Morph联创:加密行业缺乏中心化枢纽或会阻碍创新

比推Опубліковано о 2024-09-10Востаннє оновлено о 2024-09-10

作者:Morph联创Azeem Khan,CoinDesk;编译:白水,金色财经

去中心化是 Web3 中一个备受争议的话题,但它可能扼杀创新的一个领域是风险投资。在 Web2 中,风险投资集中在湾区,这为创始人们创造了一个明确的中心,他们知道他们需要在那里。如今,顶尖的建设者分散在全球各地,缺乏一个中心枢纽可能会阻碍一些最有前途的创新者获得他们所需的资源,以建立、启动和扩大能够推动行业向前发展的公司。

考虑一位创始人在 Web2 中建立一家人工智能 (AI) 公司的例子。如果你在世界任何地方开发人工智能产品,人们普遍认为你需要找到通往湾区的路。这是因为湾区拥有许多世界顶级风险投资家 (VC)、大量才华横溢的专业人士、可以作为灵感的成功公司,以及像 Y Combinator 这样的加速器。

当然,这种中心化也存在弊端,就像任何情况一样,双方都存在机会成本。举几个例子,获得美国签证仍然是国际创始人面临的最困难的障碍之一。除此之外,湾区高昂的生活成本也是有据可查的。对大多数人来说,搬迁意味着搬到一个没有朋友或家人的地方,这会带来一系列心理和情绪健康挑战。

此外,弄清楚如何在一个新城市建立人脉网络并非易事,因为新城市往往远离任何熟悉的地方。然而,有许多人成功克服了这些挑战,在几十年里建立了价值数十亿美元的公司。虽然这并不容易,但传统观点认为这仍然是可以实现的。

现在,让我们将这一点与加纳、阿根廷或越南的创始人进行对比。来自南美、非洲和东南亚等地区的建设者通常有实际用例,区块链可以改善日常生活,特别是由于银行等领域缺乏强大的基础设施,或者因为年轻人更愿意采用新技术。虽然这些地区可能有出色的建设者,但由于没有建立网络或关系,他们在将项目扩展为成熟公司时处于明显劣势。如果没有集中的中心或强大的关系,这些建设者在将他们的创新推向全球规模时面临重大挑战。

建设创新中心需要的不仅仅是风险资本,但由于风险投资公司的职责是寻找和资助最好的公司,当顶级建设者与可能推动他们的想法的风险投资之间出现脱节时,就会出现一个重大障碍。这可能意味着,即使有开创性的想法和在此基础上发展的人才,许多潜在的企业家也无法获得必要的资源。在这种情况下,一定程度的中心化——特别是在创新中心——实际上可以成为增长的积极催化剂。

加密货币推特上普遍存在一种观点,即没有令人兴奋的事情发生,也没有人开发消费者应用程序来吸引大众。有些人甚至认为风险投资家没有资助这些项目,因为他们被视为资本主义的讽刺画,只专注于为自己的利益支持下一家基础设施公司。

但如果我们从错误的角度看待问题会怎样?一些最好的建设者,特别是在全球南方,是否有可能根本无法获得创办能够将用户带到链上的公司所需的资源?如果我们接受这个前提,那么解决方案就是建立必要的桥梁,不是吗?

一些最优秀的区块链建设者,尤其是来自全球南方国家的建设者,根本无法获得创办能够将用户引入区块链的公司所需的资源。

现实情况是,风险投资既不可能也不太可能同时出现在所有地方。即使行业日趋成熟,越来越多的风险投资流入 Web3 公司,期望资金能够在全球范围内平等分配也是不现实的。我们已经看到某些枢纽成为创新者的首选目的地,这些枢纽受到监管便利、签证准入、生活成本、气候和时区等因素的吸引。纽约、里斯本、迪拜、新加坡和布宜诺斯艾利斯等城市正逐渐成为枢纽。但由于这种成熟需要时间,问题仍然存在:我们在此期间能做些什么来促进创新?

