Working on Geneosophy, which deals with comprehension and enables the formalization and verification of concepts such as life and intelligence.
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.