Thinking On Paper

In 2009 an active American satellite collided with a defunct Russian one at 22,300 miles per hour. The resulting debris field created over 150,000 pieces of space junk that won't decay for a century. Nobody paid for it. Nobody cleaned it up... because nobody had to.

That is the tragedy of the commons in orbit, and it is getting worse. 

Conjunctions, the close-passing events that require satellites to burn fuel to avoid collision, grew from 1.7 million in 2020 to 4 million in 2022. Elon Musk has applied for a licence for a million objects. 

This episode covers: 

Kessler syndrome: the tipping point where collisions become unstoppable, and how close we are
Why the insurance market is not pricing orbital collision risk
Astroscale: the company using magnetic docking to clean up space junk, and the Siberian rocket explosion that nearly ended them
Why the economic solution to the tragedy of the commons breaks down completely in orbit
NASA Administrator Jim Bridenstine on SpaceX: "there is only one thing worse than a government monopoly"
Whether a mission-driven monopoly plays by different rules
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Timestamps

(00:00) How 150,000 pieces of space junk ended up in orbit and why nobody cleaned them up
(06:21) Kessler syndrome explained: the tipping point where collisions become unstoppable
(10:57) Why the insurance market is not pricing orbital collision risk
(13:50) Government intervention, the Moon Treaty and the five-year deorbit rule
(20:26) Active debris removal: magnets, robots and who is building the solutions
(22:37) Astroscale: how one company is trying to clean up space junk commercially
(24:53) Who pays to clean up orbit when the market has no incentive to
(26:26) Is SpaceX a monopoly and does that matter for the space industry
(29:08) NASA Administrator: there is only one thing worse than a government monopoly
(33:04) Space governance, coordination and whether the tragedy of the commons can be solved in orbit

Spin qubits could scale quantum computing using the same semiconductor fabrication lines that print 50 billion transistors on an Nvidia chip. No new manufacturing paradigm required.

Brandon Severin, Oxford PhD and founder of Conductor Quantum, joins Mark and Jeremy to explain why that matters. 

You need hundreds of reliable qubits for meaningful quantum computation. The industry has dozens. Spin qubits, built from modified transistors, controlled by classical voltages, no lasers, no vacuum, may be the most practical path to millions.

This episode covers:

Why qubit fidelity and coherence time determine what a quantum computer can actually do
How AI automates the calibration problem that makes human-controlled quantum scaling impossible - "you can't have a billion Brandons"
Why trapped ions vs spin qubits is the wrong debate
What Google's quantum algorithm result actually proved, and why it matters
Why the physicists who understand semiconductor manufacturing may unlock use cases pure quantum researchers never reach
The two camps dividing the quantum industry: build one qubit at a time, or build for a million

Also: quantum startup culture vs the AI boom, Brandon's Y Combinator experience, and why scaling quantum looks more like building a rocket ship than climbing a ladder.

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Brandon Severin: https://www.conductorquantum.com/

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Timestamps

(00:00) Introduction: spin qubits and the quantum scaling problem
(03:47) Trapped ions vs spin qubits: fidelity, coherence, and tradeoffs
(06:14) What qubit fidelity means and why it determines scaling limits
(08:25) What is a spin qubit? Building from the transistor up
(11:06) Semiconductor fabrication as quantum computing's manufacturing advantage
(15:00) The quantum circus: superposition, measurement, Schrödinger's cat
(17:17) Shuttling qubits — moving electrons across a chip
(20:33) How AI automates quantum calibration (the control problem)
(25:00) Quantum scaling vs AI scaling: the GPU parallel
(29:08) Quantum startup culture and the AI generation gap
(32:59) Building for a million qubits — rocket ships vs ladders
(36:52) Why quantum is taking so long: talent, concentration, and meaning
(39:43) What seems impossible now that will be routine in 20 years

Quantum computing has been five years away for thirty-five years. Infleqtion CTO Pranav Gokhale makes the case that 2028 is different, because for the first time, logical qubits actually exist.