所有这些都不意味着未来是黯淡的。有许多可靠的线上和线下举措的例子,旨在让全球的建设者加入进来。Zuzalu 和 Edge Esmeralda 等弹出式城市和网络国家越来越受欢迎,它们专注于技术创新的非传统地点,并将来自世界各地的年轻创新者聚集在一起。像 Developer DAO 这样的项目正在努力教育和让更多的建设者加入 Web3,而 BuidlGuild 则专注于做同样的事情,重点是以太坊。

ETH Accra 和 ETH Vietnam 等活动以去中心化的方式全年举行,聚集了全球城市的建设者,共同开展令人兴奋的项目。像 ETHGlobal 这样的公司全年都会举办线上和线下的黑客马拉松,而以太坊基金会 (EF) 的 Devcon 学者计划通过承担来自世界各地的参与者加入和了解以太坊的费用,成功地吸引了新的人才。

EF 还为想要参加的当地人提供折扣门票。为建设者和增长而努力的人就在那里,这些都是风险投资家如何更明智地部署资本、让他们自己寻找资源的例子。他们中最聪明的人会这样做。有些人已经这样做了。

去中心化带来了挑战和机遇。上面讨论的问题最终会得到解决——很可能是由创新思想家在拥有资源的人和需要资源来创建公司的人之间架起桥梁来解决。事后看来,这似乎很简单,但关键是要为那些在实地辛勤工作的人提供资金。通常,推动行业前进的人资金最少。如果我们想加快采用的速度,我们需要加快为那些应对最严峻挑战的人提供资金的速度。

因此,对于那些试图弄清楚将营销预算投入到哪里的风险投资家来说,不要在下次会议上举办豪华晚宴,而是做些不同的事情,直接资助那些将建设者聚集在一起、吸纳新人才和应对扩展 Web3 的真正挑战的计划。

说明: 比推所有文章只代表作者观点,不构成投资建议

Пов'язані матеріали

Google CEO Admits Lagging Behind in Coding

Google CEO Sundar Pichai acknowledged in a recent interview that Google's Gemini AI models are currently "lagging behind" in coding capabilities, particularly for complex, long-horizon tasks requiring advanced developer expertise. He noted the field is advancing at an "unprecedented" pace, where 30-60 days now brings changes equivalent to five years in the past. Pichai expressed that achieving Artificial General Intelligence (AGI) now seems closer than previously imagined due to rapid progress. While highlighting strengths in text, multimodal, and reasoning tasks, Pichai admitted competitors like Anthropic and OpenAI have focused more intently on coding. He emphasized Google's commitment to catching up, citing internal tools like Antigravity 2.0 and the newly released Gemini 3.5 Flash, which aims to address previous shortcomings. Regarding Google Search's AI-driven overhaul, Pichai stated changes will be gradual to align with user needs, not disrupt the core search experience or its advertising model. He addressed public AI anxiety as understandable, given the technology's potential to reshape jobs and society, but remained optimistic about AI augmenting human capabilities and creating new opportunities. Pichai stressed the need for broad societal dialogue and responsible development as AI approaches more advanced, potentially recursive self-improvement stages. He affirmed Google's long-term commitment to leading in AI while navigating its profound implications responsibly.

marsbit1 год тому

Google CEO Admits Lagging Behind in Coding

marsbit1 год тому

The Paradox of Automation: The Stronger the AI, the Busier Humans Become

The Paradox of Automation: The more powerful AI becomes, the more work humans have to do. This article, based on observations from AI-heavy company Every, argues that while AI agents automate tasks like coding, writing, and customer service, they don't eliminate human jobs. Instead, they transform work and create *more* demand for human expertise. AI commoditizes "yesterday's human capabilities" by cheaply generating code, text, and images from past data. This leads to an abundance of similar, generic outputs. Consequently, what becomes scarce and valuable is human judgment in the present moment: knowing *what* is worth doing, *why*, and *how* to do it well. The article identifies two collaboration models: "Agent employees" for delegated tasks and "human-AI collaboration" within tools like Claude Code for complex work. In both cases, humans are essential to set direction, judge quality, and maintain systems. As AI makes execution cheap, human roles shift from executors to designers, reviewers, and meaning-makers. The author addresses "benchmark anxiety" by explaining that AI excels within specific, human-defined problem "frames." As AI masters one frame (e.g., code rewriting), new, more complex frames emerge (e.g., deciding *when* to rewrite). This creates an ongoing cycle where AI chases the frames, but humans remain the "framers." Even with advanced AGI, this dynamic may persist as long as AI lacks true human-like agency and self-directed purpose. The core paradox holds: automation amplifies the need for the very human judgment it seems to replace.

