Thinking On Paper

Scott Crowder, VP of Quantum Adoption at IBM, shows us what’s inside a quantum computer, from the hardware that hangs inside the fridge where the qubits live to IBM’s System One from 2018.

He shows how the hand-wired early machines gave way to superconducting flex cables carrying thousands of signals, and what IBM’s 2029 fault-tolerant quantum computer will look like.

It fits in a room, not a football field.

📺 Watch our full conversations on IBM’s road to 2029: https://www.youtube.com/watch?v=pigjajbkFXw&t=1204s

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

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

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#MindUploading #BrainEmulation #AndersSandberg #Transhumanism

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

"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

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

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

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

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

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.

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