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Thinking On Paper

Mark Fielding and Jeremy Gilbertson

The human story of technology. Are you tired of the algorithm choosing everything for you? In a world increasingly vibe coded by 20-year-olds and run by billionaires, this is where you think about technology for yourself.

I'm a technology writer and snowboarder. Jeremy is a musician who builds data centres. Every week we cross swords with the CEOs, founders and outliers of tech and culture. We’ve talked quantum with IBM, AI with Microsoft and Space tech with NASA.

Under it all? What the hell does it all mean for you, your work and your family.

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  • 30 episodes
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  • English

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  • November 3 · 7 min

    The unknown geopolitics of mining trillion dollar asteroids

    There's enough gold, platinum, and rare earths hurtling around our solar system, to sink global economies. Asteroid mining could invalidate the US dollar, says AstroForge CEO Matt Gialich. It's also an indication of what all the fuss is about. So, trillion-dollar asteroids... who actually owns them? U.S. space law essentially says companies can keep the material they bring back, but they do not own the asteroid itself. Legally, AstroForge doesn't own the rock. But realistically, as Matt says, who else is going to mine them? “If I can go mine the universe and I am the sole supplier of resources from the universe, well now Earth becomes beholden to me.” Please enjoy the show. Links & Resources 📺 Watch more space interviews with NASA, SpaceX, and ESA: Space Playlist on YouTube Connect with Thinking on Paper 🌐 Website & Show Notes: thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Spotify: Listen on Spotify 🍎 Apple Podcasts: Listen on Apple Podcasts

  • October 30 · 18 min

    Consciousness, the philosophy of mind and how to upload your brain │ Anders Sandberg

    Anders Sandberg expects computers to run human-sized brains within a few decades. In 2008, he and Nick Bostrom wrote Whole Brain Emulation: A Roadmap, which put the most likely date at around 2060. And before you say, "There's no way I'll upload my brain to the internet in twenty years," Anders is confident about the computing power. The open question is getting your scanned brain data to behave like a real brain. As if the rest is easy. He explains how far a simulated fruit fly has already got, why AGI might arrive before brain emulation, and what scanning the brain of a philosopher who doubts machines can be conscious might teach us. Then we get weird. Or weirder. If you copy yourself, which one is married to your spouse? And how many of you would be too many? Anders would form an upload union. He imagines copies that spend the same weekend in two places, then merge their memories. And he explains why we'd need AI auditors to stop one person uploading a million copies of himself to win an election. Please enjoy the show. Connect with Thinking on Paper 🌐 Website & Show Notes: thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Spotify: Listen on Spotify 🍎 Apple Podcasts: Listen on Apple Podcasts Chapters (00:00) Can a simulated brain be conscious? (03:00) When will we upload a human brain? (08:45) Life as an emulated mind (12:46) A hundred copies of you (18:07) Uploading into humanoid bodies ------- #MindUploading #BrainEmulation #AndersSandberg #Transhumanism

  • October 24 · 6 min

    A Harvard economist on who writes the next space treaty

    Who writes the next space treaty? We put the question to Harvard economist Matthew Weinzierl and Blue Origin's Brendan Rosseau, co-authors of Space to Grow. Neither wants a master plan. Weinzierl would start by gathering 25 to 30 leading thinkers from start-ups, government and non-profits. Yet he is sceptical that any room can design the future of space from the top down. He prefers order that emerges on its own. Rosseau begins with the end state: competition that drives progress, no military conflict, and rules of the road like those that govern the sea. He doubts one grand treaty could deliver that, and suggests a little strategic ambiguity may even help. Please enjoy the show. And subscribe if you do. Full Episode & Links • Watch on YouTube: https://www.youtube.com/watch?v=tnInzxdiFkk&t=1363s Connect with Thinking on Paper 🌐 Website: https://www.thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Listen on Spotify: Listen on Spotify 🍎 Listen on Apple Podcasts: Listen on Apple Podcasts Chapters (00:00) You're in charge of space. Now what? (01:04) Matt: "I like emergent order" (02:39) Brendan: competition yes, war no (04:41) Why not one grand treaty? (05:22) The four-word rule for space #SpaceTreaty #SpaceToGrow #ThinkingOnPaper

  • October 22 · 13 min

    Is this why you shouldn't let AI write for you?

