# Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithm

arXiv: https://arxiv.org/abs/2101.07627 · HTML: https://mlsanity.com/paper/2101.07627/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jan 2021.

## Built on by (most cited first, 7 of 7)

- [Neural cellular automata: applications to biology and beyond classical AI](https://mlsanity.com/paper/2509.11131/) (2025)
- [Capturing Emerging Complexity in Lenia](https://mlsanity.com/paper/2305.09378/) (2023)
- [EINCASM: Emergent Intelligence in Neural Cellular Automaton Slime Molds](https://mlsanity.com/paper/2305.13425/) (2023)
- [Toward Building Science Discovery Machines](https://mlsanity.com/paper/2103.15551/) (2021)
- [Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata Ecosystems](https://mlsanity.com/paper/2406.09654/) (2024)
- [Is the `Agent' Paradigm a Limiting Framework for Next-Generation Intelligent Systems?](https://mlsanity.com/paper/2509.10875/) (2025)
- [Self-Replicating Neural Cellular Automata: Quantifying Emergent Phenotypic and Genotypic Diversity in an OpenEnded Substrate](https://mlsanity.com/paper/2609.19902/) (2026)

## Abstract (arXiv)

We propose an artificial life framework aimed at facilitating the emergence of intelligent organisms. In this framework there is no explicit notion of an agent: instead there is an environment made of atomic elements. These elements contain neural operations and interact through exchanges of information and through physics-like rules contained in the environment. We discuss how an evolutionary process can lead to the emergence of different organisms made of many such atomic elements which can coexist and thrive in the environment. We discuss how this forms the basis of a general AI generating algorithm. We provide a simplified implementation of such system and discuss what advances need to be made to scale it up further.