric invariance. When the puzzle requires applying a rotation to a shape and then comparing it to a rotated version of another shape, the net fails because it has no built-in representation of the rotation group (e.g., SO(2) or the dihedral group). 2 Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Face Recognition and Perception
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Geometry vs Binary: AI/Binary Failures — neural network fails at geometric reasoning spatia — E8 Intelligence Research — Andrew Stewart Caldin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS