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The Man Who Proved We Can’t Control AI (And What That Means for Humanity) | Roman Yampolskiy
Dr. Roman Yampolskiy joins me to explore one of the most urgent and uncomfortable questions of our time: what happens when we create intelligence that surpasses our own? We unpack the difference between the AI tools we use today and the emergence of artificial general intelligence, and why the transition from narrow systems to self-improving intelligence may mark a point where human control is no longer possible. Roman shares why even the people building these systems do not fully understand how they work, and why that gap in understanding becomes exponentially more dangerous as capabilities increase.
In this conversation, we explore the limits of control, prediction, and safety in a world where intelligence can recursively improve itself beyond human comprehension. Roman lays out why the problem of AI alignment may be fundamentally unsolvable, what timelines experts are realistically considering, and why even a single mistake at that level could have irreversible consequences. This episode invites a deeper reflection on what we are creating, what we assume we can control, and whether humanity is prepared for the intelligence it is bringing into existence.
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André’s Book Recs: https://www.knowthyselfpodcast.com/bo… 00:00 Intro 01:25 What Is AGI and Why Should We Be Scared? 05:17 Roman’s Journey: From Optimism to Impossibility 09:07 The High Risk, Zero Reward Equation 13:01 Why Superintelligence Is Uncontrollable, Unexplainable, and Unverifiable 18:00 How Long Do We Have? The AGI Timeline 21:24 How Superintelligence Could Actually Kill Us 23:28 Are We Living in a Simulation? 28:21 Can AI Become Conscious? 31:28 Ad: BiOptimizers 32:41 The Possible Timelines: Terminator, the Matrix, or the Zoo 42:24 I-Risk, X-Risk, and S-Risk: Three Ways It Goes Wrong 46:31 The Human Meaning Crisis: Jobs, Purpose, and What’s Left 49:02 Ad: Based Bodyworks 50:20 What Empowers Us as Individuals Right Now 59:37 The Race to Doom: Who’s Building It and Why They Won’t Stop 1:07:41 Can AI Be Conscious — and Does It Already Have Internal Experiences? 1:12:41 Hacking the Simulation: Quantum, DMT, and Escaping the Code 1:18:30 Simulation Theory, Religion, and the Same Ancient Map 1:29:34 The Deal Roman Would Offer Altman, Dario, and Elon 1:39:44 What Is Humor? A Computer Scientist’s Theory 1:43:03 What Comes After: Singularity, Death, and Knowing Thyself ___________ Episode Resources: https://www.romanyampolskiy.com/ https://www.amazon.com/Unexplainable-?tag=lifeboatfound-20… / andreduqum
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___________ 00:00 Intro 01:25 What Is AGI and Why Should We Be Scared? 05:17 Roman’s Journey: From Optimism to Impossibility 09:07 The High Risk, Zero Reward Equation 13:01 Why Superintelligence Is Uncontrollable, Unexplainable, and Unverifiable 18:00 How Long Do We Have? The AGI Timeline 21:24 How Superintelligence Could Actually Kill Us 23:28 Are We Living in a Simulation? 28:21 Can AI Become Conscious? 31:28 Ad: BiOptimizers 32:41 The Possible Timelines: Terminator, the Matrix, or the Zoo 42:24 I-Risk, X-Risk, and S-Risk: Three Ways It Goes Wrong 46:31 The Human Meaning Crisis: Jobs, Purpose, and What’s Left 49:02 Ad: Based Bodyworks 50:20 What Empowers Us as Individuals Right Now 59:37 The Race to Doom: Who’s Building It and Why They Won’t Stop 1:07:41 Can AI Be Conscious — and Does It Already Have Internal Experiences? 1:12:41 Hacking the Simulation: Quantum, DMT, and Escaping the Code 1:18:30 Simulation Theory, Religion, and the Same Ancient Map 1:29:34 The Deal Roman Would Offer Altman, Dario, and Elon 1:39:44 What Is Humor? A Computer Scientist’s Theory 1:43:03 What Comes After: Singularity, Death, and Knowing Thyself ___________.
Penrose vs EWOG: Consciousness and Quantum Collapse
Consciousness beyond penrose quantum microtubules?utm_source=share&utm_medium=member_android&rcm=ACoAADcXNX8BNm6vE2wHF7V91czmcuYXcuPHhY4.
