Drone delivery is not about filling the sky with quadcopters, Etienne Louvet argues.

It is about rebuilding light-cargo logistics for places where vans, ferries, roads, and traditional delivery networks struggle: islands, remote communities, rural routes, hospitals, offshore platforms, and hard-to-reach homes.

The conversation explains how Iona Drones is building fixed-wing VTOL aircraft for autonomous last-mile delivery, carrying parcels under 20 kg over long distances while navigating BVLOS flight rules, aviation regulation, weather, privacy, detect-and-avoid software, manufacturing, and the economics of making drone logistics cheaper than sending a vehicle for one parcel.

Enjoy.
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TIMESTAMPS

(00:00) Intro 

(01:50) How much weight can drones carry

(02:29) What counts as light cargo 

(06:51) How drone regulations actually work 

(13:04) Self-assessment and risk management 

(14:12) Getting municipalities to say yes 

(16:38) Weather problems 

(19:48) Where Iona Drones is now 

(20:58) Maximizing payload capacity 

(21:58) Drone design choices 

(23:27) BVLOS

(26:08) Drones and privacy

(30:45) Drones in existing logistics 

(35:02) Where autonomous delivery is headed 

(39:30) Technology and human progress

Can you use AI to think better or think more critically? Philosopher Pia Lauritzen says no. The second we give up to the shortcut use AI, we are letting go of the very basic condition that forces us to think.

When we ask if machines can think, the first question should be: why do humans think? Why do we think?

For Pia, it is fairly simple. We think because we know there is something we do not know. We have a problem. There is a gap. A gap between what I know and what I want to know. 

So I have to start thinking. That is why I ask these questions and that is why I put up with this pain in my head of trying to figure something out that I do not know.

The machine does not have that problem. It does not know that it does not know. 

It is like an animal. 

It does not know that it does not know. 

Of course it is a matter of how you understand thinking. But if you consult the old thinkers and not just the engineers and technologists, then you will have a really hard time finding anyone who would say that a machine could ever think. 

And if it cannot think itself, why should it be able to help us think? We are the only ones who know how to do that.

This is the core problem. AI feels helpful. It removes the discomfort of not knowing where to start. It fills the blank sheet. But that discomfort is not a bug. 

That discomfort is the feature. That discomfort is what thinking is.

And it is at this point that I am reminded of the scene in Con Air. Define irony.

Please enjoy the show.

Cheers, 

Mark & Jeremy.

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

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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.

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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. 

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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.

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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.

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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.

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Email: [email protected]

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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?

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--

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.

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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.

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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:

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• 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?