    "AI is a very poor writer," says celebrated author, hip-hop historian, and Bruce Lee biographer Jeff Chang. While large language models can mirror sentence structures or copy paragraphs, Chang argues that the raw output is garbage. He also shares insights from his interview with legendary hip-hop producer DJ Shadow on his KALW radio show, Notes from the Edge. Shadow calls generative AI music "corny" and warns that those hyping artificial intelligence tools are usually the ones profiting from them. This leads to the ultimate question for modern creators: If you rely on AI for ideation, are you actually being creative? In this episode, we cover: • Why Jeff Chang writes every word himself and limits AI to research • The craft of revision: Why great non-fiction requires four drafts • Insights from Karen Hao, DJ Shadow, and the commercial hype around AI tools • How analog constraints, turntables, and four-track recording built modern sampling culture • The difference between machine-generated ideas and human artistic judgment • Could an 18-year-old produce the next Endtroducing..... using generative AI models? Please enjoy the show. Connect with Thinking on Paper 🌐 Website & Show Notes: thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Spotify: Listen on Spotify 🍎 Apple Podcasts: Listen on Apple Podcasts Chapters (00:00) Does Jeff Chang Use AI to Write? (01:33) The Revision Process: Why Great Writing Takes Four Drafts (04:51) Karen Hao, DJ Shadow, and Why AI Music Feels "Corny" (07:18) What Analog Sampling Culture Teaches Us About AI (11:32) Ideation vs. Artistry: Can You Be Creative If AI Does the Thinking? (13:20) Could an 18-Year-Old Make the Next Endtroducing..... with Generative AI? .. #jeffchang #djshadow #generativeai #hiphopculture #sampling #writingcraft #creativity #thinkingonpaper

  • October 20 · 7 min

    What is Yann Lecun's world model? Part 1

    If you want superintelligence inside robots and autonomous agents, a Large Language Model (LLM) isn't enough, AI needs a true world model. In this episode of Thinking On Paper, Mark and Jeremy get their heads around world models, how they work, and why they represent the next frontier of superintelligence. Pim de Witte, CEO of General Intuition, recently sat down with Meta Chief AI Scientist Yann LeCun at Station F in Paris to frame the limits of current AI. De Witte compared LLMs to a snowball rolling downhill: it can't see the crash coming because "its entire world is just itself." Meanwhile, traditional video generation models act like a dream, you watch the frames unfold, but you can't interact or change the outcome. A true world model acts like a lucid dream: an interactive simulation where the agent acts, and the model accurately predicts what happens next. Jeremy also explains why game studios still struggle to code believable stadium crowd physics fan-by-fan, and how spatial-temporal world models can learn emergent crowd dynamics instead. We discuss: • Video Models vs. World Models: Why visual generation is passive "dreaming" while world modeling is interactive "lucid dreaming" • The Snowball Metaphor: Why LLMs lack true physical perception and spatial reasoning • Epistemic Uncertainty: How AI handles what it hasn't seen in its training data • Aleatoric Uncertainty: Managing real-world randomness that can never be eliminated • Diffusion vs. V-JEPA: Comparing image-based diffusion predictors to Yann LeCun's Joint-Embedding Predictive Architecture • The Backrooms Effect: Why AI video models generate blurry faces and show visual doubt when predicting futures Please enjoy the show. Connect with Thinking on Paper 🌐 Website & Show Notes: thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Spotify: Listen on Spotify 🍎 Apple Podcasts: Listen on Apple Podcasts Chapters (00:00) Video Models vs. World Models: Dreaming vs. Lucid Dreaming (00:41) Why Video Game Stadium Crowds Still Look Fake (01:44) Can Compute Alone Recreate Realistic Stadium Crowds? (02:09) Predicting Multi-Agent Outcomes with Spatial AI (02:55) LLMs as Snowballs: The Lack of Physical Perception (04:00) Epistemic Uncertainty: What the Model Hasn't Seen (04:35) Aleatoric Uncertainty: Managing Inherent Randomness (05:16) The Backrooms & Blurry Visuals: How Models Express Doubt (06:24) Diffusion vs. JEPA: Two Architectures for Predicting the Future (06:55) How Generative Image Models Turn Noise into Reality #worldmodels #artificialintelligence #yannlecun #pimdewitte #robotics #generalintuition #spatialai #jepa #thinkingonpaper

  • October 15 · 54 min

    The mind-bending science of trapped electron quantum computers

    You don't need a PhD to enjoy learning about quantum computing. This is the proof. Johannes Pollanen, CTO of EeroQ, thinks on paper about quantum computing, electron spin qubits, and scaling the future of quantum technology. EeroQ has its chips made in commercial semiconductor foundries, coats them in a thin layer of superfluid helium, and floats single electrons about 10 nanometres above the surface. Without a PhD, you'll learn: • Why quantum computers already exist, and why they aren't the machines we need yet • Superconducting circuits, trapped ions, neutral atoms, silicon spins, photons and electrons on helium • Why helium never freezes, and why Johannes calls it "the cleanest system" for electron qubits • Why wiring together lots of dilution refrigerators sounds hard to a low-temperature physicist • What nature's identical particles teach engineers Please enjoy the show. 📚 EeroQ: https://www.eeroq.com/ 🌐 Thinking On Paper: https://www.thinkingonpaper.xyz 📷 Instagram: toptechpodcast 🎧 Watch On YouTube: https://youtu.be/Veyc5Vf6sSI 🍎 Listen on Apple Podcasts: Apple Podcasts Chapters (00:00) Quantum computing at a wedding (03:57) Reverse engineering quantum computing (05:15) Quality or quantity of qubits (06:23) The modalities of quantum computing (12:36) You'll need liquid helium (19:01) Transistors and silicon (20:21) Is that thing behind you using helium-3? (26:15) How do you cool quantum systems? (31:08) How do you make more qubits? (35:15) How do you do a computation on a qubit? (40:05) Faster quantum computers (43:45) Can IBM make a useful quantum computer? (46:00) The quantum lessons of nature (48:33) Carry over question #quantumcomputing #quantumphysics #technologynews

