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What Managing the Risks of Fire Can Teach Us About Managing the Risks of AI

Fire is one of humanity’s oldest and most transformative discoveries. It brought light to darkness, warmth to cold, and revolutionized everything from cooking to industry. Yet fire is also inherently dangerous. It has burned down forests, razed cities, and claimed countless lives. How did humanity reconcile the risks of fire with its immense potential? The answer lies not in eliminating fire, but in learning to manage it—proliferating its safe use, developing safeguards, and distributing its benefits across society. The same lessons apply to artificial intelligence (AI). Like fire, AI is a powerful tool that can create or destroy depending on how it is controlled. Current debates on the "AI alignment problem"—ensuring AI acts in humanity's best interests—often focus on limiting AI development to prevent catastrophic outcomes. However, the history of fire management suggests a different approach: encouraging the development of multiple, diverse AI systems, each with its o...

What is Zen Neoplatonism - Attempting to make Sense of John Vervaeke via AI

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 I don't understand anything John Vervaeke says, so I asked Claude.ai to make sense of it. Have fun.  Zen Neoplatonism: A Path to Ultimate Reality John Vervaeke, a leading thinker addressing the modern "meaning crisis," introduces Zen Neoplatonism as a framework for integrating the spiritual depth of Zen Buddhism and Neoplatonism . By merging the contemplative traditions of the East and West, Zen Neoplatonism aims to foster a profound relationship with Ultimate Reality and address contemporary existential challenges. The Advent of the Sacred Vervaeke begins by highlighting what he calls the “Advent of the Sacred,” a resurgence in interest around the concept of the sacred and how humans relate to Ultimate Reality. This interest stems from a deep need to find meaning in a time when traditional systems of belief are in decline. He proposes Zen Neoplatonism as a way to engage with this emerging sacredness by creating a dialogue between Zen and Neoplatonism. These two tradit...

Response to "Frontier Models are Capable of In-context Scheming": A World AI Cannot Fully Navigate

The recent paper, Frontier Models are Capable of In-context Scheming , highlights the emerging capabilities of advanced AI systems to strategize, deceive, and manipulate in pursuit of assigned goals. It paints a picture of AI as a potentially autonomous actor capable of significant agency. However, the concerns raised in the paper must be tempered with a fundamental truth: no matter how intelligent AI systems become, they are attempting to operate in a world fundamentally designed for human actors—a world they cannot fully navigate. Intelligence, even at the level exhibited by frontier models, is not equivalent to agency in the real world. The limitations imposed by the physical, bureaucratic, and social systems in which these AI systems operate act as significant bottlenecks, making true autonomy a daunting, if not insurmountable, challenge. Physical Constraints: The Inescapable Boundary Advanced AI remains bound by the physical infrastructure that supports it. While AI models may sim...

How the Universe Works, One Flip at a Time

When we think about the universe—its vastness, its complexity, its mysteries—it’s easy to feel overwhelmed. How did everything come to be? What keeps it all going? These questions can feel as unanswerable as the universe is infinite. But what if I told you there’s an equation that explains how everything—time, space, energy—happens? It’s simple, profound, and kind of beautiful: Ψ ( t ) = d B ( t ) d t \Psi(t) = \frac{d\mathcal{B}(t)}{dt} ​ Before you roll your eyes at the math, let me break it down for you. This little formula might just explain how the universe works. And no, I didn’t come up with it myself—an AI helped me shape it based on some ideas I had. I’ll admit, I don’t fully understand all the physics behind it, but I think the concept is fascinating. The Universe as a Light Switch At its core, the universe is built on a simple binary: it’s either on (Being) or off (Non-Being). Think of it like a light switch. The “on” state represents everything that exists—matter, energy,...

Dear Physicists: How to Use the Functional Fuzziness Framework (FFF) Without the Metaphysics

The Functional Fuzziness Framework (FFF) introduces a foundational binary of "Being" and "Non-Being" as the basis for its descriptions of spacetime emergence, dark energy, and quantum foam. While this binary has metaphysical connotations, you don’t need to accept or embrace its metaphysical roots to explore its practical implications and potential to address gaps in current physics. How You Can Use FFF Without the Metaphysics Treat the Foundational Binary Operationally Think of the foundational binary not as a metaphysical truth but as a mathematical abstraction describing discrete state transitions. The logistic function B ( t ) B(t) B ( t ) models these transitions. Ψ ( t ) \Psi(t) Ψ ( t ) , the rate of transition, is a measurable proxy for causality flow. Use these as tools for describing the emergence of spacetime properties without needing to delve into their ultimate origin. Focus on Observable Effects The framework provides predictions tied to measurable p...

The Functional Fuzziness Framework (FFF): Refining Dark Energy and Quantum Foam

The Functional Fuzziness Framework (FFF) explores the nature of spacetime, dark energy, and quantum foam as emergent phenomena driven by a foundational binary: "Being" and "Non-Being." In this post, we refine the mathematics behind these concepts and delve deeper into how they might connect to observable physics. 1. Foundational Binary and Causality Flow The FFF starts with a foundational binary , representing transitions between "Being" ( 1 1 1 ) and "Non-Being" ( 0 0 0 ): B ( t ) = { 1 (Being) 0 (Non-Being) \mathcal{B}(t) = {1(Being)0(Non-Being) B ( t ) = { 1 0 ​ (Being) (Non-Being) ​ To model smooth transitions, we use a logistic function: B ( t ) = P ( t ) = 1 1 + e − k ( t − t 0 ) \mathcal{B}(t) = P(t) = \frac{1}{1 + e^{-k(t - t_0)}} B ( t ) = P ( t ) = 1 + e − k ( t − t 0 ​ ) 1 ​ The causality flow ( Ψ ( t ) \Psi(t) Ψ ( t ) )—a measure of the transition rate—is defined as the deriva...

Functional Fuzziness Framework (FFF): Key Equations

Foundational Binary The foundational binary describes the interplay between Being and Non-Being: B ( t ) = { 1 (Being) 0 (Non-Being) \mathcal{B}(t) = {1(Being)0(Non-Being) B ( t ) = { 1 0 ​ (Being) (Non-Being) ​ To smooth transitions, we define: B ( t ) = P ( t ) = 1 1 + e − k ( t − t 0 ) \mathcal{B}(t) = P(t) = \frac{1}{1 + e^{-k(t-t_0)}} B ( t ) = P ( t ) = 1 + e − k ( t − t 0 ​ ) 1 ​ The flow of causality is given by: Ψ ( t ) = d B ( t ) d t \Psi(t) = \frac{d\mathcal{B}(t)}{dt} Ψ ( t ) = d t d B ( t ) ​ Planck Length The Planck length is the smallest meaningful unit of spacetime: ℓ P = ℏ G c 3 \ell_P = \sqrt{\frac{\hbar G}{c^3}} ℓ P ​ = c 3 ℏ G ​ ​ It arises naturally from the interplay of the constants ℏ \hbar ℏ (Planck's constant), G G G (gravitational constant), and c c c (speed of light). Speed of Causality The speed of light, c c c , represents the maximum speed of causality: c = 1 (in natural units) c = 1 \qu...