Moonshots with Peter Diamandis

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Urgent Update- AI Sputnik Moment: Kimi K3 Released w/ Emad Mostaque | Ep. 272

Explore episode Jul 19, 2026

Where this was said

Sub-1-Bit Quantization and the Future of Computing Substrates

At 1:11:50 · chapter starts 1:07:40

Alex Wissner-Gross takes the quantization story to its logical extreme: Samsung's recently published NanoQuant model already achieves sub-1-effective-bit-per-weight through sparsity, quantization, and low-rank factorization. His extrapolation puts sub-1-bit quantization going mainstream within the next year. Emad Mostaque puts a specific marker down: 0.78 bits per weight is his predicted floor, at which point models could be physically etched into silicon — the gate is just absent or present, no power required to store the weight. Dave Blundin adds that if the computation is just multiply-by-1, multiply-by-0, or multiply-by-minus-1, an entirely new class of computing substrates becomes viable — photonic chips, crystals, biological systems, anything that can represent three states. He projects 100 to 10,000x improvement in raw compute within 3 years through quantization and new computing methods, multiplicative with algorithmic improvements. Dave Blundin notes this vaulted to his favorite piece of media ever recorded on the pod.

Technology
Sub-1-Bit Quantization: There's Plenty More Room at the Bottom

Urgent Update- AI Sputnik Moment: Kimi K3 Released w/ Emad … · Jul 19, 2026 Technology

Alex Wissner-Gross reports that Samsung's NanoQuant model has already broken the 1-effective-bit-per-weight barrier using sparsity, quantization, and low-rank factorization. His extrapolation: sub-1-bit quantization goes mainstream within the next year. The endpoint, per Emad Mostaque, is 0.78 bits per weight — and at that point, models could be literally etched into silicon.

2m 32s

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