以太坊的文化冲突:异议、去中心化与进步

链捕手Published on 2024-12-17Last updated on 2024-12-17

原标题:《Ethereum’s culture clash: Dissent, decentralization and progress

作者:Macauley Peterson,Blockworks

编译:邓通,金色财经

 

以太坊社区正处于文化十字路口,对杰出贡献者 Max Resnick 的离职引发的激烈反应揭示了围绕治理和异议的更深层次的紧张关系。Resnick 对以太坊治理和可扩展性方法的批评引起了压倒性的负面反应,包括指责其为「Solana 工厂」和其他人身攻击。这些回应凸显了以太坊社交层和决策过程中更广泛的问题。

以太坊中的极端主义

以太坊极端主义已经开始反映出比特币极端主义的一些不太有建设性的特征。关于异议日益被压制的争论比比皆是,批评者被贴上局外人或反对者的标签。Resnick 的批评虽然强调了真正的挑战,但也遭到了敌意。他的沟通风格通常被认为是敌对的,疏远了关键贡献者。社区中的一些人认为他的离开是一个积极的因素,强化了共同的价值观,并强调异议必须是建设性的,以避免分裂。

这并非 Resnick 所独有。 Jon Charbonneau 等人也对去中心化作为一种抽象理想的想法提出了挑战,认为它会扼杀实践中富有成效的辩论。 Charbonneau 在他的「以太坊的北极星」博客文章中写道:「如果去中心化是唯一的目标,那么为什么不降低区块 Gas 限制、降低 Blob 数量并增加时隙时间呢?很多时候,大喊‘啊哈,这是牺牲权力下放!’只是用来结束富有成效的辩论。」

Charbonneau 强调以太坊需要定义其独特的目的。他敦促社区遵循长期原则,避免受短期动态驱动的决策。

社交层:优势还是劣势?

以太坊对社会共识的依赖长期以来一直被誉为正式治理的去中心化替代方案。然而,这种方法有缺点。即使以太坊的核心开发流程透明运作并吸引了不同的利益相关者,决策往往似乎由 Twitter 等平台上响亮、有影响力的声音主导。

核心开发人员遵循共识驱动的流程,公开构建以确保决策反映广泛的意见。这一过程抵制正式的捕获,但如果反对的声音被排除在外,则有可能陷入停滞。 Resnick 定期为 Eth Research 做出贡献,分享有关可扩展性和治理的见解,但他没有参加 ACD 电话会议,也没有大量参与活动。

比特币的教训

比特币的上涨,包括其涨至 10 万美元,不仅仅是由极端主义推动的。它源于持续的宣传努力,让政府、机构和公众参与建立强有力的社会经济叙事。相比之下,以太坊在很大程度上避免了现实世界的倡导,而是专注于维持其去中心化的精神。

以太坊的未来取决于信念和包容性的平衡。社区必须认识到,仅靠技术进步是不够的——强大的文化基础同样重要。纯粹性测试和不受控制的极端主义可能会扼杀创新和辩论,因此必须引入促进公开对话而不损害权力下放的机制。

以太坊最大的优势在于它的适应性。通过正面解决文化挑战,社区可以留住有价值的贡献者,并确保以太坊作为去中心化、包容性生态系统的领导地位。

Trending Cryptos

Related Reads

After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

Following the withdrawal of Aave and a sharp drop in its Total Value Locked (TVL), the valuation of the high-performance DeFi blockchain MegaETH faces scrutiny. Once a highly anticipated project with a fully diluted valuation (FDV) reaching around $2 billion, MegaETH saw its TVL plummet from a May peak of $245 million to just over $30 million in July, a roughly 70% decline. Its native token, MEGA, currently trades around $0.048 with a market cap of approximately $54 million and an FDV of about $480 million. The report identifies a core vulnerability: MegaETH's TVL was heavily dependent on a single protocol, Aave V3, which at its peak contributed around 90% of the chain's TVL. A significant portion of this capital is attributed to leveraged yield-farming strategies involving stablecoins like USDe. When the profitability of these strategies diminished, capital rapidly exited, exposing the lack of diversified, sustainable activity. Three key mismatches between MegaETH's valuation and its fundamentals are highlighted: 1. **Valuation vs. Real Usage:** With an FDV of ~$4.8B but only ~$1M in annualized protocol revenue and ~2,600 daily active addresses, the valuation appears disconnected from current economic activity. 2. **Token Narrative vs. Ecosystem Reality:** Despite its DeFi narrative, nearly 80% of the chain's recent protocol revenue comes from a trading card game, Monster, not from core DeFi applications like Aave. The chain's native stablecoin, USDM, also shows low trading volume and a declining market cap. 3. **Short-Term Hype vs. Long-Term Delivery:** Initial hype from token generation, blue-chip integrations, and influencer support has faded. Major protocols like Uniswap now hold minimal TVL on the chain, indicating that early capital was largely transient and driven by incentives rather than organic demand. The situation reflects a broader market trend where investors are becoming less tolerant of valuations based on inflated TVL and narrative, demanding clearer evidence of sustainable transactions, revenue, and ecosystem development. While MEGA's price may experience short-term rebounds from market sentiment, a fundamental re-rating likely depends on the team's ability to convert its remaining resources into tangible, user-retaining applications and genuine ecosystem growth.

