Ethereum’s next scaling leap may come from making everyone stop doing the same work
Cheaper proofs could widen verification while builders and provers still need the data to keep blocks and rollups moving. The post Ethereum’s next scaling leap may come from making everyone stop doing the same work appeared first on CryptoSlate.
Ethereum co-founder Vitalik Buterin says advances in cryptography could turn decentralization from a performance cost into a scaling advantage for the network.
In a Sept. 27 essay, Buterin described Ethereum's long-term destination as a “cryptographic world computer,” an architecture in which computation and data can increasingly be distributed across different participants while compact proofs allow others to cheaply verify that the work was performed correctly.
The shift would mark a departure from the traditional blockchain model in which every node downloads transactions and repeats much of the same computation. Instead, Ethereum could push more work across a wider network of specialized participants without requiring every validator to reproduce it, potentially allowing decentralization itself to contribute to performance.
“Perhaps the most important shift” is that decentralization is moving beyond being a burden accepted for safety and robustness and can, in limited cases, become a performance strength, Buterin wrote. Distributed networks can store larger quantities of data and run more computation in parallel, including work around the transaction mempool.
That revives one of Ethereum's earliest ambitions. Developers in the mid-2010s considered distributing different pieces of computation across participants much as centralized systems divide workloads between servers. The obstacle was verification: dividing the work created the additional problem of establishing that every participant had performed its portion correctly.
Modern cryptographic proofs increasingly provide that missing layer, Buterin said, while their computational overhead continues to decline.
The change is part of a broader overhaul that Buterin argues will make Ethereum around 2030 qualitatively different from the blockchain systems that emerged with Bitcoin.
Ethereum's future verification model would rely increasingly on data sampling and succinct cryptographic proofs rather than requiring every validator to download and independently execute everything. Consensus is also moving toward a more optimized proof-of-stake design, while block construction is being divided among multiple participants instead of being controlled by a single producer.
Zero-knowledge technology is already central to that direction. Ethereum's proposed L1 zkEVM model would allow a specialized prover to execute a block and generate a proof of correct execution, which other nodes could verify much more cheaply than re-executing every transaction themselves. The technology remains under active research and has not been integrated into production Ethereum clients.
The result, if the roadmap works as intended, would be a network where doing work and checking work become increasingly separate functions.
Buterin argues that separation could allow Ethereum to retain the security benefits of broad verification while tapping distributed infrastructure for more computation, storage and potentially privacy. Infrastructure surrounding Ethereum could also compete more aggressively on latency even if the base chain itself never approaches the response times of centralized servers.
He described the eventual system as a hybrid combining traditional blockchain properties with cryptographic verification, privacy and decentralized components operating away from the base chain.
The transition could also alter the economics of building applications on Ethereum.
On a conventional blockchain, developers largely think about the amount of data or computation an application consumes. Buterin expects the structure of that computation to become increasingly important as Ethereum attempts to parallelize work across different participants.
Applications that package large amounts of interdependent computation into one serial transaction could become comparatively expensive, while workloads separated into well-defined components that can be parallelized, aggregated or pruned could become cheaper.