  • October 10 · 55 min

    Bruce Lee and the making of Asian America │ Jeff Chang

    Bruce Lee’s cultural legacy shapes modern world culture like few others. Alongside icons like Bob Marley and Muhammad Ali, his legend continues to influence action cinema, hip-hop, and martial arts philosophy. In Water Mirror Echo: Bruce Lee and the Making of Asian America, celebrated cultural biographer Jeff Chang joins Thinking On Paper to explore kung fu, mindset, Asian American empowerment, and the pop-culture history behind the man. In the second half of the show, we shift to artificial intelligence, music sampling, and the creative act. How does Jeff Chang view generative AI? What does his close friend, legendary hip-hop producer DJ Shadow, think about AI tools, sampling ethics, and machine-made music? (Spoiler: Shadow tried AI, and he thinks it's corny). How do you explain Bruce Lee to a generation raised on John Wick and The Matrix? Chang starts simply: "He’s the guy who made all of that possible." In this episode, you’ll learn: • How Bruce Lee evolved from a war baby in occupied Hong Kong and child star to cha-cha champion and Hollywood pioneer • His struggle with racism in Seattle, his role as Kato in The Green Hornet, and the famous letter he wrote promising himself $10M and global fame • The cinematic evolution between The Big Boss, Fist of Fury, and Enter the Dragon • The deeper meaning behind "Be Water" and the title Water Mirror Echo • How DJ Shadow and Jeff Chang view AI, sampling culture, and the legacy of Endtroducing • Autonomous media, machine creativity, and whether humans can truly love art created by an algorithm Please enjoy the show. Links & Resources 📚 Jeff Chang’s books & bio: jeffchang.net 📷 Jeff Chang on Instagram: @zentronix 🖊️ Read Jeff's Substack: zentronix.substack.com Connect with Thinking on Paper 🌐 Website & Show Notes: thinkingonpaper.xyz 📷 Instagram: @toptechpodcast 🎧 Spotify: Listen on Spotify 🍎 Apple Podcasts: Listen on Apple Podcasts Chapters (00:00) Bruce Lee, AI, and the First Draft (02:06) Who Was Bruce Lee? Defining a Legend (05:15) How Bruce Lee Made Zen Pop Culture (10:05) The Letter to Himself and Napoleon Hill's Mindset (15:33) Wartime Hong Kong & Martial Arts Origins (18:37) Seattle, Early Racism, and Cha-Cha Champion (21:19) The Big Boss, Fist of Fury, and Enter the Dragon (28:17) Be Water: Bruce Lee's Philosophy & Real Fighting (32:21) Water, Mirror, Echo: Meaning Behind the Book Title (34:25) Does Jeff Chang Use AI? (40:24) DJ Shadow on AI, Sampling, and Endtroducing (48:26) Generative Art: Could You Love Machine-Made Music? (54:28) Single-Mindedness and Bruce Lee's Final Legacy #brucelee #jeffchang #djshadow #ai #generativeai #watermirrorecho #asianamericanhistory #hiphopculture #thinkingonpaper

  • October 7 · 47 min

    Quantum computing goes rock and roll

    What would a gamer do with a quantum computer? Or a musician? Harry Kumar, co-founder of Moth Quantum, argues that quantum computing needs creativity and art to push the industry forward, so we’re going to find out. Moth built Quantum Backrooms, a video game where a quantum computer builds the maze. Each tile on the map is a qubit, and the correlation between two neighbouring qubits decides whether a wall stands between them. The game shows no quantum advantage and runs no faster than a classical computer. It certainly isn’t GTA 6. So why build it? Look at early AI: image generation was no better than a child’s drawing, yet millions signed up. That is the step before commercial value. People are creative and want creative tools. While using quantum mechanics for material science and protein folding is incredible, it doesn’t bring in the masses—which is why Harry is waiting for quantum computing's "Dylan-goes-electric" moment. In this episode of Thinking On Paper, we cover: • How Atlas, Moth's platform, lets you run images through a quantum computer without writing code • Whether a musician could hear the difference between quantum and classical randomness • Quantum shaders, artistic expression, and potential in music and visual effects • Why Richard Feynman's idea of a computer that works like nature excites artists • The intersection of quantum computing, AI, and autonomous media Please enjoy the show. Links & Resources • Try Atlas: platform.mothquantum.com • Moth Quantum: mothquantum.com • More quantum episodes: Watch on YouTube Thinking on Paper is a long-form interview podcast with Mark Fielding and Jeremy Gilbertson exploring the human story of technology, AI, quantum computing, and science. Chapters (00:00) Introduction to the episode and guests (01:32) Who is Harry Kumar and what is Moth Quantum? (04:18) The concept behind Quantum Backrooms and its inspiration (06:06) The end state in quantum game mechanics and creative mapping (09:58) Quantum advantage and hardware considerations (10:31) Using games to explore quantum mechanics (12:52) Target audience for quantum creative platforms (17:02) Comparison to Unreal Engine and platform versatility (20:33) Quantum shaders and potential in music and visual effects (28:27) Quantum as a new form of artistic expression (36:04) Quantum computing and the nature of creativity (44:52) Autonomous media and AI in creative processes (45:48) How to access and experiment with Moth Quantum's platform Connect with Thinking on Paper ◼ Choose your own technology adventure: https://www.thinkingonpaper.xyz ◼ Running a tech conference? Book us to host: Conference Hosting ◼ Listen on Apple Podcasts: Apple Podcasts ◼ Follow Mark: LinkedIn ◼ Follow Jeremy: LinkedIn #quantumcomputing #quantumgames #mothquantum #quantumphysics #creativeai #technology #podcast

