Grant Cardone Bets on Bittensor as the Next Gen. Crypto Asset

Grant Cardone officially entered Bittensor with strategic investments, sitting down alongside Brian Dixon to break down the thesis behind why the real estate mogul is now allocating capital to decentralized AI infrastructure. The central pitch is that Bitcoin is decentralized money and Bittensor is decentralized intelligence, running the same tokenomics that made Bitcoin a generational asset.

The conversation covered how closed-source models including Perplexity, ChatGPT, and Claude are already licensing Bittensor intelligence for a growing share of their queries, and how the network’s proof-of-work architecture with a 21 million supply cap creates the same scarcity mechanics on the intelligence layer. The signal from Cardone’s entry is that mainstream capital is starting to treat Bittensor as a next-generation asset class rather than a crypto experiment.

From Decentralized Money to Decentralized Intelligence

The comparison Cardone drew leans on a familiar analogy from software history, extended into the AI era.

1. Bitcoin is decentralized money: Bittensor is decentralized intelligence.

2. The software parallel: Closed-source software (Instagram, Facebook) controls the codebase entirely. Open-source software lets anyone read, contribute, and build.

3. The same split is arriving in AI: OpenAI, Anthropic, Perplexity, and Grok run closed models. Bittensor sits on the open-source side, letting anyone contribute intelligence to the network.

4. Subnets as app-businesses: Each of the 128+ subnets functions like a specialized business application, with distinct verticals covering inference, medical intelligence, financial intelligence, and beyond.

The point is that closed-source AI still depends on open-source contributions underneath, the same way closed-source software companies quietly rely on open-source libraries across their stack.

Closed AI Is Already Licensing Bittensor Intelligence

The insight that most caught Cardone’s attention is that this dependency is already happening in the AI market today, just below the surface.

1. A small percentage of Perplexity, ChatGPT, and Claude queries are being served by Bittensor intelligence. The share is measurable today and growing.

2. The licensing is not disclosed to end users. Users see the closed-source model’s answer without knowing where part of it came from.

3. The share will grow significantly over time. As subnets become more sophisticated across their specialized verticals, more of the frontier’s query load will route through Bittensor infrastructure.

This is the value accrual argument. The closed-source AI incumbents are becoming customers of the decentralized intelligence layer, and that customer relationship generates demand for TAO rather than displacing it.

Bitcoin Tokenomics on the Intelligence Layer

The final piece of the pitch is that Bittensor runs the exact monetary architecture that made Bitcoin a generational asset.

How to Read a Subnet’s Tokenomics Page on Taostats (For People Who Hate Spreadsheets)

1. Fixed 21 million supply: Same as Bitcoin, capped at the protocol level.

2. Proof-of-work architecture: Compute contribution is required to earn rewards, mirroring Bitcoin’s mining structure.

3. Predictable halving schedule: Daily issuance halves on a fixed cadence, creating the same supply shock dynamics that have driven Bitcoin’s cycles.

The design produces long-term scarcity on a network whose product is intelligence rather than a store of value, which is what makes the asset novel.

Bitcoin’s monetary architecture applied to a productive commodity is a different setup than either Bitcoin or any prior crypto asset has offered.

From Real Estate to the Intelligence Layer

Cardone built his empire in real estate and business scaling, which makes the pivot into decentralized AI infrastructure the more interesting signal in the announcement. When operators of that scale start allocating to Bittensor, the perception around the ecosystem shifts from an experimental crypto asset to an early position in a next-generation asset class.

The intelligence trade is not over. It has moved to a layer most public-market investors have not looked at yet, and the mainstream validation is only just beginning to arrive. For a network already supplying quiet inference load to the largest closed-source AI models, Cardone’s entry is one of the sharper signals that the wave is building.