When Nic Lane, a computer scientist at the University of Cambridge and co-founder of Flower AI, pointed out that 'distributed methods are expected to break the scale limits of Collective-1', a fundamental revolution in the AI field is quietly brewing. This is not just a simple stack of technologies, but a deep restructuring of the 'power structure of AI'. At the forefront of this trend is Origins, a public blockchain dedicated to building a callable, scalable, and inclusive blockchain foundation.
The Hidden Threshold of AI Large Models: The Matthew Effect of Concentrated Resources
Current AI model training almost entirely relies on massive amounts of data and supercomputing power concentrated in high-end data centers. This model, while efficient, has resulted in a significant Matthew effect: only large enterprises or nations with substantial financial resources and access to chip resources and bandwidth infrastructure can train commercially competitive models. This is the status quo that Flower AI aims to change—breaking the 'AI oligopoly' with distributed methods.
As Lane said, 'Distributed solutions can scale computing power more elegantly.' This concept naturally aligns with the technical route of the Origins public blockchain. Origins is not just a public blockchain born for AI; it is a global public infrastructure aimed at the future intelligent economy, designed from the ground up to serve as a technology platform for integrating distributed resources.
Multimodal and Edge Intelligence: Origins Aligns with Flower AI's Goals
Flower AI is currently incorporating images and audio into its training system, moving towards multimodal models. Such models have extremely high requirements for real-time performance, geographic distribution, and scene adaptation—challenges that centralized architectures struggle to meet.
The on-chain modular mechanism and composable smart contract architecture of Origins support on-demand invocation, deployment, and sharing of model components. It allows developers to package different modality model components into 'smart services' and deploy them at edge nodes close to data sources, achieving efficient inference while ensuring privacy, greatly expanding the boundaries of multimodal AI applications.
At the same time, Origins is constructing a stablecoin USD1 and a multi-asset incentive pool to establish on-chain payment and revenue mechanisms for AI model development, training, and invocation, making model training not just a research or engineering activity, but a continuously profitable way to participate in the ecosystem.
AI Power Restructuring: Origins and New Paradigm Resonance
As Helen Toner stated, 'The Flower AI solution has potentially significant implications for AI competition and governance.' This is not just a change in technical pathways; it is the beginning of the reconstruction of global AI discourse power. The mission of Origins is to build the foundation that supports this new paradigm—a blockchain platform that allows 'anyone, anywhere' to participate in the construction of an intelligent society.
In the future, AI will no longer belong to a few, but will become a productivity tool shared by all. Origins not only provides technology but also shapes a new order: AI will no longer operate around capital concentration but will grow based on open network collaboration. It is this combination of decentralization and usability that makes Origins stand out among the many AI public blockchains today.
Conclusion:
As global AI enters a competition for models with hundreds of billions of parameters and a new stage of multimodal cognitive evolution, a public blockchain that truly supports the operation of a distributed intelligent economy becomes unprecedentedly important. Origins is not a public blockchain that follows the narrative, but a pioneer in defining a new standard of 'AI for everyone'. Between centralized behemoths and global developers, Origins is building the bridge to the future.
Usability is the only truth for AI public blockchains; universal accessibility is the future direction of AI.
