# Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT

arXiv: https://arxiv.org/abs/2309.13094 · HTML: https://mlsanity.com/paper/2309.13094/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 93 references that are in the map.
- First posted on arXiv 22 Sep 2023.

## Builds on (most cited first, 3 of 3)

- [Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases](https://mlsanity.com/paper/2102.11965/) (2021)
- [Discrete and continuous representations and processing in deep learning: Looking forward](https://mlsanity.com/paper/2201.01233/) (2022)
- [There's Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines](https://mlsanity.com/paper/2212.10675/) (2022)

## Abstract (arXiv)

Modern computational natural philosophy conceptualizes the universe in terms of information and computation, establishing a framework for the study of cognition and intelligence. Despite some critiques, this computational perspective has significantly influenced our understanding of the natural world, leading to the development of AI systems like ChatGPT based on deep neural networks. Advancements in this domain have been facilitated by interdisciplinary research, integrating knowledge from multiple fields to simulate complex systems. Large Language Models (LLMs), such as ChatGPT, represent this approach's capabilities, utilizing reinforcement learning with human feedback (RLHF). Current research initiatives aim to integrate neural networks with symbolic computing, introducing a new generation of hybrid computational models.