2026 9 episodes
- Julien Camirand Lemyre (Nord Quantique): One Cavity, One Error-Corrected Qubit
- Sebastian Hassinger (The New Quantum Era): why neutral atoms lead the qubit race for now
- Michaela Eichinger (Quantum Machines): Why classical compute and HPC integration define useful quantum
- Gil Kalai (Hebrew University): Why correlated noise may block quantum error correction for good
- Bob Sorensen (Hyperion Research): Solve real bottlenecks first, then evaluate quantum
- Christian Weedbrook (Xanadu): Scaling photonic quantum computers with optical networking
- Scott Aaronson (UT Austin): Why quantum skepticism keeps losing ground
- Vishal Chatrath (QuantrolOx): Turning weeklong qubit characterization into a 25-minute automated run
- Jonathan Reiner (Quantum Machines): Why Control Electronics Can’t Bottleneck Error Correction
2025 9 episodes
- Kike Miralles (Intel Capital): Why logical qubits, not qubit counts, now matter most
- Bert de Jong (Berkeley Lab QSA): Why DOE science needs far less precision than cryptography
- Sebastian Weidt (Universal Quantum): Why scaling trapped ions beats rushing NISQ to market
- Tal David (Quantum Art): Scaling trapped ions with multi-qubit gates instead of shuttling
- Scott Genin (OTI Lumionics): Classical emulation of 80 qubits still beats quantum chemistry claims
- Michelle Simmons (SQC): Atom-precision qubits hit 98.87% fidelity, no error correction
- Maud Vinet (Quobly): 100,000 Qubits Per Wafer, But Control Is The Hard Part
- David Rivas (Rigetti): Why vertical integration and chiplets scale superconducting qubits
- Matthijs Rijlaarsdam (QuantWare): Why fan-out, not qubit count, is the real scaling wall
2024 10 episodes
- Yuval Boger (QuEra): Why Google bet on neutral atoms for logical qubits
- Rob Schoelkopf & Ray Smets (Quantum Circuits): Catching qubit errors at the hardware level
- Renaud Béchade (Anzaetek): Why hospitals with too little data need quantum machine learning
- Mariia Mykhailova (Microsoft): Bridging the gap from qubit basics to real quantum algorithms
- Shengtao Wang & Jonathan Wurtz (QuEra): Why neutral atom error correction could make quantum chemistry useful
- Mike Biercuk & Natasha Sachdeva (Q-CTRL): Error tools make today’s noisy hardware solve real problems
- Catherine Vollgraff Heidweiller (Google Quantum AI): Building a product roadmap from quantum supremacy
- Thomas Ehmer (Merck KGaA): Why a pharma company builds its own quantum roadmap
- Chris Ballance (Oxford Ionics): Trapped Ions on a Classical Chip, No Quantum Fab Needed
- Nathan Shammah (Unitary Fund): Open source as quantum’s missing infrastructure
2023 8 episodes
- Earl Campbell (Riverlane): Why Logical Qubit Counts Hinge on Error Rates
- Misha Lukin, Dolev Bluvstein & Harry Zhou (Harvard/QuEra): 48 logical qubits from moving atoms
- Ish Dhand (QC Design): Selling fault-tolerant blueprints instead of building qubits
- Tommaso Demarie (Entropica Labs): Building the middleware layer for fault-tolerant quantum computing
- Stephanie Simmons (Photonic): Why photonic interconnects, not more qubits, unlock fault tolerance
- Oliver Dial (IBM): Why scale, quality, and speed matter more than qubit count
- Michael Biercuk (Q-Ctrl): Quantum control as the missing layer for stable hardware
- Andrew Dzurak (Diraq): Why Silicon Spin Qubits Can Ride Existing Chip Fabs
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