“The sound of weak tea”

– Synesthesia (Cytowic – 1989)

Mirrors of the Mind

These are the mirrors that allows us to reflect on human consciousness and decide what aspects of our perception and embodiment are critical.  And allow us to reflect on the next generation of AI as they engage in deep learning from direct perception of the world.

• Synesthesia (Wikipedia)
• Aphantasia and Hyperphantasia
• Blindsight
• Anauralia
• Hyperthymesia  and variations of Inner Speech
• Flow States
• Lucid Dreaming

Participants in this Deepdive are encouraged to explore a variety of these mind states to develop a sense of what “embodiment” entails and what an AI might express if somehow embodied.

Books

The Embodied Mind: Cognitive Science and Human Experience (2016)

• Author(s): van Thompson, Eleanor Rosch and Francisco J. Varela
• Perspective: This classic book, first published in 1991, was one of the first to propose the “embodied cognition” approach in cognitive science. It pioneered the connections between phenomenology and science and between Buddhist practices and science — claims that have since become highly influential. Through this cross-fertilization of disparate fields of study, The Embodied Mind introduced a new form of cognitive science called “enaction,” in which both the environment and first person experience are aspects of embodiment.

Wednesday is Indigo Blue (2009)

• Author(s): Richard E. Cytowic
• Perspective: A person with synesthesia might feel the flavor of food on her fingertips, sense the letter J as shimmering magenta or the number 5 as emerald green, hear and taste her husband’s voice as buttery golden brown. Synesthetes rarely talk about their peculiar sensory gift—believing either that everyone else senses the world exactly as they do, or that no one else does. Yet synesthesia occurs in one in twenty people, and is even more common among artists. One famous synesthete was novelist Vladimir Nabokov, who insisted as a toddler that the colors on his wooden alphabet blocks were “all wrong.”

The Frog Who Croaked Blue: Synesthesia and the Mixing of the Senses (2008)

• Author(s): Jamie Ward
• Perspective: Everyone will be closely acquainted with at least 6 or 7 people who have synesthesia but you may not yet know who they are because, until very recently, synesthesia was largely hidden and unknown. Now science is uncovering its secrets and the findings are leading to a radical rethink about how our senses are organized. In this timely and thought-provoking book, Jamie Ward argues that sensory mixing is the norm even though only a few of us cross the barrier into the realms of synesthesia.

Journal/Review Articles

A Call for Embodied AI (2024)

• Authors: J Giuseppe Paolo Jonas Gonzalez-Billandon Balázs Kégl
• Journal: unpublished – arXiv
• Perspective: We propose Embodied AI (E-AI) as the next fundamental step in the pursuit of Artificial General Intelligence (AGI), juxtaposing it against current AI advancements, particularly Large Language Models (LLMs). We traverse the evolution of the embodiment concept across diverse fields (philosophy, psychology, neuroscience, and robotics) to highlight how E-AI distinguishes itself from the classical paradigm of static learning. By broadening the scope of E-AI, we introduce a theoretical framework based on cognitive architectures, emphasizing perception, action, memory, and learning as essential components of an embodied agent. This framework is aligned with Friston’s active inference principle, offering a comprehensive approach to E-AI development. Despite the progress made in the field of AI, substantial challenges, such as the formulation of a novel AI learning theory and the innovation of advanced hardware, persist.

Minds in movement: embodied cognition in the age of artificial intelligence (2024)

• Authors: Louise Barrett, Dietrich Stout
• Journal: Philos Trans R Soc Lond B Biol Sci (2024) 379 (1911): 20230144 .
• Perspective: This theme issue brings together researchers from diverse fields to assess the current status and future prospects of embodied cognition in the age of generative artificial intelligence. In this introduction, we first clarify our view of embodiment as a potentially unifying concept in the study of cognition, characterizing this as a perspective that questions mind–body dualism and recognizes a profound continuity between sensorimotor action in the world and more abstract forms of cognition. We then consider how this unifying concept is developed and elaborated by the other contributions to this issue, identifying the following two key themes: (i) the role of language in cognition and its entanglement with the body and (ii) bodily mechanisms of interpersonal perception and alignment across the domains of social affiliation, teaching and learning.