🧠⚛️ Beyond Penrose: Can Consciousness Be Derived from Geometry? For more than 30 years, Roger Penrose and Stuart Hameroff proposed that consciousness emerges through Objective Reduction (OR) inside neuronal microtubules. Penrose’s key equation is remarkably simple: τ_OR = ℏ / E_G where: τ_OR = collapse time ℏ = reduced Planck constant E_G = gravitational self-energy of the spacetime superposition The idea is: 🌌 Spacetime superposition ⟶ Gravitational instability ⟶ Wavefunction collapse ⟶ Conscious event But a major question remained: ❓ What is the mathematical mechanism that actually causes collapse? The EWOG framework attempts to provide one.
Maths is Cooked: AI’s Latest Breakthrough — And What’s Next
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As AI continues to improve its reasoning abilities, mathematicians are increasingly worried about the computer algorithms replacing them. In late May, those fears got even worse when OpenAI revealed that one of its general-purpose reasoning models had written a proof solving a math problem that’s sat unsolved for more than 80 years. But should they actually be worried? Let’s take a look.
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Scientist’s ‘mini‑universe’ measures time without clock
The experiment addresses a long-standing question in physics — in some theories of the universe, there is no built‑in clock so how do you tell what comes ‘before’ and ‘after’ without external time?
Professor Barontini showed that the system follows the standard equations of quantum physics and demonstrates that deep questions about the nature of time — usually discussed only in theories about the universe as a whole — can be tested in controlled laboratory experiments.
The experiment provides a powerful testbed for ideas in quantum cosmology and gravity, meaning that ideas relating to the early universe can now be tested experimentally in the lab.
Brain-computer interface enables independent, accurate communication for man living with ALS
A new study demonstrates that a person with severe paralysis caused by amyotrophic lateral sclerosis (ALS) can use a brain-computer interface (BCI) at home to communicate, work and interact with the digital world—without the need for researcher support. Published in Nature Medicine, the results mark a significant step toward delivering practical assistive technology for people with severe speech and motor impairments.
The BCI system was developed at UC Davis, in collaboration with colleagues at Brown University and Mass General Brigham Neuroscience Institute. It is equipped with advanced decoding algorithms that translate neural signals into text (speech BCI) and enable cursor control (movement BCI). It allows full interaction with a personal computer.
The brain-computer interface is designed to restore communication and computer control by decoding neural activity linked to attempted speech and movement. Although recent advances have achieved high accuracy in research settings, real-world adoption has been limited by two key challenges: independent at-home use and reliable long-term performance.
Alonzo Church
His revolutionary idea? Before “computer science” was even a field, Church invented the lambda calculus (λ-calculus)—an elegant, abstract system for expressing computation through pure mathematical functions. In 1936, he used it to prove that no universal algorithm could ever decide the truth of all mathematical statements, solving Hilbert’s famous Entscheidungsproblem in the negative. This became known as Church’s Theorem, and it revealed something profound: there are hard limits to what any machine can compute.
That same year, Church articulated what we now call the Church–Turing thesis: any problem that can be “effectively calculated” can be computed by a Turing machine—or equivalently, expressed in lambda calculus. When Alan Turing learned of Church’s work, he traveled to Princeton to study under him. Together, they proved their two seemingly different models of computation were fundamentally equivalent, laying the bedrock for all future computer science.
Alonzo Church was born on June 14, 1903, in Washington, D.C., where his father, Samuel Robbins Church, was a justice of the peace [ 5 ] and the judge of the Municipal Court for the District of Columbia. He was the grandson of Alonzo Webster Church (1829−1909), United States Senate Librarian from 1881 to 1901, and great-grandson of Alonzo Church, a professor of Mathematics and Astronomy and 6th President of the University of Georgia. [ 6 ] As a young boy, Church was partially blinded by an air gun accident. [ 7 ] The family later moved to Virginia after his father lost his position at the university because of failing eyesight. With help from his uncle, also named Alonzo Church, the son attended the private Ridgefield School for Boys in Ridgefield, Connecticut. [ 8 ] After graduating from Ridgefield in 1920, Church attended Princeton University, where he was an exceptional student. He published his first paper on Lorentz transformations [ 9 ] in 1924 and graduated the same year with a degree in mathematics. He stayed at Princeton for graduate work, earning a Ph. D. in mathematics in three years under Oswald Veblen.