链捕手2h ago

After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

链捕手2h ago

Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: China's AI Models at an Inflection Point China's open-source/open-weight large language models (LLMs) have reached performance parity with top global proprietary models, according to a Goldman Sachs report. This is driven by architectural innovations and higher parameter efficiency, allowing Chinese models to achieve comparable capabilities at 2%-10% the parameter size and significantly lower cost. The market is evolving into a two-tiered structure: a high-end segment (e.g., GLM5.2, Qwen3.7 Max) with premium pricing and a low-end, price-sensitive segment for global SMEs and individual users. Key points: * **Cost & Performance:** Innovations like Mixture of Experts (MoE) enable high performance with smaller models. Projects like Meituan's LongCat 2.0, trained on domestic hardware, highlight progress in tech self-sufficiency. * **Open-Source Strategy:** Most Chinese players use open-source/open-weight models for flexibility and ecosystem growth. However, Goldman notes this may underreport actual deployment and revenue. A shift toward "open-weight + community license" models with revenue sharing (e.g., MiniMax) could improve monetization. * **Market Shift & Global Expansion:** Enterprise AI adoption is shifting from "token maximization" to "ROI-first." International expansion, especially in non-US markets, is a major growth driver. Chinese models are increasingly available on global platforms like AWS Bedrock and Microsoft Copilot. * **Competitive Landscape:** Using a framework based on pricing power, cost advantage, and financial strength, Goldman identifies **Zhipu AI and DeepSeek** as the strongest in foundational text models, and **ByteDance** as the leader in multimodal/video generation. The report maintains Buy ratings on MiniMax and Kuaishou. * **Market Growth:** China's AI model API and subscription revenue is projected to grow from an estimated ¥35 billion in 2026 to ¥879 billion by 2030.

marsbit2h ago

Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

marsbit2h ago

Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry? China's AI large model sector is at a historic inflection point. Goldman Sachs argues that the intelligence of Chinese open-source/open-weight models is approaching top global proprietary models. Rapid adoption by domestic enterprises and global SMEs is creating a data flywheel effect that will further drive model iteration. The evolution is summarized as moving from "DeepSeek's cost-efficiency moment last year to GLM's model-intelligence moment this year." Chinese models achieve near-state-of-the-art performance at significantly lower cost, primarily due to architectural innovations like Mixture of Experts (MoE) and higher parameter efficiency. Models like DeepSeek V4 Pro (1.6T params), GLM5.2 (0.7T), and MiniMax M3 (0.4T) are much smaller than global leaders. Recent advancements in coding capability are attributed to better data curation and RLHF. Landmarks like Meituan's LongCat 2.0, trained fully on domestic AI chips, demonstrate progress in hardware stack independence. The market is forming a "two-tiered structure." The high-end tier (e.g., GLM5.2, Alibaba's Qwen3.7 Max) prices around $1 per million tokens, about 10-25% of US top models, with estimated inference gross margins of 10-20%. The low-end tier (priced as low as $0.06-$0.2 per million tokens) targets price-sensitive global SMEs and individuals. MiniMax derives 60-70% of revenue overseas. Goldman forecasts China's AI model API/subscription revenue to grow from an estimated RMB 35bn in 2026 to RMB 879bn by 2030. Most Chinese players adopt open-source/open-weight strategies for deployment flexibility and community feedback, though this limits monetization as deployments on third-party platforms (e.g., Alibaba Cloud) may not generate direct revenue. A shift towards "open-weight + community license" models with revenue-sharing agreements (like MiniMax's approach) could improve unit economics. International expansion, particularly in non-US markets, is the key growth driver. The global enterprise AI paradigm is shifting from "token maximization" to "ROI prioritization." Chinese models are already hosted on major global platforms like AWS Bedrock and are under consideration for integration into Microsoft Copilot. Using a competitive framework based on pricing power, cost advantage, and financial strength, Goldman identifies the strongest players: In foundational text models, Zhipu AI (initiated coverage) and DeepSeek lead. In multimodal/video generation, ByteDance's Seed is the frontrunner, with Kuaishou's Kling and MiniMax's Hailuo also well-positioned. Goldman maintains a Buy rating on MiniMax, citing its attractive valuation.

链捕手2h ago

Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

链捕手2h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片