Key Takeaways:
Bitcoin's network hash rate exceeds the combined power of the world's top 100 supercomputers by more than 600,000 times, according to Bittensor co-founder Ala Shaabana.
Bitcoin's network hash rate exceeds the combined power of the world's top 100 supercomputers by more than 600,000 times, Bittensor co-founder Ala Shaabana said Tuesday at the Proof of Talk summit in Paris.
"We all know that Bitcoin really dwarfs the top 100 supercomputers," Shaabana, co-founder of Bittensor and partner at Crucible Labs, said. "It's over 600,000 times the power of really what these supercomputers can do."
Shaabana argued that the same incentive architecture that turned Bitcoin into a computing force can be redirected toward artificial intelligence. Bittensor, a Layer 1 protocol built on the same codebase philosophy as Bitcoin — a hard cap of 21 million tokens, halvings hardcoded into predetermined blocks, no pre-mine and no venture capital — replaces Bitcoin's hash-puzzle mining with running and validating AI models. The network organizes compute across 128 specialized subnets, each defining its own goal, with miners competing for TAO token rewards by meeting it.
"The long-term bull case is no longer primarily technological," Shaabana said. "It is driven by debt, liquidity, and declining trust in traditional sovereign systems. Subnets really create markets. Intelligence really is no longer locked behind issues of organization; signals will define the truth, and performance is really rewarded."
How Bitcoin's Playbook Maps to AI
Shaabana's core argument rests on a simple premise: if coordination and code created the world's most powerful financial computing engine, the same blueprint can be applied to AI. By breaking a network into 128 individual problem-solving subnets, developers can source global hardware and intelligence without a central tech monopoly.
The mechanism depends entirely on incentive design. "Show me the subnet, and I'll tell you what the miners are optimizing for," Shaabana said, adapting a well-known market quote. If participants are rewarded for raw compute speed, they optimize for speed. If rewarded for data storage, they optimize for storage. By setting programmatic goals, open networks attract talent and computing power more efficiently than standard corporations, he argued.
Implications for Decentralized AI
The comparison places Bitcoin's proof-of-work network — often criticized for energy consumption — in a new light as the backbone of a distributed computing model that could challenge centralized AI infrastructure from companies such as OpenAI, Google and Microsoft. Bittensor's subnet structure allows anyone to contribute hardware or models to specific problem sets, with rewards distributed automatically on-chain.
Shaabana said the shift in computing infrastructure mirrors a broader change in how value is created. True computing power no longer belongs to isolated corporate data centers, he argued, but to open, global networks where performance is transparently rewarded.
This article is for informational purposes only and does not constitute investment advice.
