# Reflections on "Can AI Understand Our Universe?"

arXiv: https://arxiv.org/abs/2501.17507 · HTML: https://mlsanity.com/paper/2501.17507/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 16 references that are in the map.
- First posted on arXiv 29 Jan 2025.

## Builds on (most cited first, 2 of 2)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Thinking Fast and Slow in AI](https://mlsanity.com/paper/2010.06002/) (2020)

## Built on by (most cited first, 1 of 1)

- [Large Language Models for Limited Noisy Data: A Gravitational Wave Identification Study](https://mlsanity.com/paper/2512.04031/) (2025)

## Abstract (arXiv)

This article briefly discusses the philosophical and technical aspects of AI. It focuses on two concepts of understanding: intuition and causality, and highlights three AI technologies: Transformers, chain-of-thought reasoning, and multimodal processing. We anticipate that in principle AI could form understanding, with these technologies representing promising advancements.