He married Mary Julia Kuczinski in 1925. The couple had three children: Alonzo Jr. (1929), Mary Ann (1933), and Mildred (1938).
After receiving his Ph.D., he taught briefly as an instructor at the University of Chicago. [ 10 ] He received a two-year National Research Fellowship that enabled him to attend Harvard University in 1927–1928, and the University of Göttingen and University of Amsterdam the following year.
Simplifying complex ideas in sketches
What would you see if you tried to travel alongside a light wave at the speed of light? And suppose you held a mirror in front of you as you zipped along. What would you see in the mirror? This and similar thought experiments were posed by the young Albert Einstein to himself in his teens. It’s come to be known as Einstein’s Mirror and is also the title of a popular book on relativity. It would at first seem that light, reflected off your face, could never reach the mirror to, in turn, reflect back into your eyes to see it. So what would you see? It was only years later that Einstein developed a theory that answered this puzzle. And it required some fundamental adjustments to how we understood the world, which still bend my mind to think about them. These include: You can’t travel at the speed of light. Time is not fixed; it is relative. The speed of light is a universal constant—it is the same, independent of the motion of the source. Einstein wrote: “After ten years of reflection, such a principle resulted from a paradox upon which I had already hit at the age of sixteen: If I pursue a beam of light with the velocity c [the velocity of light in a vacuum], I should observe such a beam of light as a spatially oscillatory electromagnetic field at rest. However, there seems to be no such thing…” — Autobiographical notes, 1949 I’ll try to explain a little as I understand it. Our usual experience is that velocities are additive. Suppose I am on a moving train carriage and I throw a ball from the back of the carriage to the front. For an observer outside the train, that ball moves at the speed of the train plus the speed of the ball relative to me. But light behaves differently. As you approach the speed of light, the energy required to keep accelerating approaches infinity. In effect, you can’t reach the speed of light. So an observer of a flying Einstein wouldn’t see light travelling from him to the mirror at twice the speed of light. What changes is time. For the high-speed Einstein, the light would appear to travel away from him to the mirror and back at its usual immense speed. However, for an observer, what would only seem a moment for the high-speed Einstein might take years for the rest of us—the experience of time changes with velocity. It’s a remarkable turn for a simple and fascinating question. It’s amazing to me that the young Einstein would both pose this question, continue work on it, and then think to question some of the most self-evident facts of our world as we experience it: that time is not fixed, that a speed cannot be reached, and of course, ultimately, that energy is matter. The book Einstein’s Mirror is co-authored by my Dad (respect!). It’s full of photographs, fascinating stories, and the characters that moved physics forward. It includes the people, events and science central to another of Christopher Nolan’s films, Oppenheimer. Perhaps Christopher read it 🤔 Related Ideas to Einstein’s Mirror Also see: Laplace’s Demon Redshift Looking back in time The Doppler Effect Sonic Boom The most beautiful equation — Earlier this year, we attended a showing of Christopher Nolan’s Interstellar at the Royal Albert Hall in London with Hans Zimmer’s soundtrack played by a live orchestra. It was a fantastic way to experience a remarkable film—a film that manages to make black holes, wormholes, and time slippage both understandable (largely) and part of the plot. It strikes me as an astonishing achievement for a mainstream film.
The AI tools shaping patient care may be operating outside regulatory oversight. MIT researchers say it’s time to change that
Every day, across thousands of American hospitals, artificial intelligence quietly shapes decisions that determine patient outcomes. An algorithm flags a patient as high risk for sepsis; a risk score informs whether a woman receives additional cancer screening; a deterioration model triggers an alert that sends a care team to a bedside. These tools are embedded in the workflows of nearly two-thirds of US hospitals, integrated into the electronic health record systems clinicians rely on daily. But many have never been reviewed by the FDA.
A new viewpoint in The Lancet Digital Health, co-authored by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic, traces how this problem took root, why it carries serious consequences, and what genuine transparency would require to fix it.
The argument, the scientists say, is not that AI has no place in clinical decision-making. It is that a $4 billion market of clinical decision support tools operates largely beyond public accountability, leaving patients and providers often unable to know whether the tools influencing their care have been validated, by whom, or for which populations they work as intended.