In the first episode of the Embodied AI Podcast, Ron tells us about his journey from Stanford to machine learning and the people that inspired him to dig deeper on philosophical questions around embodiment. Ron lays out 4 dimensions to think about Embodied AI and situates its role in the history of AI - mainly the move away from Symbolic AI. We take a close look at his 2003 paper on Embodied Artificial Intelligence, making connections to the relevance problem, Lewis Carroll's What the Tortoise Said to Achilles, Ludwig Wittgenstein, and current matching learning. Ron also discusses his work on non-conceptual content and synthetic phenomenology, showing us how we can use embodied technologies to study non-systematic aspects of our experience or that of a robot. We finish off with his recent ideas about AI creativity and the future of Embodied AI, with some career advice for younger listeners.

Timestamps: 

(00:00) - Intro

(01:48) - Ron's background

(06:08) - What is Embodied AI?

(25:21) -  Symbolic AI

(35:10) - 2003 Paper: Relevance/Frame Problem

(49:36) - Embodied AI and current machine learning

(52:49) - Non-Conceptual Content 

(1:01:30) - Synthetic Phenomenology

(1:05:48) - AI creativity

(1:19:42) - Career Advice

(1:24:23) - Future of Embodied AI 

Ron's Sussex webpage

Ron's Blog page - see for synthetic phenomenology artwork: 

Papers

2003 Embodied Artificial Intelligence paper

1996 DPhil Thesis on Non-Conceptual Content

Douglas Hofstadter: Waking Up from the Boolean Dream, or, Subcognition as Computation paper

Paper by Tom Froese and Tom Zienke: 

My Twitter