
The TAO Pod EP 14: Quantum Biology Meets Bittensor: Engineering Life & AI Compute
33 snips
Feb 24, 2026 They dive into quantum biology and how room-temperature quantum effects could reshape life engineering. They explore compute efficiency limits for AI and why new substrates may be needed. BitTensor’s model of turning tasks into currency and how subnets monetize R&D get explained. They discuss product progress from Ridges, confidential compute advances, and how decentralization and market dynamics affect adoption.
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Room Temperature Quantum Effects In Biology
- Quantum biology shows room-temperature quantum effects in proteins and microtubules, implying biology itself performs computation.
- Joseph Jacks cites FELs and experiments observing phonon-photon transforms and microtubule computation across eukaryotes.
Compute Efficiency Is AI's Core Bottleneck
- Compute efficiency is the single biggest bottleneck for scaling AI; demand far outstrips chip and optimization improvements.
- Jacks argues current semiconductors won't scale 10–500x and biology-inspired substrates or new algorithms are needed.
Use Subnets To Monetize Fundamental R&D
- Use BitTensor subnets to incentivize hard R&D that central companies won't fund directly.
- Jacks explains Nova miners predict protein morphologies, turning fundamental discovery into monetizable outputs for wet-lab testing.



