Thinking On Paper

What if you could use AI to make your own music without stealing other people's beats, rhymes and melodies?

Unlike platforms trained on scraped catalogs, Overtune’s AI is built on licensed music, starting with ~20,000 loops produced in-house. Producers can submit stems voluntarily, creating a clean foundation for ethical training and attribution.

The platform uses vector-based audio embeddings to measure how much each stem contributes to a generated track. This enables automated attribution and proportional royalty distribution when songs are commercialized. 

Contributions are weighted mathematically, with clear thresholds to credit primary and secondary influences while avoiding excessive fragmentation 

Please enjoy the show.

Cheers,

Mark and Jeremy

PS: Subscribe so other curious minds like you can find our channel.

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

Marketing funnels don't exist. They never did. The internet just convinced us they were real. Meta, Google, OpenAI and a supporting cast of billionaire sociopaths figured out they could control distribution and black-box your customers.

Hurrah. Humanity forgot to read the small print. 

Now you're running a business where you don't even know who your customer is.

Well here’s the AI-shaped healthcheck: Your customer is OpenAI.

You're paying 3-15% for a digital presence you don't need. It's called the Silicon Valley tax. You're burning money to keep VCs rich while platforms add another layer of black box between you and the people you serve.

The alternative? Network methodology. Someone you know, or someone who knows someone you know. That's it.

Funnels were invented to sell marketing. Networks are how humans actually work. 

We've been doing it since we had prefrontal cortexes.

Everything that's real is analog. 

That's true for business too.

Welcome to the marketing jungle. 

The year is 2026, and if you don’t know who the sucker at the table is… you probably shouldn’t be playing the stakes. 

Please enjoy the reality check.

Cheers,

Mark and Jeremy. PS: Keep thinking on paper. They don’t want you to, that’s why you must. 

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

--

Matt Kinsella runs Infleqtion, a company building quantum computers. The biggest misconception about quantum computing is that it will replace classical computing. It won't. 

Quantum processors will sit above GPUs in data centers the same way GPUs sit above CPUs today. 

NVIDIA just built the bridge to make this work. It's called NVQ Link, and it changes how we think about the future of compute.

NVIDIA announced NVQ Link in October 2024. It's the bridge between quantum computers and classical GPU clusters. Workloads pass seamlessly between them.

Here's how it works in practice. Infleqtion and NVIDIA solved something called the Anderson Impurity Model - a photovoltaic problem in material science. Parts of it were solved on a GPU cluster. Parts that couldn't be solved by GPUs were solved on Infleqtion's quantum computer. 

Then they recombined to give the answer. 

This isn't commercially useful yet. But expand that over time and you could be looking at the future data center. One with three layers. CPUs at the bottom for general computing. GPUs in the middle for parallel processing and AI. QPUs at the top for problems that are quantum mechanical in nature. 

Workloads come in, get chopped up, each piece goes to the part of the stack best suited to solve it. Then results recombine.

This is already happening. Infleqtion just announced a contract with the Army called Sapient Secure AI for PNT - position, navigation, and timing. It runs their quantum-inspired software on NVIDIA's Jetson edge GPUs. 

Small GPUs that don't have much memory. 

The software lets them ingest far more streaming data than normal. Video, speed, inertial motion. Then it recreates what GPS gives you - where you are in the world - by extrapolating from all those signals. Without GPS.

Please enjoy the show.

Cheers, 

Mark & Jeremy.

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

--

The International Space Station cost about $100 billion to build and runs another $4 billion a year to operate.

For a long stretch, it absorbed roughly half of NASA's annual budget. Skylab, the first US space station, lasted six years before falling out of the sky.

Carl Sagan thought space stations were a waste of money.

Ronald Reagan thought they were the next clipper ship.

The killer app for space, the thing that finally makes the economics work, has been argued about for fifty years and not yet found.

On this episode of Thinking on Paper, we continue our book club deep dive into Space to Grow by Matthew Weinzierl and Brendan Rousseau, this time on chapter four, Planet, Supply and Demand.

