观点：以太坊VC对基建的痴迷正在拖累全行业

区块律动Published on 2024-08-29Last updated on 2024-08-29

#以太坊#VC#基础设施#加密市场

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Harvard and Others Exit, Six Core Talents Depart in a Month: What's Happening to Ethereum?

Ethereum faces significant internal and external pressures, marked by a wave of high-profile departures from its core development team and a loss of confidence from major institutional investors. Within four months, at least seven key figures—including researchers, protocol leads, and a former executive director—have left the Ethereum Foundation. This exodus, partly triggered by controversy over a new "mission statement" requiring employee sign-off, risks derailing critical roadmap upgrades like PeerDAS and Verkle trees, and has already contributed to delays in the planned Glamsterdam upgrade. Compounding the internal instability, major institutions are reducing their exposure. Goldman Sachs slashed its iShares Ethereum Trust holdings by approximately 70%, and Harvard's endowment fund completely exited its $87 million Ethereum ETF position. Concurrently, the Ethereum Foundation itself has been unstaking and selling ETH for "treasury rebalancing," further unsettling the market. These challenges emerge as Ethereum's competitive dominance erodes. Its share of the total DeFi market has fallen to around 54%, with rivals like Solana and Base gaining ground. In fee revenue, it was recently outpaced by newer chains like Hyperliquid. Furthermore, a trend of institutions exploring proprietary or hybrid blockchains (exemplified by Circle's Arc) threatens Ethereum's position as the premier settlement layer for institutional assets. While founder Vitalik Buterin's vision for Ethereum as a secure, decentralized "technical sanctuary" and "world computer" remains clear, its realization is threatened by the concurrent loss of execution capability, institutional patience, and market share during a critical competitive phase.

链捕手3m ago

Harvard and Others Exit, Six Core Talents Depart in a Month: What's Happening to Ethereum?

链捕手3m ago

IOSG | After the Halving of Developer Count: Crypto Isn't Dead, It's Just Handing Over Talent to AI

IOSG Report: Crypto's Developer Exodus Masks a "Talent Deleveraging" and Migration to AI The number of monthly active crypto developers on GitHub has roughly halved from its 2022 peak to around 23,000. This decline is not a sign of industry collapse but a "talent deleveraging." The exodus consists largely of newcomers who entered during the bull market, while the cohort of established developers (2+ years of experience) has grown to a record high, now contributing about 70% of the code. These core builders are consolidating in ecosystems with real users and activity, like Bitcoin and Solana. The crypto industry has forged a unique skill set: building operational, trusted systems from scratch in environments with no external authority, near-zero tolerance for error, and missing rules. This involves creating trust through pure code/mechanisms and making judgments under profound technical and economic uncertainty. This capability is finding new, high-value applications in the AI era, which faces structurally similar problems: trust in opaque autonomous systems, a lack of governance frameworks, and coordination among self-interested AI agents. Key migration patterns include: 1. **Direct Hardware/Infrastructure Translation:** Projects like CoreWeave pivoted from GPU mining to AI compute supply. 2. **Mechanism Design & Trust Engineering:** Crypto's experience in decentralized coordination and incentive design (e.g., via tokenomics, staking/slashing) is being applied to critical AI challenges: * **Compute Aggregation & Verification:** Solving trust and efficiency problems in decentralized GPU networks (e.g., Hyperbolic). * **AI Agent Governance:** Using cryptoeconomic mechanisms to align the behavior of multiple autonomous AI agents (e.g., EigenLayer's approach). * **Autonomous Agent Payments:** Leveraging stablecoins and programmable money for fast, permissionless micro-transactions between AI agents (e.g., x402 protocol). The builder's role is evolving from "writing smart contracts" to "designing trust mechanisms for autonomous AI systems." This convergence is reflected in hiring trends at major firms and significant capital allocation from top venture funds like Paradigm and a16z into the crypto-AI intersection. While regional approaches differ—with the US focusing more on foundational protocol innovation and Asia on application-layer integration—the core thesis remains: the systemic skills honed in crypto's trustless environments are becoming a scarce and critical asset for scaling AI.

marsbit4m ago

IOSG | After the Halving of Developer Count: Crypto Isn't Dead, It's Just Handing Over Talent to AI

marsbit4m ago

From Farm to Entrepreneur: After Building Flying Cars, He Bet on the Robot Sector and Created a $39 Billion Giant

From Farm to Tech Tycoon: Brett Adcock's Journey to a $39B Robot Giant Brett Adcock, a serial entrepreneur from an Illinois farm, has built his third major venture, humanoid robotics company Figure AI, into a $39 billion behemoth backed by NVIDIA, Intel, and others. His path began with the sale of his recruiting platform Vettery for $110 million in 2018. He then co-founded and took electric air taxi company Archer Aviation public in 2021 before departing over strategic differences. Adcock founded Figure AI in 2022 with a 30-year vision to create general-purpose humanoid robots that can work in human-designed environments, aiming to address labor shortages in manufacturing, logistics, and retail. The company gained attention through live-streamed robot sorting challenges and a viral demo, though it faces skepticism over its high valuation versus early commercial progress. A key moment was Figure's split from OpenAI in 2024 after a brief collaboration, with Adcock claiming OpenAI provided limited value and deciding to develop AI models internally—a move OpenAI contested. Adcock's pattern is tackling capital-intensive, long-term tech frontiers, moving from software to aviation to robotics, betting on AI and automation as the future of labor.

marsbit36m ago

From Farm to Entrepreneur: After Building Flying Cars, He Bet on the Robot Sector and Created a $39 Billion Giant

marsbit36m ago

How to Become a Pro Claude User in 30 Days?

"How to Become a Claude Power User in 30 Days" outlines a structured month-long program to transform from a casual user into someone who leverages Claude as a core productivity system. The first week focuses on mastering prompt structure (Role, Context, Task, Format, Constraints), understanding context windows, and setting up foundational Projects and Memory for personalized context. The second week involves building reusable workflows for research, writing (using a two-step outline-first process), and decision-making. The third week shifts to automation: using Claude Cowork for autonomous file tasks, connecting tools like Google Drive and Slack, and setting scheduled automation. The final week is for compounding gains: optimizing all workflows based on feedback, building a personal knowledge repository, teaching the system to a colleague, and designing a complete, ideal "Claude Operating System." By day 31, the user operates with an autonomous assistant that handles routine tasks with deep context, freeing them for high-value creative and strategic work. The core message is that consistent, systematic configuration over 30 days creates a powerful, personalized productivity advantage.

marsbit1h ago

How to Become a Pro Claude User in 30 Days?

marsbit1h ago

Data: 75% of Traders on Hyperliquid Are Losing Money. What Are the Profitable Ones Using?

On Hyperliquid, approximately 75% of addresses are losing money, indicating that manual traders are increasingly competing against automated systems. Profitable traders primarily employ one of three approaches: 1) Running systematic, high-frequency strategies (e.g., one address executed 261k trades with a 64.75% win rate), 2) Placing high-conviction, asymmetric bets with large positions (e.g., 50 trades yielding $4.48M at a 28% win rate), or 3) Using algorithms for execution while making manual macro judgments. The article argues that traditional methods like chart patterns or reacting to social media news are often already priced in by bots, making such traders the "exit liquidity" for systematic players. Success now depends on unique narrative timing, structural insights, or conviction during market capitulation.

marsbit1h ago

Data: 75% of Traders on Hyperliquid Are Losing Money. What Are the Profitable Ones Using?

marsbit1h ago

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