At the Proof of Talk summit in Paris, experts highlighted a major shift underway in global computational infrastructure. Ala Shaabana, co-founder of Bittensor and Crucible Labs, argued that c
At the Proof of Talk summit in Paris, experts highlighted a major shift underway in global computational infrastructure. Ala Shaabana, co-founder of Bittensor and Crucible Labs, argued that computing power is no longer confined to closed, enterprise data centers. Instead, it is increasingly aggregated across open, decentralized, and global networks.
Explaining the enormous scale achieved by distributed systems, Shaabana compared the Bitcoin network’s processing power to that of traditional institutional infrastructures. Bitcoin’s hash rate currently exceeds the combined computing capability of the world’s 100 most powerful supercomputers by over 600,000 times. He emphasized this staggering comparison is unique to Bitcoin and reflects its unparalleled scale in decentralized computation.
According to Shaabana, Bitcoin has far surpassed the top 100 supercomputers, with its hash rate over 600,000 times higher than the aggregate computing power of those systems.
This analysis bolsters the view that decentralized networks are not just alternative financial systems, but represent a new paradigm for massive-scale computational organization. During his address, Shaabana detailed how open networks, through code and incentive mechanisms, can pool vast hardware resources that previously required centralized coordination.
Bittensor, as described by Shaabana, is structurally similar to Bitcoin as a Layer 1 protocol. The network enforces a fixed supply of 21 million tokens, features predetermined halving events embedded within its blocks, has no pre-mining, and operates without venture capital funding. However, unlike Bitcoin, Bittensor does not rely on hash-based mining. Instead, it incentivizes the training and validation of artificial intelligence models.
Mini glossary: Bittensor is a blockchain network that aims to organize the production and validation of artificial intelligence models through economic incentives. In this system, a subnet refers to a specialized subnetwork within the ecosystem, each focused on a particular task and operating with its own reward structure.
The Bittensor ecosystem comprises 128 expert subnetworks. Each subnet determines its mission, while miners compete for TAO token rewards by maximizing their performance within these targets. The network’s reward system is engineered to determine which forms of intelligence and output are advanced, aligning incentives with network goals.
For Shaabana, the heart of this system lies not in central coordination but in incentive design. By examining any given subnet, it’s easy to see what outcome miners are optimizing—whether the reward is for computational speed or data storage, the dominant output follows the structure of the incentive.
Shaabana explained that recent long-term bullish scenarios are driven less by technology alone, and more by a combination of debt, liquidity concerns, and waning trust in traditional sovereign systems. He noted that subnets are fostering new market creation, with performance rewarded directly by network participants.
In this light, Shaabana argued that Bitcoin’s code-driven coordination mechanism, which turned it into a global computational giant, can be extended to the field of artificial intelligence. He asserted developers can now access worldwide computing resources and expertise, split across 128 subnets, without relying on a single dominant tech platform.
He also contended that when open networks assign clear, programmatic goals, they are often more effective than traditional corporate structures at attracting both talent and computational resources. In such models, it is not the technical architecture, but rather the economic incentives guiding participants toward specific outcomes, that determines overall system effectiveness.
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