[Long English Thread] Scroll Co-founder: The Inevitable Path of ZK

Chainfeeds Guide:

Forty years ago, zero-knowledge proofs (ZK) were just an overlooked idea, a mathematical curiosity. Twenty years ago, they became million-dollar bank experiments. Today, zero-knowledge proofs are no longer just a promise.

Source:

Author:

Sandy Peng

Opinion:

Sandy Peng: Since the original paper in 1985, zero-knowledge proofs have undergone decades of academic exploration and industrial skepticism: In the 1980s-1990s, scholars extended interactive proofs into zero-knowledge variants and explored non-interactive implementations (such as the Fiat-Shamir heuristic); in the 2000s, enterprises and cryptography research groups began limited experiments, but actual deployments remained rare, with the technology mainly confined to niche scenarios such as identity or privacy systems and specific hardware. After 2020, with the rise of blockchain and roll-up architectures, the cost, latency, and engineering complexity of ZK systems dropped significantly, but the average cost per proof was still as high as about $80 (as of December 2023). Today, the cost of transactions on the Scroll chain is less than $0.01, representing an 8,000-fold reduction. Technologies once considered "impossible" are now cheaper than many Optimism-based rollups. Zero-knowledge proofs are not just scalability tools; their core capability also includes privacy management, i.e., selectively revealing or hiding information, providing users and institutions with financial security and dignity—something transparent blockchains cannot achieve. The popularization of zero-knowledge technology is similar to the development of AI. In AI, many companies focus on model building—OpenAI, Anthropic, Google, etc., train systems from the ground up, mastering optimization layers and data; while other companies develop applications based on these models, packaging existing intelligence into apps, chat interfaces, or productivity tools. Both approaches create value but also generate different power dynamics: controlling the foundational model means mastering core capabilities, while developing only on top of them means relying on someone else’s roadmap—essentially the difference between owning land and renting land. For example, Apple integrates OpenAI models into Apple Intelligence instead of building its own models. Even model providers realize that simply building better models is not enough to secure market advantage. When user experience is provided by upper-layer applications, foundational model providers may become invisible infrastructure—powerful but easily replaceable. Realizing this, OpenAI launched its own browser, voice interface, and video generation tool Sora, both showcasing model capabilities and controlling user relationships. This trend is accelerating its impact on the crypto space: some teams focus on infrastructure, while others develop user applications. Both are equally important: infrastructure without users is an empty shell, while applications lacking underlying control cannot scale in the long term. Based on this, Scroll is evolving from a "single chain" into an ecosystem encompassing end-user products, enhancing user experience with a mobile-first design and achieving coordinated development of infrastructure and applications. Scroll’s infrastructure has achieved breakthroughs in cost and privacy. Through the latest Feynman upgrade, its transaction costs are lower than some OP-rollups; Cloak provides an auditable privacy layer for the chain; Ceno introduces next-generation zero-knowledge provers using the GKR sumcheck protocol. On the user side, @usxcapital launched the first zero-knowledge-driven neodollar—a stablecoin that is both private and spendable, with yields of about 10-15%; Garden offers encrypted savings applications; @ether_fi Cash has completed 1.2 million transactions, with total spending exceeding $100 millions; RWA projects like @ProjectMochaHQ tokenize Kenyan coffee trees, allowing anyone to invest in agriculture; @ChatterPay enables transfers via WhatsApp; @SynthOS__ uses AI to recommend personalized yield portfolios. The development of zero-knowledge proofs has spanned 40 years, from mathematical curiosity to bank experiments, and now to an inevitable trend. Early on, costs were high and deployment was difficult, but today zero-knowledge proof systems are not only efficient and usable, but also ensure selective data disclosure, enabling possibilities for finance, governance, and institutional experiments. Transparent blockchains can support speculation, ordinary payments, and some institutional applications, but lack of privacy makes them unsuitable for sensitive scenarios. Strong privacy blockchains can achieve almost all functions in finance, voting, governance experiments, etc., providing a solid foundation for digital economies and institutional experimentation. Zero-knowledge technology has evolved from theoretical experiments to an irreversible core of infrastructure.