SEDULity: A Proof-of-Learning Framework for Distributed and Secure Blockchains with Efficient Useful Work
arXiv:2512.13666v2 Announce Type: replace-cross Abstract: The security and decentralization of Proof-of-Work (PoW) have been well-tested in existing blockchain systems. However, its tremendous energy waste has raised concerns about sustainability. Proof-of-Useful-Work (PoUW) aims to redirect the meaningless computation to meaningful tasks such as solving machine learning (ML) problems, giving rise to the branch of Proof-of-Learning (PoL). While previous studies have proposed various PoLs, they all, to some degree, suffer from security, decentralization, or efficiency issues. In this paper, we
The increasing energy consumption of traditional Proof-of-Work blockchains and the rapid advancements in AI/ML research are driving the development of more sustainable and 'useful' consensus mechanisms like Proof-of-Learning (PoL).
This paper addresses a critical challenge in blockchain sustainability by proposing a more secure and efficient Proof-of-Learning framework, potentially making blockchain technology more palatable for widespread adoption and addressing environmental concerns.
The proposed SEDULity framework offers a proof-of-learning mechanism that aims to resolve previous security, decentralization, and efficiency issues, shifting blockchain validation towards beneficial computational tasks.
- · Blockchain developers
- · AI/ML researchers
- · Crypto investors (long-term)
- · Environmental advocates
- · Traditional Proof-of-Work blockchain operators
- · Energy-intensive mining hardware manufacturers (eventually)
The adoption of Proof-of-Learning could drastically reduce the energy footprint of blockchain networks.
This shift may accelerate the integration of AI/ML tasks directly into blockchain consensus, creating self-sustaining AI research ecosystems.
Nations or entities with strong AI research capabilities could gain a competitive edge in securing future blockchain networks leveraging PoL.
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