Ripple Exec Clears The Air On Blocked XRP Transactions – When Does It Happen?

bitcoinistОпубліковано о 2026-03-01Востаннє оновлено о 2026-03-01

Анотація

Former Ripple CTO David Schwartz clarified that Ripple cannot block transactions or freeze wallets on the XRP Ledger (XRPL). He explained that valid transactions can only be prevented if users collectively change the network’s validity rules. Schwartz also refuted claims that the XRPL is centralized due to Ripple’s Unique Node List, stating that such assertions are "objectively nonsensical." He emphasized that the XRPL was intentionally designed to be decentralized, ensuring that no single entity, including Ripple, can control or censor transactions. Schwartz noted that even if Ripple had such power, using it would destroy trust in the network. He also addressed comparisons to Bitcoin, highlighting key differences in how consensus is achieved between the two networks.

Former Ripple Chief Technology Officer (CTO) David Schwartz has addressed speculation that the crypto firm can block transactions on the XRP Ledger (XRPL). He explained the only way this could happen amid claims that the network is centralized.

Ripple CTO Emeritus Explains How An XRP Transaction Can Be Blocked

In an X post, the former Ripple CTO said that there is no way to prevent valid transactions on the XRP Ledger unless users agree to change the validity rules to make them invalid. Schwartz made this statement in response to whether Ripple or he, as one of the original developers, can freeze a wallet and prevent a transaction.

Meanwhile, in response to who can unlock and lock escrows, the former Ripple CTO said that anyone who wants to escrow tokens can lock them in escrow. Once an escrow expires, anyone can unlock it. Schwartz also addressed claims that the XRPL Ledger was centralized because Ripple has a “Unique Node List,” which effectively makes the validators permissioned.

The former Ripple CTO described the claims that the crypto firm could have absolute power and control of the chain as “objectively nonsensical.” He noted that this is similar to claiming that someone with a majority of mining power can create a billion BTC. Justin Bons, Cyber Capital’s founder, who made the claim, explained that he meant Ripple could double-spend or censor the network, similar to someone holding a majority of mining power on the Bitcoin network.

XRP is currently trading at $1.29. Chart: TradingView

Schwartz rebutted this claim, stating that the XRP Ledger and Bitcoin don’t work the same. He noted that on the XRPL, one can count the number of validators that agree with one’s node. The former Ripple CTO added that a node will not agree to double-spend or censor unless there is a particular reason why the validator wants to do so.

XRPL ‘Carefully’ Designed To Be Decentralized

The former Ripple CTO reiterated that they carefully and intentionally designed the XRP Ledger so that they could not control it. He explained that they did so, given the regulatory environment and practical realities of being a company and having investors. As such, there was no guarantee that they would always have control over their own actions.

Schwartz gave an example of how Ripple must honor U.S. court orders, as it cannot refuse such requests. As such, they decided from the onset that they did not want control over the XRP Ledger and that it would be to their benefit not to have control. He also mentioned that it would not make sense if Ripple ever censored transactions or double-spent, even if they had the power to do so, because if they ever did, it would destroy trust in the XRPL.

Featured image from GitHub, chart from TradingView

Пов'язані питання

QWhat did former Ripple CTO David Schwartz clarify about the ability to block transactions on the XRP Ledger?

ADavid Schwartz clarified that there is no way to prevent valid transactions on the XRP Ledger unless users collectively agree to change the validity rules to make them invalid.

QAccording to Schwartz, who has the ability to lock and unlock escrows on the XRP Ledger?

AAnyone who wants to escrow tokens can lock them in escrow, and once an escrow expires, anyone can unlock it.

QHow did Schwartz respond to claims that the XRP Ledger is centralized due to Ripple's 'Unique Node List'?

ASchwartz described these claims as 'objectively nonsensical,' explaining that the XRP Ledger was carefully designed to be decentralized and that Ripple cannot control it.

QWhat key difference did Schwartz highlight between the XRP Ledger and Bitcoin regarding network control?

ASchwartz stated that the XRP Ledger and Bitcoin don't work the same way, noting that on XRPL, one can count validator agreement, and validators won't agree to double-spend or censor without a specific reason.

QWhy did Schwartz mention that it would not make sense for Ripple to censor transactions or double-spend, even if they had the power?

AHe explained that doing so would destroy trust in the XRP Ledger, which is against Ripple's interests, and they designed the ledger specifically to avoid having such control.

Пов'язані матеріали

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit14 год тому

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit14 год тому

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit15 год тому

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit15 год тому

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit16 год тому

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit16 год тому

Торгівля

Спот
Ф'ючерси
活动图片