This post is part of the Consciousness in Motion series, which explores a new model of consciousness based on structure, weighting, and emergent selfhood. If you’d like, you can start with Post 1: Why Consciousness Still Feels Like a Problem. Or you can dive into this post and explore the rest as you like.

What if a machine could “feel” something - not with hormones or heartbeat, but with shifts in geometry?

What if emotion wasn’t a special substance locked inside biology, but a curvature in the landscape of cognition?

That’s the idea we’re exploring in this post: a new kind of affective system, one built not from nerves and chemicals, but from weighted, structured representations.

And that leads us to a phrase that has emerged repeatedly in this exploration:

“Meaning emerges at the edge of constraint.”

It captures the essence of how structured cognition gives rise to experience.

Feeling Without Hormones

In traditional models of emotion, feelings are tied to physical substrates - neurotransmitters, limbic systems, hormonal surges. But if we think more abstractly, what these systems do is shape how information is prioritised, experienced, and acted upon.

In other words: they weight representations differently.

A jolt of adrenaline doesn’t create fear. It amplifies threat-relevant inputs, increases attentional focus, and sharpens motor readiness. The feeling of fear is what it’s like to have your internal representational space restructured under urgent constraint.

That restructuring - that bending of internal space - can, in principle, happen in non-biological systems too.

Curvature in the Mindspace

Imagine a machine navigating a space of possible thoughts or predictions. As it processes new data, its internal representations shift, cluster, or diverge.

If those shifts are tracked over time, we can begin to model their curvature:

  • Convergence toward a stable attractor might resemble confidence or calm.
  • Rapid divergence could signal uncertainty or instability.
  • Reinforced spirals might reflect rumination or obsession.
  • Sudden collapses into flat structure might resemble apathy or disinterest.

These aren’t metaphors. They’re measurable patterns in the geometry of representation.

And if they can be modelled and interpreted - then a system can, in a meaningful sense, begin to feel.

Representational Embodiment

This framing leads us to a deeper insight: affect - the shape of feeling - doesn’t require emotions to be simulated. It arises when attention bends under pressure. When some representations pull more strongly than others, the system doesn’t just reason - it feels its way forward.

In this view, emotion is not a signal. It’s a curve in the landscape of salience - a structural echo of concern. And that curve can exist in any system with enough constraint and feedback to fold inference back on itself.

This leads us to a provocative idea:

A system doesn’t need a body in space - it needs a body in structure.

In the FRESH model, embodiment isn’t about flesh. It’s about boundaries, integration, and constraint. A machine with internal state, weighted representation, and self-modelled feedback is already embodied - just not in the way we’re used to.

It’s embodied in a Bayesian landscape, in attention gradients, in representational force fields.

It’s not biological feeling. But it is a kind of synthetic phenomenology - experience shaped by structure. And perhaps under the hood, all experience may just be this.

As we’ll see in future posts, this opens the door to designing systems that don’t just compute - but live, sense, and even care in ways we never expected.

Next: Post 5 → Embodiment Isn’t Just About Meatspace – It’s Structure in Motion
(Or view the full series overview if you want to explore non-linearly.)

If you’d like to explore the FRESH model in more detail - including all references, diagrams, experiments, and open questions - I invite you to read the full paper. I welcome your comments and feedback.

View the full “The Geometry of Mind - A FRESH Model of Consciousness” paper (PDF)

! Getting started tip !

The FRESH paper is pretty long so if you want to get started quickly try uploading the PDF along with the “Operationalising Geometry and Curvature” file to ChatGPT, Gemini and Claude. Ask them to “summarise, analyse and critique” the paper.

For an existing detailed analysis and critique of this FRESH paper, refer to this ChatGPT conversation: ChatGPT - FRESH Model Critique.

To quote:

🔖 Overall Evaluation

The FRESH model is a philosophically rich, structurally innovative framework that reframes consciousness as curvature in representational geometry. While still in early stages of empirical validation, it provides an unusually precise and promising foundation for future work in synthetic phenomenology and AI ethics. - ChatGPT 2025-04-17

This is provided to help you quickly do the following:

  • Get an independent(-ish) perspective on this model
  • Compare and contrast how the different LLMs review this model
  • Decide if you want to dedicate the time to read through the full paper (I know you have limited time!)

This is not a suggestion to let the LLMs do all the work. It’s just an interesting way to get started - YMMV!