He explains what a logical qubit is using a Wi-Fi analogy: noisy physical qubits are like corrupted data packets; logical qubits are the clean, usable signal that comes out the other end. Humanity had zero logical qubits before 2023. Infleqtion now has twelve, with a public roadmap to thirty in 2026 and one hundred in 2028.

At one hundred logical qubits, material science and drug discovery become the first real quantum use cases - and the timeline stops being a prediction and starts being an engineering problem.

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Why does it cost NASA $4.2 billion per launch when SpaceX predicts Starship could do the same job for $10 million?

Mark and Jeremy work through Part 3 of Space to Grow by Matthew Weinzierl and Brendan Rosseau, the book the space industry is reading, and find two stories running in parallel: the wreckage of the space SPAC bubble, and NASA's uncomfortable reinvention in the commercial era.

This episode covers:
How SPACs turned space startups into crypto: Virgin Orbit went from a $3.7B valuation to bankruptcy in two years; Astra went public at $2.1B with zero rockets that had ever reached orbit
Why $100 invested in space startup stocks at IPO was worth $10 by early 2024
The stag hunt problem: why genuinely big things in space require coordination and trust that the industry hasn't built yet
NASA's Artemis programme explained, and why the South Pole of the Moon holds 100,000 Olympic swimming pools of frozen water that could become rocket fuel
The $4B SpaceX and $3.4B Blue Origin contracts that signal NASA is finally learning to share
Can NASA evolve from doing it to enabling it, before China gets there first?

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Chapters

(00:00) What is a SPAC? 
(01:30) Why space SPACs failed 
(03:20) Virgin Orbit & Astra: the worst examples 
(06:00) SPACs vs Crypto: same story? 
(08:30) The Stag Hunt: why space needs coordination 
(11:00) NASA Artemis explained 
(13:00) SLS vs Starship cost breakdown 
(17:00) SpaceX & Blue Origin lunar contracts 
(20:00) The Moon Race vs China 
(22:00) Can NASA survive the commercial space era?

Infleqtion put a quantum atomic clock inside a UK military submarine. Before that, they put quantum technology on the International Space Station.

They are building neutral atom quantum computers that operate at room temperature, atoms colder than outer space, controlled by lasers, no freezer required.

Mark and Jeremy sit down with Matt Kinsella, CEO of Infleqtion, to learn why neutral atoms are pulling ahead of every other quantum modality.

This episode covers:
Why GPS is becoming unreliable and how quantum clocks replace it with unspoofable, unjammable precision timing
How neutral atoms become the coldest place in the known universe while the surrounding system stays at room temperature
Why a quantum clock and a quantum computer are essentially the same technology at different levels of complexity
The CPU → GPU → QPU data centre stack: how drug discovery and battery design get split across classical and quantum compute
Why logical qubits - which humanity had never demonstrated before 2023 - change the quantum computing timeline
How Infleqtion's quantum memory software is already expanding GPU context windows today

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Timestamps:

(00:00) Trailer
(01:50) Why coordination matters: From internal strategy to GPS timing
(04:48) What is a quantum clock and how does it link to GPS?
(07:18) Nature's metronome: How atoms keep time with laser precision
(08:14) Room temperature quantum: Why neutral atoms don't need freezers
(12:38) The Rydberg state: Making atoms sensitive to the entire RF spectrum
(14:03) Quantum clock on a UK submarine
(17:06) Quantum in space: Voyager partnership and the International Space Station
(18:48) Hybrid quantum-classical workflows: How QPUs layer above GPUs
(23:18) Software layers: From laser control to developer applications
(25:32) Drug discovery example: GPU, CPU, QPU
(29:03) The bridge between classical and quantum: Memory architecture innovations
(31:54) How Quantum Clocks & Products Lead To Quantum Computers
(33:48) Nvidia
(35:42) Quality or Quantity of Qubits 
(38:00) Quantum mechanics and free will: Does wave collapse prove consciousness?
Love it.
Thanks. 

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⁠⁠Listen to every podcast⁠⁠

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Email: ⁠[email protected]⁠

--
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: why you can't copy-paste quantum data
(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?