解读蓝盒子团队的BTC L2项目Merlin Chain

Odaily星球日报Publicado em 2024-01-30Última atualização em 2024-01-30

Resumo

Merlin Chain主网预计将于2024年2月上线。

BRC-420 协议生态项目在前段时间的整体行情回调中逆势上涨。

其中,蓝盒子(BRC 420)的价格一度从 0.15 U 飙升至 26, 000 U,市值达到 1 万 BTC,紧随 BAYC 和 CryptoPunks 之后。截至目前,蓝盒子在 Ordinals 范围内的 10 k 合集中单价仍然位居榜首。

解读蓝盒子团队的BTC L2项目Merlin Chain

解读蓝盒子团队的BTC L2项目Merlin Chain

(图源:Twitter @zad1130

蓝盒子的背后是 Bitmap Tech 团队,除了 BRC-420 协议,他们还推出了 Bitmap.Game(Bitmap 元宇宙)和 Recursiverse(基于递归协议的产品矩阵)。Bitmap 的市值最近从 300 万美元飙升至最高 2.9 亿美元,持币地址达到 3 万+,与蓝盒子一样,成为 Ordinals 生态备受关注的项目之一。

Bitmap Tech 团队在本周推出了比特币二层解决方案 Merlin Chain 的测试网,并在采访中透露其主网也将于 2024 年 2 月上线。本文旨在通过梳理 Merlin Chain 的公开信息,还原其愿景和解决路径。

旨在成为比特币二层网络的领军者

比特币一层网络的交易量在 Ordinals 生态的崛起下迅猛增长,然而设计时未充分考虑数据密集型交易,导致比特币网络拥堵不堪。为解决这一问题,近期涌现了众多比特币扩容方案,从需要自我保证安全的侧链到 DA 基于比特币一层网络的 Rollup,讨论纷纷。

解读蓝盒子团队的BTC L2项目Merlin Chain

(比特币网络日交易费,图源 token terminal)

在这众多方案中,以 EVM 侧链结合跨链桥的解决方案成为了立即可实施的方案,并在短期内成为比特币二层网络的标配。Bitmap Tech 团队深耕比特币生态多年,迅速投身到二层网络的开发中,推出了 Merlin Chain。

值得注意的是,改善一层网络的拥堵和降低交易手续费只是 Merlin Chain 要解决的问题之一。该团队正着眼于“比特币网络中新增用户数极少”这一更为深刻、复杂的问题。

解读蓝盒子团队的BTC L2项目Merlin Chain

(比特币网络日活跃地址数,图源 token terminal)

Merlin Chain 的目标不仅仅是改善比特币一层的交易环境,更是在二层引入更多原生的应用。通过在二层实现对一层资产、协议和用户生态的赋能,比如基于 Bitmap 构建用户可轻松进入的元宇宙、基于 BRC-420 构建 DeFi 协议以最大化释放其图币二象性,来放大比特币生态整体的资产潜力。

ZK-Rollup 技术集成与资产安全保障

在技术实现路径上,Merlin Chain 采用了 ZK-Rollup 技术,将大量的交易证明压缩成一个简单的校验和,从而降低 DA 上链成本。二层的 sequencer 节点负责收集和批量处理交易,通过 zkEVM 生成压缩后的交易数据、ZK 状态根以及 Proof 证明。

压缩后的交易数据和 ZK Proof 将通过去中心化 Oracle 网络上传到比特币一层的 taproot 中,面向全网公开,以确保透明度和公正性。

其中,去中心化 Oracle 网络节点将会被要求质押 BTC,以保证其不会做恶。用户则可以基于压缩数据、ZK 状态根和 ZK Proof 发起对 ZK-Rollup 的挑战。成功挑战将导致回滚到上一验证通过状态,并罚没 Oracle 节点的锁仓资产,确保系统的安全性和可信度。

通过这些技术模块的整合,Merlin Chain 有望构建一个高效、安全、原生比特币的二层解决方案。

引领原生比特币生态的整合与扩张

除了强大的技术实力之外,Merlin Chain 与其他 Layer 2 项目的不同之处还在于,团队极为注重“比特币原生”,希望最终能为比特币的发展做出贡献。因此,作为服务比特币生态的第一步,团队通过账户抽象协议,成功实现了比特币钱包在 EVM 链上的集成。

在 Merlin Chain 上,原生比特币生态系统的用户可以继续使用他们的比特币钱包,在一层和二层网络之间自由切换,还能够体验比特币与其他资产之间的无缝互换。与此同时,之前从未接触过比特币的以太坊生态系统用户也可以使用他们熟悉的 EVM 钱包,例如 MetaMask,来进行交互,支付稳定币或以太坊、BNB、MATIC 等 EVM 系代币。通过这种方式,Merlin Chain 成功降低了比特币与以太坊两个生态系统用户之间的互动门槛,有望为比特币生态系统带来新的用户增长和活跃度。

解读蓝盒子团队的BTC L2项目Merlin Chain

除此之外,Merlin Chain 还支持 BRC-20、BRC-420、Bitmap、Atomicals 等铭文协议。用户可以通过跨链桥将这些原生资产转移到 Merlin Chain,甚至可以在 Merlin Chain 上以更低的价格和至少三倍的交易速度铸造比特币一层的铭文。

解读蓝盒子团队的BTC L2项目Merlin Chain

在 Merlin Chain 上,用户在一层网络上获得的铭文资产将会自动被添加到白名单中,以确保用户在 Merlin Chain 上的交易安全。这一系列的设计使得 Merlin Chain 成为一个多元化、高效率的生态系统,吸引了各个领域的合作伙伴。

解读蓝盒子团队的BTC L2项目Merlin Chain

目前,Merlin Chain 已经公布了的生态伙伴涵盖了 DEX、DeFi、游戏、社交等多个领域,预计在主网上线后将进一步扩大其生态规模。

坚守比特币原生信仰,践行去中心化治理

在代币经济方面,Merlin Chain 坚持对“比特币原生”的信仰,否定了使用以太坊资产作为比特币二层网络治理代币的构想,转而选择采用原生的 BRC-20 协议。作为对去中心化理念的遵循,Merlin Chain 的治理代币会根据链上用户的质押和活动情况,把绝大部分代币都释放给用户和社区。

解读蓝盒子团队的BTC L2项目Merlin Chain


Leituras Relacionadas

1996 or 1999? Walsh's First Test is 'How to View AI'

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distinguishes between expected and unexpected productivity booms. A widely anticipated boom, like the current AI wave, can cause people to spend future wealth gains in advance, overheating the economy before productivity actually rises, thus requiring preemptive rate hikes. He cites rising costs for AI data centers as evidence of such overheating. Fed Governor Christopher Waller offers a rebuttal to Goolsbee, noting the "expected spending" mechanism only works if people can borrow against future income, which many households cannot do due to borrowing constraints. Wall also faces a paradox related to his desire to reduce the Fed's use of "forward guidance" (pre-announcing policy moves). This practice was established in 1999 when Greenspan began signaling hikes to avoid market shocks. If the economy follows a less optimistic path, Wall may be forced to choose between using the guidance he wants to abolish or risking market volatility by staying silent. The ultimate question defining Wall's first major test remains: Is this 1996 or 1999?

marsbitHá 5m

1996 or 1999? Walsh's First Test is 'How to View AI'

marsbitHá 5m

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbitHá 1h

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbitHá 1h

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbitHá 1h

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbitHá 1h

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbitHá 3h

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbitHá 3h

Trading

Spot
Futuros
活动图片