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 stand at a peculiar moment in human history. Our technical capabilities have never been more impressive—we can manipulate matter at the atomic level, build machines that mimic human conversation, and map the neural activity of living brains in real time. Yet our deepest questions remain as mysterious as
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.
Dr. Marcus Doubtful, former quantum physicist turned philosopher of science. Dr. Andrew Sofist, a computational physicist and AI researcher who has just delivered a triumphant presentation on large language models' reasoning capabilities. Andrew: Marcus, I have to say your critique of AI during the Q&A was... unnecessarily
Dr. William Compute – CTO of a Fortune 100 company Dr. Marcus Doubtful – physicist turned philosopher William: Marcus, with all this talk about Artificial Intelligence, I’ve been rethinking what computers can actually achieve. Marcus: That’s unexpected coming from you. Especially now — AI is advancing in every field. You can’
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
The Alchemist's Equivalence: a dialogue. Dr. John Computationalist, a computer scientist, sits across from Dr. Marcus Doubtful, a physicist turned philosopher. John: Look, Marcus, I think you're being way too doom-and-gloom about where we're headed. Yeah, sure, we don't have all the
You check your blog and realize it's been eleven months since your last post—ironically, that post was itself a reassurance that you were still around after a previous silence. Time has a peculiar way of dissolving when you're immersed in work. Eleven Months In that
The truth is, I've been busy with a significant breakthrough: the first implementation of a Geneosophic expression. Specifically, I've been working on the conceptual expression of a neuron, which can be verified in the third person and executed on a computer.