Thinking On Paper

"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
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◼ Listen on Apple Podcasts: Apple Podcasts
◼ Follow Mark: LinkedIn
◼ Follow Jeremy: LinkedIn
#quantumcomputing #quantumgames #mothquantum #quantumphysics #creativeai #technology #podcast