Infleqtion and Nvidia solved the problem that has blocked quantum computing for 35 years. Pranav Gokhale and Sam Stanwyck explain exactly what broke, what fixed it, and why 2028 is the year of 100 qubits.

Quantum computing has always promised to transform drug discovery, battery technology, material science, and AI, but the gap between classical and quantum computing made real-world applications impossible. That changed in 2024.

Quantum computing explained by the people building it.

Pranav Gokhale, CTO of Infleqtion, and Sam Stanwyck, Group Product Manager of Quantum Computing at Nvidia, Think On Paper about how quantum and classical computing divide workloads in real time, what logical qubits actually unlock, and why Jensen Huang believes every Nvidia GPU supercomputer will eventually have a quantum core.

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Chapters

(00:00) Why quantum computing matters right now 

(01:20) Why Nvidia is betting big on quantum 

(02:52) NVQ-Link: the bridge between quantum and classical computing

(09:29) Who decides what runs on the quantum computer vs the GPU?

(12:33) AI helping quantum, quantum helping AI 

(16:56) Building a space elevator battery: a real quantum workflow 

(20:09) The quantum algorithm zoo 

(22:04) From noisy qubits to logical qubits 

(24:00) How much energy does a quantum computer actually use? 

(27:05) The no-cloning theorem

(27:20) The biggest unanswered question in quantum computing

(30:47) A $20M NASA program and a telescope for underground 

(33:32) What do we want humans to be?

Philip Johnston is the CEO of Starcloud. He put an Nvidia H100 chip in space and gave a TED talk about it. As you do if you're responsible for building the infrastructure for space-based data centers. 

Elon Musk was not the first. He follows in the footsteps of Mr Johnston. And so, rather than Mr SpaceX, our first technology reaction video is this TED talk from San Francisco.   

We watched it for the first time. Live. On TV. 

This is not theoretical. It's also not up to date. Philip filmed this in October 2025. Starcloud have already launched the Nvidia H100 on a Falcon 9 up into space. 

It's happening disruptors and curious minds. It's happening. 

Philip predicts most data centers will be in space within 10 years. 

We agree. 

Please enjoy the show.

Cheers, 

Mark & Jeremy.

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Dr. Philip Metzger spent nearly 30 years at NASA before joining the University of Florida to research what happens when rockets land on the moon.

Rocket exhaust blows lunar dust at three kilometers per second. Without an atmosphere to contain the blast, every launch becomes a global event. A 40-ton lander one kilometer from an antenna will jam it after ten launches. NASA's Artemis program wants a sustained lunar presence. China aims for 2029. Multiple nations and private companies are racing to the moon.

But no one has agreed on how much damage is acceptable or who decides.Elon Musk concluded we cannot build enough AI on Earth without environmental catastrophe and said factories must be built on the moon. When AI production moves to space, Metzger's research shows it will drag the entire space economy upward to values billions of times Earth's current output.

If a few people control an industry that produces a billion times Earth's economic value, democracy cannot survive. They will buy politicians and control militaries. The stakes couldn't be higher. Metzger now directs the Stephen Hawking Center for Microgravity Research and Education, creating programs for students worldwide to develop space technology, own intellectual property, and start companies. Questions answered:- After Artemis, will NASA still have a role to play?- What makes Starship critical for lunar operations?- When will data centers in space be cheaper than on Earth?- Are hotels on the moon actually viable?- Why mine the moon for Helium-3?- When will asteroid mining become profitable?- Why does lunar rocket dust create international conflict?- What is "fully autonomous luxury communism"?- How can students globally participate in space and own IP?- What can past economic revolutions teach us about space?- What products make economic sense to manufacture in space?- What are the environmental limits of launch rates?- How does space ownership affect democracy's survival?Metzger led NASA's research on rocket blast effects for lunar missions - studying how rocket exhaust affects the airless moon and the infrastructure that will be built on the surface. He now directs the Stephen Hawking Center for Microgravity Research and Education, working on how to democratize space ownership globally.Please enjoy the show.Cheers, Mark & Jeremy.

Please enjoy the show.

Cheers, 

Mark & Jeremy.

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Take your Thinking Further. 

Stephen Hawking Center: https://sciences.ucf.edu/physics/microgravity/lab/

Philip X: https://x.com/drphiltill

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TIMESTAMPS

(00:00) Introduction to Space Exploration and Economics

(01:26) NASA's Role in Future Space Exploration

(06:45) Impact of Rocket Exhaust on Lunar Soil

(14:39) Geopolitical Challenges in Space

(23:39) Democratizing Space for Future Generations

(33:45) Emergent Forces vs. Hierarchical Forces

(34:08) Exploring Microgravity Applications

(38:39) Rapid Fire Space Technology Opinions

(44:02) The Future of Humans and Technology

Iona delivery drones are not your typical multi-propeller drone. They're small planes with a bathtub-sized cargo bay, but take off vertically, then the propellers tilt and it flies like an actual aircraft.

Listen up disruptors and curious minds! Today we're Thinking On Paper with CEO and founder Etienne Louvet. 

On the agenda?

• A new logistics vertical in the sky
• Why British weather is the perfect training ground for delivery drones
• What BVLOS actually means
• Why "beyond visual line of sight" is critical
• Why Iona are deliberately working under the strictest aviation regulators instead of going somewhere easy. 

Please enjoy the show.

Cheers, 

Mark & Jeremy.

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

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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 explained 

(26:08) Drones and privacy concerns 

(30:45) Implementing 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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We taught technology to generate music before we taught it how to assign fair credit to musicians. Nicholas Ponari explains why Overtune rejects one-prompt AI music generation in favor of human-in-the-loop creation. 

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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What is the value proposition of going into space? What is the killer app? How do we make money? And specifically, looking at space stations and satellites, do the economics actually work?In part one of our Space to Grow book club, we learned how SpaceX reduced launch costs by 97%. Matthew Weinzierl and Brendan Rosseau showed us how NASA gave the keys to private industry. The result was dramatically cheaper access to space.

But so what?

Who cares?

So A bunch of billionaires can go to space for less money than before. What does that mean for you?

What does that mean for me?In Part 2, we bring in the skeptics. They ask reasonable questions.

Why spend money on hotels on the moon when there are problems on Earth? Why mine asteroids for precious metals when we have problems here?

The pursuit of space is inspiring, but inspiration can blind us to reality.Outside of a few obvious existing users like satellites and government science missions, how could the rest of us and organizations benefit from lower costs to orbit?

How much of what the optimists see as potential will turn into reality?Please enjoy the show.

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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

Shapol led rocket launches before building AI to prevent the wrong switch from crashing your favorite apps. Two-thirds of data center outages are caused by human error.

Someone flipping the wrong switch is all it takes to bring down AWS. Airplanes can't take off, hospitals can't function. AI can fix this. 

Shapol, CEO of Entangl, explains how his company is solving this billion-dollar problem with AI-powered autonomous operations that understand every circuit, server, and switch in a data center.

In This Episode:

- Why 18-month generator lead times force risky shortcuts

- How VR trains engineers without touching live systems  

- The path from standard operating procedures to AI-guided work

- Space-based data centers and manufacturing futures

- Kevin Kelly's question: What should humans become?

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About Shapol:

Shapol and co-founder Antanas previously oversaw four rocket mission launches. Frustrated with engineering design software, they created Entangl - a platform that automates data center operations, generates maintenance procedures in real-time, and integrates with building monitoring systems to predict failures before they happen.

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Key Topics:

Data center reliability, AI automation, infrastructure operations, space manufacturing, autonomous systems, cloud computing, engineering design

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?