  • September 28 · 41 min

    AI data centers don't have to make us all die of thirst

    Data centers use vast amounts of water primarily to cool air, not chips. Evaporative cooling systems chill the air that gets blown across server racks—and that evaporation is where the water loss occurs. Remove the air, and you eliminate the majority of water consumption. In this episode of Thinking On Paper, Simon Jesenko, CEO of Iceotope, explains how fanless, precision liquid cooling is revolutionizing AI data center infrastructure. By circulating 15 to 20 liters of dielectric fluid—a highly refined, safe liquid—inside a sealed chassis, Iceotope cools every single component directly without relying on air or external fans. Jesenko addresses the sensational headlines surrounding AI's water footprint, noting that critics are describing legacy air-cooled facilities. Once data centers transition to fully sealed liquid-cooled architectures, water and energy consumption drop dramatically. We discuss: • Why direct-to-chip cooling only solves 80% of server heat, and what components stay hot • What dielectric coolant liquid actually is, where it comes from, and why major energy companies like Shell and Exxon produce it • The early history of liquid cooling leaks and how it shaped the data center industry's risk aversion • Why cooling the Power Supply Unit (PSU) and memory—not just the GPU—is critical for efficiency and AI compute density • How crypto miners proved immersion cooling years before enterprise data centers • Optimizing tokens-per-watt and deploying silent edge AI infrastructure in offices and extreme environments Please enjoy the show. Links & Resources • Learn more about Iceotope: https://www.iceotope.com/ Connect with Thinking on Paper ◼ Choose your own technology adventure: https://www.thinkingonpaper.xyz ◼ Running a tech conference? Book us to host: Conference Hosting ◼ Listen on Spotify: Listen on Spotify ◼ Listen on Apple Podcasts: Listen on Apple Podcasts ◼ Follow Mark: LinkedIn ◼ Follow Jeremy: LinkedIn Chapters (00:00) Introduction to Data Center Cooling Challenges (01:07) Data Center Water Usage vs. Agriculture & Industry (03:00) Open Loop vs. Closed Loop Cooling Systems (04:18) Guest Introduction: Simon Jesenko (CEO, Iceotope) (05:02) Misconceptions About Data Center Water & Power Consumption (06:08) The Evolution From Legacy Air Cooling to Liquid Cooling (07:31) Direct-to-Chip Liquid Cooling Explained (08:40) Water Consumption: Traditional vs. Fully Liquid-Cooled Facilities (10:29) Market Transition Toward Total Liquid Cooling (12:23) Airflow Elimination & System-Level Thermal Management (13:34) Environmental Factors & Geographic Placement of AI Workloads (15:50) Integrating Precision Liquid Cooling into OEM Hardware (19:02) Future-Proofing Next-Gen High-Density GPU Clusters (22:02) Immersion Cooling History & Lessons from Crypto Mining (23:25) What is Dielectric Fluid? Safety & Environmental Impact (26:50) Market Adoption & Enterprise Opportunities for Iceotope (30:56) Optimizing PSU Thermal Efficiency & Tokens per Watt (34:15) Industry Trends in Next-Gen High Performance Computing (HPC) (37:24) Thermal Limits & Capacities of Current Liquid Cooling Tech (40:26) Daily AI Workflows & Closing Thoughts #datacenters #liquidcooling #iceotope #aiinfrastructure #gpus #sustainability #greentech #thinkingonpaper

  • September 16 · 48 min

    He lived on an island for Elon Musk, now he makes houses from grass │Nathan Silvernail, Plantd

