# Embodied AI in Machine Learning -- is it Really Embodied?

arXiv: https://arxiv.org/abs/2505.10705 · HTML: https://mlsanity.com/paper/2505.10705/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 46 references that are in the map.
- First posted on arXiv 15 May 2025.

## Builds on (most cited first, 19 of 19)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Do As I Can, Not As I Say: Grounding Language in Robotic Affordances](https://mlsanity.com/paper/2204.01691/) (2022)
- [RT-1: Robotics Transformer for Real-World Control at Scale](https://mlsanity.com/paper/2212.06817/) (2022)
- [Code as Policies: Language Model Programs for Embodied Control](https://mlsanity.com/paper/2209.07753/) (2022)
- [Inner Monologue: Embodied Reasoning through Planning with Language Models](https://mlsanity.com/paper/2207.05608/) (2022)
- [Open X-Embodiment: Robotic Learning Datasets and RT-X Models](https://mlsanity.com/paper/2310.08864/) (2023)
- [BridgeData V2: A Dataset for Robot Learning at Scale](https://mlsanity.com/paper/2308.12952/) (2023)
- [Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language](https://mlsanity.com/paper/2204.00598/) (2022)
- [PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs](https://mlsanity.com/paper/2402.07872/) (2024)
- [Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI](https://mlsanity.com/paper/2407.06886/) (2024)
- [Binding Touch to Everything: Learning Unified Multimodal Tactile Representations](https://mlsanity.com/paper/2401.18084/) (2024)
- [Revisiting Active Perception](https://mlsanity.com/paper/1603.02729/) (2016)
- [Retrospectives on the Embodied AI Workshop](https://mlsanity.com/paper/2210.06849/) (2022)
- [ASC: Adaptive Skill Coordination for Robotic Mobile Manipulation](https://mlsanity.com/paper/2304.00410/) (2023)
- [Grounding Multimodal Large Language Models in Actions](https://mlsanity.com/paper/2406.07904/) (2024)
- [The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learning](https://mlsanity.com/paper/2311.00924/) (2023)
- [Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects](https://mlsanity.com/paper/2209.05802/) (2022)
- [All Robots in One: A New Standard and Unified Dataset for Versatile, General-Purpose Embodied Agents](https://mlsanity.com/paper/2408.10899/) (2024)
- [Co-Design of Embodied Intelligence: A Structured Approach](https://mlsanity.com/paper/2011.10756/) (2020)

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

- [The body is not there to compute: Comment on "Informational embodiment: Computational role of information structure in codes and robots" by Pitti et al](https://mlsanity.com/paper/2512.22868/) (2025)

## Abstract (arXiv)

Embodied Artificial Intelligence (Embodied AI) is gaining momentum in the machine learning communities with the goal of leveraging current progress in AI (deep learning, transformers, large language and visual-language models) to empower robots. In this chapter we put this work in the context of "Good Old-Fashioned Artificial Intelligence" (GOFAI) (Haugeland, 1989) and the behavior-based or embodied alternatives (R. A. Brooks 1991; Pfeifer and Scheier 2001). We claim that the AI-powered robots are only weakly embodied and inherit some of the problems of GOFAI. Moreover, we review and critically discuss the possibility of cross-embodiment learning (Padalkar et al. 2024). We identify fundamental roadblocks and propose directions on how to make progress.