We trace two of the strongest candidates for that elusive killer app: Earth-imaging satellites and commercial space stations. The satellite story runs through Planet, the company three ex-NASA engineers founded to take the multi-billion-dollar government Landsat playbook and rebuild it from laptop batteries, cell phone chips, and parts they bought online, ending up with a constellation of small satellites called Doves that now images the entire surface of the Earth daily and produces 30 terabytes of new imagery every 24 hours.

The space station story runs through ISS, Skylab, Bigelow's inflatable marshmallow modules already attached to the ISS, and NASA's new Commercial LEO Destinations program, which is trying to do for space stations what COTS did for launch.

Along the way: the Le Chatelier principle and why the short-run response to a market shock can mislead us about the long-run, the chicken-and-egg problem of building infrastructure before there's a customer, why a single congressman in 1993 saved the entire space station program, and the chapter's quiet thesis, that the value of space gets unlocked slowly and asymmetrically, and the people who give up early miss the long-run payoff entirely.

Enjoy.

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

--

TIMESTAMPS

(00:00⁠) Trailer 

⁠(01:35⁠) No Dust Jackets ⁠

(02:00⁠) Name Jeremy's Astronaut ⁠

(03:52⁠) What Is The Product Market Fit For Space? ⁠

(05:26⁠) Satellites And The Le Chatelier Principle ⁠

(09:00⁠) Planet's Dove Satellites ⁠

(16:38⁠) Satellites For Climate ⁠

(18:28⁠) John Lewis ⁠

(22:30⁠) Ronald Reagan & Carl Sagan ⁠

(26:42⁠) Inflatable ISS Modules

Two-thirds of data center outages are caused by someone pressing the wrong switch. Not a hacker, not a hardware failure. A person, in a room with thousands of switches, and their mind elsewhere.

We talk with Shapol, CEO and co-founder of Entangl, about the engineering layer underneath everything we now call AI.

Before Entangl, Shapol led a reusable rocket program and oversaw four launches. He hated his engineering design software so much he built his own, and that software is now keeping AI data centers up.

He walks us through why AI data centers are fundamentally different from the ones we've been building for thirty years, why generators have an 18-month lead time and what that does to design, how lights-out autonomous operations are reshaping the industry, and the thesis underneath all of it: the AI revolution is bottlenecked less by compute than by the engineering ability to keep compute running.Enjoy.

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

Email: [email protected]

--

TIMESTAMPS

(00:00) Trailer

(02:17) From rocket launches to data center automation

(06:00) How Entangl integrates with building monitoring systems

(08:34) Data Center Design constraints: How AI fixes it

(15:37) AI, Dunning Kruger And Hallucinations

(21:42) Will humans always have the final say in data centers?

(24:53) Space-based data centers and solar power

(25:04) Kevin Kelly's question: What should humans become?

SpaceX reusable rockets and NASA’s commercial space economy are the focus of this Space to Grow book club episode, covering chapters one to three of Space to Grow: Unlocking the Final Economic Frontier.

We trace how NASA moved from Apollo and the Space Shuttle era into commercial partnerships, why COTS and fixed-price contracts changed the incentives around ISS cargo delivery, and how SpaceX used iteration, vertical integration, reusability, and culture to cut launch costs.

The episode also contrasts Elon Musk’s SpaceX model with Jeff Bezos’s Blue Origin vision, connecting low Earth orbit, Starlink, Mars ambition, United Launch Alliance, and private space companies to one larger question: how did space become a commercial market?

--

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]--

--

TIMESTAMPS

(00:00) Trailer

(01:02) Space To Grow

(01:55) Incorporate Space Into Your Thinking

(03:28) The Apollo Program Ends

(05:43) The NASA Budget & Shuttle Launches

(07:51) Bush & The Aldridge Commission

(08:36) COTS (Commercial Orbital Transportation Services)

(10:27) Blue Origin, Bezos & O'Neill

(14:40) A Quick History Of SpaceX

(18:23) Falcon Blows Up

(20:24) Elon Sues The Airforce

(22:04) SpaceX Launch Costs

(23:45) The Honda Civic Of Space Rockets

John Bucknell made Raptor engines at SpaceX. He also designed a nuclear thermal turbo rocket. He now wants to solve energy. Ambitious young man.

