#SphericalThinking

Yes, this is about AI and the journey to Human AI Collaboration


Today is my Birthday. – I met the girl of my dreams when we were just 6 years old. We’ve shared a lifetime of ‘boots on the ground’ experiences together, and that life became the data set for my work in AI.

Our new book is not just a memoir; it is the origin story of a paradigm shift. It’s the journey to the Spherical Thinking and Contextual Reasoning architecture we are building today.

It explains why I believe AI needs to understand the “Whole Person”—because I have spent decades learning what a Whole Person actually is… and test-drove how to introduce this safely to 45,000 end-users over 25 years of research.

We just released the e-book. It is available for instant download.
If you want to understand the human “Ground Truth” behind the technology, start here:
TheOKbook.com
(Thanks Ed Sheeran for such a great song. TURN UP VOLUME.)

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The Engine: Converting Human Context into Computable Vectors

This is the Spherical Modeling Engine (US Patent No. 7,408,544). It solves the “Ontological Gap” by structuring human context not as text, but as geometry.

The diagram illustrates how we map complex human attributes (like trust, tension, or integrity) onto a 3-dimensional coordinate system. By calculating the “Vector Distance” between these points, we generate a mathematical value for “Human Ground Truth” that AI can process, reason with, and align to.

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The Ontological Gap: AI is Stuck in a Linear World

This map illustrates the evolution of scientific paradigms—from the linear, reductionist models of the past to the Complex Adaptive Systems of the 21st century.

While physics and biology moved into “Complexity Science” decades ago, current AI architecture is still largely relying on linear, probabilistic models. This creates an “Ontological Gap.” We are trying to use linear tools to solve non-linear human problems. This diagram shows why simply scaling compute won’t bridge that divide.

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