Nvidia Join The Quantum Computing Race

What this episode covers

Nvidia is treating quantum computing as the next stage of accelerated computing, not as a separate machine sitting apart from AI supercomputers. Sam Stanwyck from Nvidia and Pranav Gokhale from Infleqtion explain how NVQLink connects QPUs and GPUs with low-latency, high-bandwidth communication, allowing quantum computers, GPU supercomputers, CPUs, CUDA-Q, and AI software to work inside the same computational workflow. The conversation moves from logical qubits, quantum error correction, material science, battery design, and Hamiltonian simulation to quantum sensors in space, NASA, gravity mapping, edge GPUs, and why the first useful quantum systems may arrive as hybrid quantum-classical supercomputers.--⁠⁠Listen to every podcast⁠⁠Follow us on⁠ ⁠Instagram⁠⁠Follow us on⁠ ⁠X⁠⁠Follow Mark on⁠ ⁠LinkedIn⁠⁠Follow Jeremy on⁠ ⁠LinkedIn⁠⁠Read our⁠ ⁠Substack⁠⁠Email: ⁠[email protected]⁠--Chapters(00:00) Trailer(01:20) Why Nvidia(02:52) NVQ-Link(09:29) Quantum computer vs the GPU(12:33) AI helping quantum(16:56) Building a space elevator (20:09) The quantum algorithm zoo (22:04) From noisy qubits to logical qubits (24:00) How much energy does a quantum computer use? (27:05) The no-cloning theorem(27:20) The biggest unanswered question in quantum computing(30:47) A $20M NASA program (33:32) What do we want humans to be?

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Frequently Asked Questions

How long is this episode of Thinking On Paper?

This episode is 37 minutes long.

When was this Thinking On Paper episode published?

This episode was published on March 8, 2026.

What is this episode about?

Nvidia is treating quantum computing as the next stage of accelerated computing, not as a separate machine sitting apart from AI supercomputers. Sam Stanwyck from Nvidia and Pranav Gokhale from Infleqtion explain how NVQLink connects QPUs and GPUs...

Can I download this Thinking On Paper episode?

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