The Illusion of Time in Software When you watch a video game character run across a screen, witness a real-time stock ticker update, or see a physics simulation unfold, you're experiencing what appears to be continuous, flowing time. But this is a carefully orchestrated illusion. At its foundation,
We assume intelligence is computable not because we’ve proven it, but because we’ve lost the ability to conceptualize it any other way. We are no longer using computation to model reality; we are forcing reality to fit the model. * Alex: Senior engineer at a leading AI lab, 15
A Journey Through the Paradoxes of Reductionism and the Promise of Geneosophy The Pattern Behind the Paradoxes Modern knowledge has achieved extraordinary success. We've mapped the genome, simulated quantum systems, built artificial intelligence that mimics human conversation, and created technologies that transform civilization. Yet beneath this triumph lies
When we try to formalize a neuron computationally, we don't translate biology into code—we perform a violent collapse. We lock causation into fixed arrows when biology lives in causal ambiguity. We synchronize incommensurate timescales onto a global clock when neurons operate in genuine temporal incoherence. We close
We live in a computational age. When we want to formalize our thoughts—to express ideas precisely, to build models of intelligence, to create systems that reason—we almost instinctively reach for computation. The Church-Turing thesis tells us that any "effectively computable" function can be computed by a
A brain structure has persisted for 500 million years across fish, amphibians, reptiles, birds, and mammals. The basal ganglia should tell us something fundamental about intelligence itself. Yet when viewed through the computational lens, it makes no sense at all. The problem isn't the basal ganglia. The problem
There's a curious linguistic asymmetry that might explain one of the deepest divides in Western philosophy. It hides in plain sight, in something as simple as how we talk about feeling cold. The Cold Divide In English, we say: "I am cold." In Italian and French,
When Plato proposed that reality consists of two worlds—one of changing appearances and another of eternal Forms—some of his contemporaries must have thought he'd lost his mind. When Kant suggested that objects conform to the structures of our minds rather than the reverse, the philosophical establishment
Philosophy has wrestled with seemingly intractable problems for millennia: How does mind relate to body? What makes knowledge objective rather than merely subjective? How do we bridge the gap between inner experience and outer reality? These questions have spawned countless theories, debates, and entire philosophical traditions, yet they remain as
Not every domain of inquiry requires genosophical investigation. Understanding when geneosophy applies—and when traditional approaches suffice—clarifies both its potential and its proper limits. The Traditional Domain: Working Within Given Concepts Science, mathematics, programming, AI, and most philosophy operate successfully within what we might call "conceptually closed"
Philosophy of science promises to do something extraordinary: step outside the scientific enterprise to examine its foundations, methods, and assumptions with clear-eyed objectivity. From Thomas Kuhn's revolutionary analysis of paradigm shifts to Hasok Chang's sophisticated pragmatist approach to scientific practice, philosophers of science have attempted to
Philosophy has been wrestling with a fundamental question for centuries: How do we bridge the gap between mind and world? Each major philosophical tradition has offered solutions, but each has also revealed new problems. Today, we stand at a unique moment where quantum mechanics has deepened these puzzles while a
The story of artificial intelligence is not just one of increasing computational power—it’s also a story about how machines relate to meaning. Or more precisely, how meaning has been progressively sidelined in favor of statistical pattern manipulation. To understand this, we can trace AI’s evolution through a
We live trapped in a circle of our own making. We reason with concepts about objects and other concepts. We understand objects through concepts. We create new concepts by combining existing objects and concepts. Around and around we go, never stepping outside this conceptual machinery to ask the most fundamental
We live in an age of breathtaking technical sophistication and profound existential confusion. We can manipulate matter at the atomic level but can't agree on what makes life worth living. We've mapped the human genome but struggle to understand human nature. We've built global
We live in a Kafkaesque paradox: the very people we turn to for wisdom about life’s biggest questions—meaning, society, the future of humanity—are systematically selected for their inability to think about such things. Consider this absurd pattern: A tech entrepreneur optimizes engagement algorithms for maximum user addiction,
What if I told you that the deepest mysteries plaguing human knowledge—consciousness emerging from matter, the mind-body problem, infinite regress, self-reference paradoxes—aren't profound features of reality waiting to be solved, but artifacts of a particular way of asking questions? Every academic discipline, from quantum physics to
Something extraordinary hides in plain sight beneath our modern academic landscape. Physics, mathematics, biology, psychology, philosophy—these impressive disciplines that organize our understanding of the world—all rest upon a foundation they can no longer see. Like a great tree whose roots have been forgotten, our specialized fields of knowledge
Marcus Doubtful, a physicist turned philosopher. Richard Trad, a mathematician turned philosopher. Both have spent decades thinking about the foundations of knowledge, but they've reached very different conclusions. Richard: Marcus, I've been reading your recent work on disciplinary self-reference. While I find your historical analysis interesting,
I’m not questioning the usefulness of LLMs and AI in general. What I am questioning is its ability to achieve intelligence. Large Language Models (LLMs) are remarkable tools—tools to augment one’s intelligence—just as a search engine, or Wikipedia have done before them. I use them daily.
We believe we are at the cutting edge of history, but we may just be repeating its oldest mistakes. From the Sophists’ empty rhetoric to the Alchemists’ blind experimentation, humanity has a long history of mastering technique without possessing understanding. This dialogue explores how today’s AI-driven world is creating
If a machine can mimic a thought, does it mean it is thinking? This dialogue strips away the hype of modern AI to reveal the "Code That Could Never Think." By examining the structural limitations of computation, we explore the difference between a system that follows rules and
A debate between two scientists about whether traditional science can truly capture the concept of life.
Every year, thousands of bright minds enter neuroscience programs driven by a profound question: How does the brain work? They emerge years later with advanced degrees, sophisticated experimental techniques, and an uncomfortable realization—despite accumulating vast amounts of data about neural mechanisms, the fundamental mystery remains unsolved. We can map