Episode 22 of The Quantum Computing Podcast dives into fault-tolerant quantum computing, the architecture shift from noisy qubits to logical qubits that can actually run useful algorithms. Lucas and Luna explain the surface code, why Google and IBM are racing to demonstrate 'below threshold' error rates by 2027, and how Microsoft's topological qubit bet could leapfrog the whole approach. They also unpack the cost: millions of physical qubits for every logical qubit, and the supply chain bottleneck in cryogenic controllers. A concrete look at the single hardest engineering problem in quantum computing today.

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