Ala Shaabana, co-founder of Bittensor and partner at Crucible Labs, argued at the Proof of Talk summit in Paris that Bitcoin’s computational power vastly exceeds centralized infrastructure, and that decentralized networks using similar incentive models can displace traditional tech monopolies.
“We all know that Bitcoin really dwarfs the top 100 supercomputers. Does anybody know, in comparison, what the hash rate is? It’s over 600,000 times the power of really what these supercomputers can do,” Shaabana said.
Shaabana contends that decentralized networks are becoming the backbone of global computing power, replacing traditional corporate data centers. The argument hinges on incentive design. Bittensor, a Layer 1 protocol, replaces Bitcoin’s hash-puzzle mining with running and validating artificial intelligence. Miners compete for TAO token rewards by meeting subnet goals across 128 specialized problem-solving networks.
Each subnet defines its own objective. The network’s intelligence is shaped by what it chooses to reward. Shaabana framed this as a structural advantage over centralized systems. “Show me the subnet, and I’ll tell you what the miners are optimizing for,” he said.
Bittensor operates with a hard cap of 21 million tokens, halvings hardcoded into predetermined blocks, no pre-mine, and no venture capital funding. This architecture mirrors Bitcoin’s scarcity model while applying it to distributed AI validation.
Shaabana’s broader thesis challenges the assumption that centralized tech companies will retain control of AI infrastructure. “The long-term bull case is no longer primarily technological. 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,” he said.
The claim that Bitcoin’s hash rate exceeds supercomputer power by 600,000x is a quantitative assertion about energy expenditure and computational throughput. Shaabana uses it as a proof of concept: if decentralized incentive structures can coordinate that much power for proof-of-work security, the same principle can coordinate AI labor across distributed nodes.
Bittensor’s model distributes intelligence across subnets rather than concentrating it in a single corporate entity. Each subnet operator decides what problem to solve and what performance metrics matter. Miners then allocate compute to whichever subnet offers the best reward signal.
Shaabana did not provide independent verification of the 600,000x figure or detail the methodology behind the comparison. The Proof of Talk summit remarks represent his interpretation of how decentralized compute can scale beyond centralized alternatives.