    Nathan Silvernail quit SpaceX to make wood from grass. Building the first part of a rocket SpaceX ever reused—the nose cone—wasn’t enough. After a decade working for Elon Musk, he quit, took everything he had learned, and started Plantd. The plan? Make carbon-negative engineered lumber from fast-growing perennial grass. Climate tech meets space tech. Wood, without trees. Plantd's panels replace OSB, the oriented strand board that sheathes the floors, walls, and roofs of almost every new American home. In this hotly anticipated episode, Nathan joins Thinking On Paper to talk about his SpaceX journey, why he thinks Mars is a distraction from the work in front of us, how the lumber industry accounts for the wood it burns, and why building a material stronger than steel turned out to be wrong. You’ll get insight into the nine-month harvest cycle, what it takes to change the culture of an industry without letting it notice, and why he believes the unit economics that let SpaceX displace ULA will do the same to timber. Please enjoy the show. Thinking on Paper connects the dots between technology and what it means to be human. New episodes every week. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE 📺 Get clips and exclusive videos on Instagram Chapters (00:00) Grass building panels that replace wood (04:10) SpaceX: what the job actually cost him (07:56) What a payload fairing is and how SpaceX recovers it (11:52) Lumber: why anger put him in this industry (24:02) OSB alternative: a drop-in structural panel (28:00) Carbon negative building materials explained (29:50) SpaceX and ULA: the same playbook for lumber (35:55) Why hemp, bamboo and mycelium fail as building materials (40:14) Harvest: nine months against fifteen years (46:00) Why the Space Shuttle was retired

  • September 4 · 22 min

    48-hour launch windows - The National Space Transportation Policy prepares for war

    We read the new National Space Transportation Policy (NSPM-17) in full. Signed on August 20, 2026, this landmark directive shreds the 2013 space framework and rewrites how the U.S. approaches space launch, orbital logistics, range infrastructure, and point-to-point reentry. The War Department and U.S. Space Force are deeply embedded in this update—from expanding launch ranges and securing radio spectrum to enforcing a clause for rapid, responsive launch capabilities within 48 hours of need. You don't build a 48-hour launch mandate purely for scientific research; it signals a critical push for tactical space defense and fast satellite constellation replenishment. In this episode of Thinking On Paper, we analyze what could bottleneck this strategy. Is it rockets? Spaceports? Or market demand? With a White House target of 1,000 launches and reentries annually by 2030, current commercial demand—dominated by Starlink and smallsat rideshares—requires a 5x growth in orbital economics. Is this policy a realistic roadmap or a government-backed sales pitch? We also break down: • The National Space Transportation Policy (2026) vs. the 2013 directive • Tactical responsive space launch and 48-hour military deployment mandates • The target of 1,000 launches per year by 2030 and commercial market demand • The Mars exploration carve-outs and who America relies on for deep space • The International Space Station (ISS) 2030 retirement vs. China's lunar base plans • Commercial spaceports, federal reentry sites, and orbital infrastructure bottlenecks Thinking on Paper is a technology podcast exploring AI, space tech, quantum computing, commercial spaceflight, and the systems shaping the future. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on Apple Podcasts 📺 Get clips and exclusive videos on Instagram Chapters (00:00) Introduction to the US Space Transportation Policy (03:20) US Launch Frequency: 2025 vs 2026 (04:45) Commercial Space Industry & Market Demand Gap (06:24) US vs China Space Race & Global Competition (07:55) Launch Range Infrastructure & 48-Hour Responsive Space (10:00) Regulatory Frameworks, FAA & Spectrum Allocation (12:02) Smallsat Rideshare Economics & Market Opportunities (15:13) NASA Mars Carve-Out & Artemis Lunar Surface Goals (18:43) The Geopolitical Race to Mars & Commercial Landers (20:48) ISS Deorbiting & Realism of the 2030 1,000-Launch Target (23:22) Key Takeaways for Commercial Space Tech #spacetech #spacepolicy #nationalspacetransportationpolicy #commercialspace #spaceforce #astronomy #aerospace #spacex #thinkingonpaper

  • August 3 · 4 min

    This philosopher has analysed 30,000 questions, here's why you stop asking

    Why do we stop asking questions as adults? Philosopher and researcher Pia Lauritzen has analyzed over 30,000 questions and discovered a striking reality: our innate curiosity never actually disappears. The ability to wonder stays intact. What changes as we grow up is the social price tag. Every question requires you to admit you don't know something, and in corporate culture, nobody gets promoted for sounding ignorant. Ask the wrong question in the wrong room, and harmless curiosity starts to feel like a high-stakes interrogation—which is why most of us learn to keep our thoughts to ourselves. Lauritzen proves that our questioning instinct is only suppressed, not lost. In her keynotes, she gives audiences just one minute and two simple rules, resulting in everyone writing a thoughtful question instantly. They could do it the whole time; they just needed permission. In this episode of Thinking On Paper, we explore the philosophy of questions, why workplace structures punish curiosity, and whether artificial intelligence is actually capable of genuine thought. Be curious, stay disruptive. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on Apple Podcasts 📺 Get clips and exclusive videos on Instagram #philosophy #curiosity #criticalthinking #artificialintelligence #pialauritzen #workplaceculture #thinkingonpaper #podcast

  • July 28 · 5 min

    In a world of personalised AI music, you listen alone

    Nicholas Ponari says AI music makes live performance more valuable, not less. Mark Fielding calls the same future a hellscape. Ponari's scenario: by 2045 his son types a script into a generator, gets a feature film in the style of Kubrick crossed with Tarantino, and hits publish. Everyone becomes a creator in every medium. Nobody can consume a fraction of it, so AI becomes the largest curator in history. Mark's objection is that shared culture dies with it. No song anyone else has heard. No film anyone else has seen. Nothing left to talk about. Ponari's answer is scarcity. When everything is generated, the things that cannot be, a room, a crowd, live music, become more valuable than ever. Who's right? Full episode at thinkingonpaper.xyz. Be curious, stay disruptive. -- Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 ⁠Buy us a beer on Substack⁠ 🫵 C⁠hoose your own technology adventure ⁠ 📺 ⁠Watch our beautiful faces on YouTube ⁠ 🎧 R⁠emember Steve Jobs on APPLE⁠ 📺 ⁠Get clips and exclusive videos on Instagram ⁠

