Why we still don’t understand the universe — and how the Universal Momentum Model might change that.
The View from Flatland
For a long time now, I’ve been using the term Flatland to describe the kind of incomplete, surface-level thinking that dominates much of mainstream science and technology. Even as people talk about higher dimensions, multiverses, and exotic particles, it’s clear that many are still stuck in two dimensions — conceptually if not literally.
They reduce the universe to equations on a graph. A flipbook of events. An animation sketched out on the whiteboard of spacetime. But that’s not how reality works.
The universe doesn’t sit still. It moves. It flows. It spins. It’s made of interactions, not static snapshots. Everything is dynamic — and at the deepest level, nothing is ever at rest.
What I’ve discovered — what I’ve been able to observe and explain — comes from accepting that the universe isn’t flat. It isn’t made of abstract math pasted onto static geometry. It’s real. It’s alive. And everything we experience is a part of that reality.
The Original Flatland
In 1884, a schoolmaster named Edwin Abbott published a book called Flatland: A Romance of Many Dimensions. It’s the story of a two-dimensional world, inhabited by geometric beings who live their entire lives on a plane. One day, a square is visited by a being from the third dimension — a sphere — and is given a glimpse of a reality he never imagined.
When he returns to Flatland and tries to explain what he saw, he’s mocked, ridiculed, and eventually imprisoned.
It was written as a satire of Victorian society — but it also became a timeless metaphor. A reminder of how limited our perception can be when we’re trapped in a particular paradigm.
And today, nearly 150 years later, we’re still living in Flatland.
Flat Thinking in Physics and AI
Modern science prides itself on its complexity — its particle accelerators, deep field telescopes, and theoretical frameworks stacked 12 dimensions high. But underneath it all, much of it still treats the universe like it’s unfolding on a flat page.
These models are brilliant in their own way — but they’ve grown brittle. They rely on patches, exceptions, and invisible math to explain away inconsistencies. And when reality doesn’t fit the graph, we’re told to trust the graph.
Even in AI, we see the same pattern. Most models today are essentially very advanced flatteners — turning the world into sequences of tokens, images into grids, meaning into probabilities. It works, up to a point. But it can’t truly engage with the motion of the world. It can’t perceive flow, or force, or the dynamic nature of being.
It doesn’t move like the universe. It just approximates it.
The Universal Momentum Model: A New Dimensional Lens
This is where the Universal Momentum Model (UMM) comes in.
UMM proposes that the fundamental substance of the universe isn’t matter or energy, but structured momentum. Everything we see — particles, waves, fields, even time itself — emerges from the coherent interplay of circulating momentum.
Instead of imagining the universe as a frozen geometry or probability cloud, UMM invites us to see it as a living system: rotating, pulsing, interfering, recombining. The structures we observe aren’t objects in space. They’re patterns in flow. Like whirlpools in a river, they appear stable — until they’re not.
This view doesn’t reject existing science — it completes it. And it reframes many of the so-called mysteries we observe — dark matter, cosmic asymmetries, quantum strangeness — not as glitches in our understanding, but as natural outcomes of momentum in motion.
The universe doesn’t need to be made more complex. It needs to be understood more deeply.
UMAI: Building Intelligence That Moves
Just as UMM reimagines physics, UMAI (Universal Momentum Adaptive Intelligence) reimagines intelligence.
Today’s AI models are impressive, but they’re stuck in Flatland. They react to inputs based on frozen weights and static token logic. They don’t evolve in real time. They don’t adapt. They don’t flow.
UMAI is designed differently. Inspired by UMM, it treats learning as a momentum-based interaction — a continuous adaptation of internal dynamics in response to external forces. Instead of being trained once and deployed statically, UMAI is always adjusting, always tuning, always responding.
It’s not just simulating thought. It’s living in motion.
This makes UMAI more flexible, more responsive, and potentially more aligned with the real world — because it’s built on the same principles as the real world.
The Way Out of Flatland
The biggest problem with Flatland isn’t that it’s two-dimensional. It’s that the people in it think it’s all there is.
We don’t need to believe in simulations or holograms or infinite string theories to explain the universe. We just need to look closer at what’s actually here. The answers aren’t hiding in abstract math or ten-layer dimensions — they’re here, tangible, in the whirl and push and pull of momentum itself.
Even “thinking outside the box” still traps us on the page — a flat, 2D abstraction of a universe that’s anything but.
Music isn’t music on the page. Music is only music when things start to move — your lips, your hips, your alpha-wave dips.
Maybe reality is the same. Maybe when we stop trying to document it, and start learning to move with it, then we’ll know how the whole thing flows.
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Further Reading
• Universal Momentum Model (contact me directly for the paper if interested)
• Flatland: A Romance of Many Dimensions by Edwin A. Abbott (1884) (https://www.gutenberg.org/ebooks/201)
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Author’s Note:
The Universal Momentum Model (UMM) is a theoretical framework I developed to explore the fundamental connections between classical and quantum phenomena. Through UMM, I aim to understand how adaptive intelligence and natural systems exhibit both deterministic and probabilistic behaviors. The concepts discussed in this article are part of my ongoing research into how UMM principles can be applied to AI, computational systems, emerging technologies, and more.