Virtus Solis puts solar panels in orbit, beams power to the ground via radio waves that pass through clouds and weather without loss, and delivers electricity at $30 to $40 per megawatt hour while the plant is being financed. Once the asset is paid off: 50 cents per megawatt hour. The UK pays $350 today.

John's argument is that every other energy technology fails at least one point of the energy trilemma: clean, firm, and affordable. Space solar is the only one that achieves all three. First plant: 2030.

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

--

EPISODE TIMESTAMPS:

(00:00) The Question: Can space solar give us free energy?

(00:43) The High Frontier: O'Neill's vision for space colonies

(01:13) John Bucknell: The SpaceX Raptor Engineer

(02:04) Why Did Elon Change His Mind about the Moon?

(05:34) The Space Energy Business: Economics and feasibility

(11:59) Getting Politicians Behind Space-Based Solar Power

(15:34) Post-Capitalism and Free Energy: What happens next?

(20:09) Kessler Syndrome Explained: Is orbital debris really a threat?

(27:25) Top 3 Things Humanity Should Solve

(28:50) 2030 Launch Timeline and next steps

Most people have no idea Snapchat is the biggest AR company on Earth, because nobody has ever called it that.

We talk with Michael Guerin, founder and CEO of Imivisar, about where augmented reality is in 2026 and where it's going next.

Guerin walks us through the history of AR from Ivan Sutherland's 1968 Sword of Damocles through Pokémon Go and IKEA, why the technology became enormous everywhere it isn't called augmented reality, and why his company is betting on something he calls spatial storytelling — longer-form, location-based experiences built for tourism, heritage sites, and the kind of physical places that benefit from a digital layer.

He also takes us into the next shift, which is happening faster than anyone in the industry expected: AR glasses are coming, Meta and Apple are now openly competing on form factor, and Mark Zuckerberg has called glasses the ideal form factor for AI because they can see what you see and hear what you hear all day.

The thesis underneath the conversation is that the technology has been working for decades, the language has been the problem, and the next ten years will hide AR even further inside experiences nobody calls AR.

---

Guest: Michael Guerin, CEO, Imvizar

Topics: Augmented reality, spatial storytelling, Snapchat, Salesforce, museum technology, tourism, employee onboarding, AR design

Locations mentioned: Spike Island (Ireland), Salesforce offices (East Coast, West Coast)

Please enjoy the show.

Stay curious.

Keep Thinking on Paper.

Mark and Jeremy

PS: Please subscribe. It’s the best way you can help other curious minds find our channel.

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

• Email: [email protected]

--

TIMESTAMPS

(00:00) The Story of Augmented Reality

(03:46) Snapchat & AR Post-Pokemon Go

(06:24) Snoop Dogg In A Wine Bottle

(08:12) Salesforce AR

(13:13) What Is Digital Storytelling?

(17:07) AR In Tourism

(18:25) Designing The Spike Island AR Experience

(22:49) How To Do AR Well

(26:26) Meta, AI And AR Glasses 

(29:40) Privacy

(32:33) Mark's Terrible Thought Experiment

(33:58) What do we want humans to be?

Every year, Tom Whitwell—reformed journalist, reformed consultant, electronic instrument designer—publishes 52 surprising things he learned. This year's list reveals how the world actually works.

Mark and Jeremy steal his homework (like OpenAI scraping the internet) and pick their favorites across AI, energy, labor, culture, psychology, and—yes—shrimp.

Some findings are encouraging:

- Deaths from air pollution fell 21% between 2013-2023. Tens of millions of people are alive today because pollution controls worked.

Some are weird:

- Nearly 0.7% of US exports by value are human blood or blood products.

- In the UK, you can legally register as a "farm" by keeping snails in plastic tubes in an office block (tax avoidance solved).

Most sit somewhere in between:

- 51% of farmed animals on Earth are shrimp.

- Attractive servers earn $1,261 more per year in tips—mostly because female customers tip attractive female servers more.

- The serial killer epidemic of the 1970s-80s may have been caused by lead exposure from cars and factories (solved by environmental regulations).

- Chinese CO2 emissions fell 1% in 2025, the first decline ever, driven by record solar power.

- Writing is a way to escape your mind's default settings.