  • July 22 · 50 min

    AGI, recursive self-improvement and the global cooperation needed to not blow everything up

    The U.S. and China are racing to build artificial intelligence systems that could lead to machine superintelligence before anyone fully understands the consequences. The risk? Global economic meltdown and existential threat. Not on our watch. In this episode of Thinking On Paper, Mark and Jeremy examine "The Hard Question of AI," a thought-provoking essay by Planet CEO Will Marshall. Marshall argues that frontier AI governance now requires the same strict verification, trust, and global non-proliferation frameworks historically reserved for nuclear weapons. That means moving far beyond voluntary safety pledges. Real enforcement would require monitoring advanced hardware chips, tracking massive data-center construction and energy consumption, inspecting frontier AI labs, protecting whistleblowers, and establishing international red lines around recursive self-improvement (RSI). However, comparing AI to nuclear arms has major flaws. While weapons-grade uranium is scarce and heavily guarded, AI software can cross borders instantly—meaning a rogue actor or small lab could accidentally trigger AGI first. At the heart of the discussion lies one critical question: What would an AI Cuban Missile Crisis look like? What event could force the U.S. and China to cooperate beyond empty political rhetoric? We also cover: • Sam Altman, Dario Amodei, Demis Hassabis, and the real incentives behind AI safety warnings • The limits of voluntary tech regulation and the RAND verification framework • Recursive self-improvement and closed-loop AI growth loops • The geopolitics of the U.S.–China AI race and the supply chain bottlenecks • The Fermi paradox and whether governments can build institutions capable of managing superintelligence (Hint: they can't) Please enjoy the show. And don’t have nightmares. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on Apple Podcasts 📺 Get clips and exclusive videos on Instagram Chapters (00:00) Trailer (01:38) AI and Existential Risk (02:40) OpenAI, Anthropic & Google: The Frontier Labs (04:40) Nuclear Meltdown vs. Existential Threat (05:50) Why Everyone is Talking About the End of Humanity (08:00) RSI: Closed-Loop Recursive Self-Improvement (10:00) A Copyright and Legal Interlude (19:39) Why America and China Are Locked in an AI Race (23:51) The AI Cuban Missile Crisis: What Would It Take? (28:07) The Global AI Supply Chain and Data Centers (35:09) USA, China, and the Structural AI Dead-End (40:36) Applying the Nuclear Framework to Modern AI #artificialintelligence #agigovernance #existentialrisk #openai #anthropic #geopolitics #technologynews #podcast

  • July 14 · 41 min

    Agentic AI will increase demand for GPUs and CPUs

    AI companies are splashing billions on more GPUs before they use the ones they already have. Many sit idle, others use a fraction of their potential. For the hyperscalers, cloud providers and AI companies, buying more GPUs does not solve much if the GPUs already in the rack spend too much time waiting for the rest of the system. The next battle in the AI infrastructure wars is efficiency: GPU utilization, NICs, memory movement, networking, CPUs and software that keeps expensive hardware doing useful work. Moshe Tanach runs NeuReality AI, a company building infrastructure for AI inference. In this conversation, he explains why the next wave of AI infrastructure depends on GPU utilization, NICs, memory movement, networking and software efficiency, not just buying more chips. This is a technical conversation about AI inference, infrastructure efficiency and the hardware layer beneath ChatGPT, Claude, Gemini and the AI tools now being built into business software. Please enjoy the show. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 ⁠Buy us a beer on Substack⁠ 🫵 C⁠hoose your own technology adventure ⁠ 📺 ⁠Watch our beautiful faces on YouTube ⁠ 🎧 R⁠emember Steve Jobs on APPLE⁠ 📺 ⁠Get clips and exclusive videos on Instagram ⁠ -- Chapters (00:00) The GPU challenge (01:27) Training Vs Inference (05:45) Memory & Keeping The GPU Busy (07:31) Deep Seek, Blackwell & Ruben (09:03) How Ripe Is CPU For Reinvention? (11:03) AI Agents Run On CPUs (12:51) Do We Need All The Computation? (14:35) GPU Utilization Rates (16:50) Tokens In A Context Window (20:59) Data, Knowledge & Wisdom (23:56) Why Are Your GPUs Busy? (A Truck Analogy) (29:07) Hyperscalers (31:59) The Decode Phase (36:47) What More Efficient GPUs Means For The User

