Demystifying HDT² Verifiable Knowing in an AI-Driven World

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Collapse Theory

Bruce Tisler

10 episodes

2 months ago

Collapse Theory explores how knowledge isn't found—it's shaped. Each episode follows a catalytic question through the HDT² grammar: Ω (intent), Δ (entropy), Φ (resolution), and Ψ (recursion). Hosted by Bruce Tisler, this podcast dives into the cognitive physics of inquiry—where questions act like particles and collapse defines meaning. For thinkers, builders, and seekers ready to transform how we know. The voices used in this podcast is synthesized using AI text-to-speech technology. All rights to the original written content are retained by the author.

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Physics

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Demystifying HDT² Verifiable Knowing in an AI-Driven World

Collapse Theory

35 minutes 15 seconds

2 months ago

Demystifying HDT² Verifiable Knowing in an AI-Driven World

Demystifying HDT²: Verifiable Knowing in an AI-Driven World

Asking an AI, How do you know that?

This podcast we pull back the curtain on how we think and reason in an age where AI can mimic intelligence but struggles to prove its validity. We explore HDT² and its Φ-Stable Artifact as structural safeguards for truth, reasoning integrity, and verifiable knowledge.

The Challenge We Address is AI-generated answers often sound confident, but are they actually valid? We examine the crucial difference between "good enough to believe" and "structurally proven," revealing hidden biases, contradictions, and reasoning shortcuts that compromise knowledge quality.

You'll gain clear, verifiable insights into AI reasoning processes. Using practical tools for detecting flawed logic and weak arguments and an ability to distinguish between generated answers and validated knowledge. Today more than ever we need skills and tools to evaluate epistemic validity in any context.You'll learn to trace how ideas evolve, understand why they hold up under scrutiny, and identify potential failure points before they become problems.

We want everyone to think more clearly about thinking itself—whether you're evaluating AI outputs, making business decisions, or simply wanting to separate signal from noise in our information-saturated world.