Aug 17, 2026 · 1h 25m
Bittensor co-founder Jacob Steeves outlines the future of decentralized artificial intelligence
Bittensor creator Const on Affine, dTAO, "mining reasoning," and more | E2326
This episode provides a deep dive into the mechanics and economic incentives of Bittensor, highlighting how blockchain technology can be used to decentralize artificial intelligence development.
- 1Bittensor uses a competitive subnet model where developers compete for TAO token emissions based on model performance.
- 2The introduction of Dynamic TAO aims to refine the protocol economics and better incentivize high-performing machine learning models.
- 3Operating a permissionless network requires navigating adversarial threats, smart contract risks, and early-stage project failures.
The brief
Bittensor co-founder Jacob Steeves joins the show to explain how the protocol is building a decentralized, peer-to-peer network for artificial intelligence, positioning it as a competitive alternative to centralized tech giants.
By utilizing the TAO token economy, which mirrors Bitcoin with a 21 million supply cap, Bittensor incentivizes developers and validators to build and run specialized machine learning subnets that compete for token emissions.
The conversation addresses the harsh realities of a permissionless ecosystem, including security threats, bad actors, and the controversy surrounding the Templar subnet failure and subsequent rug pulls.
Despite early-stage startup failures, the network is attracting elite talent, including former Google Brain researchers, and launching subnets like Affine to focus on decentralized model training and reasoning.
Featuring
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