  • July 8 · 53 min

    Lab-Grown meat is coming to a BBQ near you

    Bruce Friedrich, founder of the Good Food Institute and author of Meat, explains why the future of food may depend less on changing human behaviour and more on changing how meat is produced. For more than 12,000 years, humans have relied on animal agriculture to produce meat. Bruce argues that this system is reaching its limits. We explore how cultivated meat is made, why it is attracting support from governments and major food companies, and why some of the biggest meat eaters are also the most open to the technology. Along the way, we discuss the environmental cost of livestock, antibiotic resistance, food security, infrastructure, consumer psychology, regulation, and whether this technology could become as transformative as renewable energy or electric vehicles. We also examine what happens to farmers, why culture may be harder to change than technology, and whether cultivated meat can ever reach price parity with conventional meat. If the next agricultural revolution is already underway, it may not begin on a farm. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE 📺 Get clips and exclusive videos on Instagram -- Chapters (00:00) Who Eats Cultivated Meat? (02:37) Cultural Significance of Meat (06:09) What Is Cultivated Meat? (08:25) The Science Behind Cultivated Meat (10:48) How Much Does Cultivated Meat Cost? (14:46) What does cultivated meat taste like? (17:10) Emerging Companies in the Lab Meat Industry (19:08) Industry Support for Alternative Meats (21:06) Government Role in Innovation (24:40) The Future of Animal Agriculture (28:25) Agricultural Policies for Sustainability (31:41) What Are Fermented Meats? (35:48) Meat And Antibiotic Resistance (39:32) The Invisible Costs of Meat Production (42:26) The Future of Cultivated Meat

  • June 23 · 51 min

    Commercial asteroid mining for platinum could destroy the US dollar

    Asteroid mining sounds insane until you speak to AstroForge CEO Matthew Gialich. Matthew’s team at AstroForge builds spacecraft to mine metallic M-type asteroids for platinum group metals, the unglamorous but essential metals inside phones, cars, chips, electronics and much more. AstroForge is one of the few companies trying to make space mining real, targeting metal-rich asteroids that could contain platinum, palladium, iridium and other PGMs. Why? Earth’s resources are getting harder, deeper and more expensive to reach. The good stuff is not sitting neatly on the surface. A lot of it is buried, depleted, regulated or uneconomic. In this episode, Matthew explains why asteroid mining may now be technically and economically possible, why Planetary Resources may have been too early, how SpaceX changed the capital story for space startups, and why AstroForge’s first deep-space spacecraft failed after travelling nearly a million miles from Earth. Please enjoy the show. Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE 📺 Get clips and exclusive videos on Instagram Chapters (00:00) Asteroid Mining Trailer (02:51) The Economic Necessity of Asteroid Mining (08:37) Lessons from Planetary Resources (10:43) Risk and Innovation (15:26) Deep Space Two (19:05) The Quest for Asteroid Exploration (22:20) Aliens & Life Beyond Earth (24:17) Ownership and Ethics in Space Mining (26:21) The Next Challenges in Asteroid Mining (27:56) Changing Earth's Economy (30:13) The Role of Capital (32:32) Matt's Vision for Space Exploration (35:06) The Drive to Explore the Universe (36:55) NASA's Evolution (39:17) Inside Astroforge (42:53) The Complexity of Space Engineering (44:25) Data Centers in Space (47:30) The Limitations of AI in Space Engineering

  • June 19 · 57 min

    The CIA think quantum computing will be useful

    Quantum computers could change medicine, material science and AI. Unfortunately, it's impossible to know how because the industry is buried under hype. Dr. Bob Sutor takes us on a masterclass through the conflicting headlines to the reality of quantum technology today. By the end of the show you’ll know what’s fact and fiction, where the industry is heading and how to protect yourself from AI slop masquerading as insight. We also learn about: Why “quantum supremacy” and “quantum advantage” claims should be treated carefully Why quantum computing is still in its prehistory How engineering discipline is changing the field What IBM and Cleveland Clinic’s protein simulation work shows about quantum chemistry Why money, sovereignty and technology are driving the quantum industry How governments are funding quantum computing in the United States, France, the UK, Finland and elsewhere What China may be doing in quantum computing Which industries are doing serious quantum research Why there are many quantum hardware approaches and no clear winner yet Whether helium-3 supply matters for quantum computing Bob also explains why quantum computers will be useful for specific classes of difficult problems where classical computers struggle, especially once systems become larger, more reliable and fault tolerant. The conversation ends with practical advice on separating the quantum noise from the Thinking On Paper signal. Please enjoy the show. -- Thinking on Paper is a technology podcast about AI, Space, quantum computing, science, and the systems shaping your life. 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE: 📺 Get clips and exclusive videos on Instagram (00:00) AI Quantum Slop (00:40) Welcome To The Show (06:04) When Quantum Computers Finally Become Useful (10:13) Why Governments Are Throwing Money at Quantum (15:53) Is China Ahead in Quantum? (18:48) Where Quantum Might Actually Matter (27:11) Can Quantum Help Fix Climate Change? (28:35) Why Battery Companies Care About Quantum (30:31) Why Quantum Doesn’t Belong in the IT Department (31:53) Who’s Doing the Real Work in Quantum? (32:40) Why Quantum Companies Need Real Customers (38:19) The Funding Problem Behind Quantum Progress (45:22) Does Quantum Computing Need Helium-3? (48:01) Will We Need a Quantum Computer Matchmaker? (50:38) How to Spot Quantum Hype Before You Share It

