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.

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.

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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?