Real Patterns (1991)

• Authors: Daniel Dennett
• Journal: Journal of Philosophy 88 (1):27-51 (1991)
• Perspective: “Real Patterns” paper argues that patterns—such as mental states, consciousness, and intentional behavior—are objectively real if they enable reliable prediction and data compression, regardless of their underlying physical details

 

Podcasts & Debates

Chasing Consciousness #82: Will AI Robots be conscious?

• Participants: Suzanne Gildert (w/Freddy Drabble)
• Perspective: WILL ARTIFICAL INTELLIGENCE ROBOTS HAVE SUBJECTIVE EXPERIENCE? WHAT ARE THE ETHICAL AND SAFETY IMPLICATIONS OF SUCH ENTITIES? WHICH QUANTUM PHYSICS THEORY CAN ACCOMODATE CONSCIOUSNESS?In this episode we have the extraordinary possibility of subjective experience and feelings in artificial intelligence robotic systems to think about. So we look at experiments to try and prove if it’s even possible; the quantum building blocks from which both living and artificial systems are made up; the ethical and safety implications of advanced intelligence instantiated in robots, and we get into the controversial search for a quantum physics theory that can accommodate consciousness.

Embodied AI, Non-Conceptual Content, AI Creativity (Embodied AI #1)

• Participants: Ron Chrisley (w/Akseli Ilmanen)
• Perspective: n 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.

The Quest for Consciousness (Chasing Consciousness #84)

• Participants: Christoph Koch (w/Freddy Drabble)
• Perspective: In this episode we have the very theme of the podcast’s title to delve into, the quest to understand the nature of consciousness. So we discuss mind and self, and what kind of substrate you need to allow for subjective experience; we look at the various philosophical positions on the nature of consciousness and ways to move beyond the unwinnable argument around the hard problem; we talk about extended cognition and cellular cognition; how integrated information theory attempts to quantify consciousness; the origin of meaning; psychedelics and the implications of mystical experiences of non-separation; whether AI will ever become conscious; and the implications of plant intelligence and memory.

Videos

What are Conscious Exotica? Consciousness, AI & the Space of Possible Minds

• Channel: Mind-Body Solution (YouTube)
• Perspective: Murray Shanahan is Professor of Cognitive Robotics at Imperial College London and a principal research scientist at Google DeepMind. Educated at Imperial College (BSc(Eng) computer science) and Cambridge University (King’s College; PhD computer science), he became a full Professor at Imperial, and joined DeepMind. His publications span artificial intelligence, machine learning, logic, dynamical systems, computational neuroscience, and philosophy of mind. He was Scientific Advisor on the film Ex Machina (2014). He has written several books, including “Embodiment and the Inner Life” (2010) and “The Technological Singularity” (2015)

The Shape of AI to Come (Yann LeCun)

• Channel: DSAI w/Dr. Osbert Tay
• Perspective: At the AI Action Summit in Paris, Yann LeCun underscored a fundamental shift in artificial intelligence—one that moves beyond the brute-force approach of large language models (LLMs). Instead of systems that merely predict the next token, the future of AI hinges on *world models*—structured, adaptive representations that can infer, reason, and plan.  This vision holds immense potential for fields like healthcare and biology, where complexity defies exhaustive computation.

V-JEPA: The next step toward Yann LeCun’s vision of advanced machine intelligence (AMI)

• Channel: META Research
• Perspective: As humans, much of what we learn about the world around us—particularly in our early stages of life—is gleaned through observation. Take Newton’s third law of motion: Even an infant (or a cat) can intuit, after knocking several items off a table and observing the results, that what goes up must come down. You don’t need hours of instruction or to read thousands of books to arrive at that result. Your internal world model—a contextual understanding based on a mental model of the world—predicts these consequences for you, and it’s highly efficient.“V-JEPA is a step toward a more grounded understanding of the world so machines can achieve more generalized reasoning and planning,” says Meta’s VP & Chief AI Scientist Yann LeCun, who proposed the original Joint Embedding Predictive Architectures (JEPA) in 2022. “Our goal is to build advanced machine intelligence that can learn more like humans do, forming internal models of the world around them to learn, adapt, and forge plans efficiently in the service of completing complex tasks.”