  • June 12 · 44 min

    Google search is just another victim of AI

    Awad Sayeed, co-founder and CTO of Parsnipp AI, joins Thinking on Paper to explain generative engine optimisation, or GEO, and how companies can become more visible inside LLMs. In this episode, we discuss: How generative engine optimisation differs from SEO Why context matters more than keywords in AI search How ChatGPT, Claude and Gemini use information differently What persona-based agents reveal about brand visibility How structured data helps AI systems understand websites Why comparison pages and clear product information matter What black-hat GEO could look like How AI-generated content could pollute the internet Whether brands should create separate experiences for humans and AI agents How advertising may develop inside AI assistants Awad argues that GEO doesn’t replace SEO. Strong websites, useful content and clear structure still matter. But companies now need to think about whether AI systems can retrieve, interpret and recommend their information in the right context. And as this is Thinking On Paper, we ask about the human impact, the wider change in the structure of the internet, trust, data and consumerism. Please enjoy the show. -- 🏠 Buy us a beer on Substack 🫵 Choose your own technology adventure 📺 Watch our beautiful faces on YouTube 🎧 Remember Steve Jobs on APPLE 📺 Get clips and exclusive videos on Instagram -- Chapters (00:00) Introduction to Generative Engine Optimization (03:36) Understanding Persona-Based Agents (06:23) The Transition from SEO to GEO (09:06) Context in LLMs and GEO (11:41) Black Hat Strategies in GEO (14:22) The Future of the Internet (16:58) Advertising in the Age of GEO (19:37) The Impact of GEO (28:22) The Evolution of AI Models (29:03) Integrating AI into Business Strategies (29:52) Agents vs. Humans (32:10) The Future of SEO and GEO (34:08) Tools for Visibility and Analytics in AI (36:00) Customer-Driven Development (39:23) The Role of Storytelling in GEO (42:04) Model Transparency and the Future of AI

  • June 11 · 46 min

    The UK is a technology backwater, can it compete on the world stage ever again?

    Rory Daniels, Head of Emerging Technology and Innovation at techUK, joins Thinking On Paper to discuss whether the United Kingdom can remain globally competitive as quantum computing, robotics, photonics, AI, and advanced computing converge. The UK possesses world-class research institutions, deep technical talent, and globally significant tech startups. However, its recurring bottleneck is scale: promising breakthrough technologies developed in British universities and laboratories are frequently commercialized, acquired, or funded overseas. Rory argues that the UK's true competitive edge doesn't lie in trying to out-scale Silicon Valley or China in a single isolated industry. Instead, it comes from integrating existing national strengths across deep learning, chip design, specialized robotics, quantum systems, silicon photonics, and 5G/6G connectivity. In this episode, we discuss: • What sets the UK robotics industry apart from the US and China • Why British robotics excels in harsh, specialized environments like nuclear sites, offshore wind turbines, and industrial inspection • How UK autonomous driving leaders like Wayve combine AI models, sensors, and connectivity • The delicate balance between autonomous robotaxis and London’s iconic black-cab industry • Why UK deep tech companies struggle to scale beyond early venture stages due to patient capital gaps • The critical role of universities, tech-transfer offices, and regional innovation hubs in Coventry, Edinburgh, Milton Keynes, and Barnsley • Using digital twins and physics-based simulation to train next-gen robotics and AVs • Why photonics is essential for quantum computing, plus the convergence of neuromorphic and biological computing • What government, investors, and industry leaders must do to keep British innovation scaling domestically Please enjoy the show. Thinking on Paper is a technology podcast exploring AI, space tech, quantum computing, science, and the systems shaping the future. 🏠 Buy us a beer on Substack 📺 Watch on YouTube 🎧 Listen on Apple Podcasts 📷 Clips and outtakes on Instagram Chapters (00:00) The UK Technology & Deep Tech Landscape (03:14) Robotics: A Distinct UK Industry Perspective (05:54) Autonomous Vehicles & Wayve in the UK (08:39) Dissecting the UK Innovation Ecosystem (11:05) Scale-Up Bottlenecks for UK Tech Founders (13:27) Regional Clusters & Government Innovation Initiatives (16:33) University Spin-Outs & Tech Transfer Offices (19:15) Barnsley: A Blueprint for Regional Tech Towns (21:53) National Policy & Funding Strategy in Robotics (24:20) Digital Twins & Synthetic Simulation Environments (27:12) Quantum Computing & Photonics Acceleration (29:24) STEM Education & Workforce for Emerging Tech (30:55) Artificial Intelligence, Judgment & Human Wisdom (38:02) Neuromorphic Computing: The Future of Energy-Efficient AI (38:23) Deep Tech Convergence: The UK's Multi-Tech Advantage (42:42) The Human Element & Building Public Trust in AI #uktech #robotics #quantumcomputing #photonics #deeptech #artificialintelligence #techuk #thinkingonpaper

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