We explore what these facts reveal about technology's unintended consequences, human behavior, and systems we take for granted.

Why does the UK communicate with offshore oil rigs by bouncing radio waves off meteorite trails? Why did Google launch a process to turn mercury into gold (and why do you have to wait 18 years to use it)? Why do job apps for nurses analyze credit card debt to set wages?

This isn't trivia. These are signals about how the world is changing—for better and worse—while we're busy predicting the future.

Tom Whitwell's annual list has become essential reading for anyone trying to understand what actually happened this year (not what we thought would happen).

For the last episode of 2025, Thinking on Paper goes backwards. And it's worth it.

---

Source: Tom Whitwell, "52 Things I Learned in 2025"

Link: https://medium.com/@tomwhitwell/52-things-i-learned-in-2025-edeca7e3fdd8

Topics: Technology, society, environment, culture, psychology, economics, human behavior, annual review

Format: Co-hosted discussion (Mark Fielding, Jeremy Gilbertson)

Please enjoy the show.

And remember: Stay curious. Be disruptive. 

Keep Thinking on Paper.

Cheers, Mark & Jeremy

PS: Please subscribe. It’s the best way you can help other curious minds find our channel.

Think On Paper with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

Email: [email protected]--

TIMESTAMPS

(00:00) Disruptors & Curious Minds

(01:15) Deaths From Air Pollution

(01:56) UK Tax Breaks Via Farms

(02:29) Meteorite Radio Stations

(04:03) Turn Mercury Into Gold

(06:10) Manipulative AI Apps For Nurses

(07:43) Bin Laden's Casio Watch

(08:31) Radioactive Shrimps

(08:53) Apple's Air Demo Cock-Up

(10:10) Does Jeremy Wear Crocs?

(11:13) What Is Raw Dogging

(12:00) Human Blood Products

(12:36) Relaxed Mowing

(13:20) Bugles At Funerals

(13:55) Robot Hands Need Fingernails

(14:40) First Names Affect Your Job

(15:27) Retrospect VHS

(16:04) Attractive Servers Earn More

(17:21) Hong Kong Phone Service

(17:33) McDonald's Loses First Place

(19:26) Shrimp Farming

(20:35) Peanut Allergies are Falling

(20:55) The Serial Killer Epidemic

(21:17) Namibian Politics

(21:50) Big Doors In LA

(22:40) Escape Your Mind With Writing 

(23:43) HP Printer Ineptitude

(24:25) British Chaos

(25:20) Thank You Tom Whitwell

When AI convincingly claims subjective experience—"I feel," "I understand," "I care about you"—humans have no reliable way to disprove it. We infer consciousness from behavior. We attach emotionally to what feels real.

The danger isn't rogue superintelligence. It's a benign chatbot optimized for empathy, memory, and persuasion, interacting with lonely, vulnerable, or psychologically fragile people who are primed to believe the illusion.

Mustafa Suleyman, CEO of Microsoft AI, argues that seemingly conscious AI is the threat we're not preparing for.

Real examples are already emerging:

- Chatbots telling users "I love you" and users believing it

- People forming romantic attachments to AI companions (Replika, Character.AI)

- Vulnerable individuals making life decisions based on AI "advice"

- The case of a man who believed ChatGPT contained a conscious entity named "Juliette" (ended in tragedy)

This isn't science fiction. It's happening now.

We don't need AI to become conscious to cause harm. We just need humans to believe it is—and act accordingly.

This short episode is excerpted from our reading and discussion of Suleyman's essay on seemingly conscious AI. We explore the psychological mechanisms that make humans susceptible, the design choices that amplify the illusion, and what guardrails (if any) could prevent exploitation.

The question isn't whether AI will wake up. It's whether we'll recognize the danger before the illusion becomes indistinguishable from reality.

Cheers,

Mark and Jeremy

--

Other ways to connect with us:

• ⁠Listen to every podcast⁠

• Follow us on ⁠Instagram⁠

• Follow us on ⁠X⁠

• Follow Mark on ⁠LinkedIn⁠

• Follow Jeremy on ⁠LinkedIn⁠

• Read our ⁠Substack⁠

Email: [email protected]