marsbit2 год тому

The Paradox of Automation: The Stronger the AI, the Busier Humans Become

marsbit2 год тому

a16z: 7 Charts to Understand How Tokenization is Changing the Nature of Assets

"a16z: 7 Charts on How Tokenization is Changing the Nature of Assets" Tokenized Assets (or Real-World Assets - RWA) are transforming asset forms, liquidity, and financial system construction. The market recently surpassed $30 billion, stabilizing around $34 billion (excluding stablecoins), representing a tenfold increase in less than two years, driven by clearer regulations, mature institutional infrastructure, and increased financial institution adoption. The primary driver of recent growth is tokenized U.S. Treasury bonds. These offer investors efficient, flexible digital access to yield-bearing assets and improve institutional operations like settlement and collateral management. Other asset classes show varied growth: asset-backed credit leads, followed by niche financial assets (e.g., reinsurance, mining notes), while venture capital took longer to scale. Market segmentation shows high concentration. In commodities, tokenized gold dominates (~$5 billion), as its standardized, storable nature fits tokenization well. Bonds are the largest category ($15.2B), but only ~5% are used in DeFi protocols. Conversely, smaller niches like reinsurance tokens see high (~84%) on-chain utilization, highlighting a core industry divide: most current tokenized assets are merely digitized records for easier holding/transfer, lacking the "composability" (free combination/interaction) that is key to blockchain-native finance. The ecosystem is distributed across multiple blockchains, with Ethereum hosting over half the value ($15.7B), followed by BNB Chain, Solana, and others. Future market size predictions vary widely (e.g., $2-$30 trillion by 2030+), but all indicate massive potential from the current small base. Tokenized assets currently represent minuscule fractions of their global counterparts (e.g., 0.01% of global bonds). The current phase focuses on digitizing straightforward assets. The next challenge is to bring more complex financial components on-chain and deeply integrate tokenized assets into composable, internet-native financial infrastructure.

链捕手3 год тому

a16z: 7 Charts to Understand How Tokenization is Changing the Nature of Assets

链捕手3 год тому

a16z: How Tokenization is Transforming the Nature of Assets in 7 Charts

"Tokenized Assets: How Tokenization Changes the Nature of Assets" by a16z Crypto The market for tokenized assets, excluding stablecoins, has grown from under $3 billion two years ago to over $340 billion today. US Treasury bonds are the primary growth driver, allowing investors to hold yield-bearing assets digitally and enabling more efficient settlement. Other key sectors include private credit (growing fastest), commodities (dominated by gold), and niche financial assets. However, the market remains concentrated in tokenized US Treasuries and gold. A critical insight is that most tokenized assets currently lack "composability." While the total market is large, only a small fraction is actively used within DeFi protocols. For instance, only about 5% of tokenized bonds and a low percentage of tokenized gold are utilized on-chain. In contrast, assets like reinsurance and private credit tokens show much higher on-chain usage rates (84% and 33%, respectively). This highlights a divide: many tokenized assets are merely digital records on a blockchain without enabling new, programmable financial applications. The Pantera Capital Token Native Index indicates over 70% of tokenized assets have minimal on-chain native functionality. Ethereum remains the dominant blockchain for tokenized assets (over $150B), but the ecosystem is diversifying across chains like BNB Chain, Solana, and Stellar, based on factors like cost and compliance. Major institutions forecast massive future growth, with predictions for the tokenized asset market ranging from $2 trillion to over $30 trillion by the early 2030s. However, compared to the global financial system (e.g., ~$140T bonds, multi-trillion dollar gold market), tokenized assets currently represent a tiny fraction (0.01% or less). The conclusion is that while tokenization has begun by digitizing and streamlining settlement for simpler assets, the next phase involves bringing more complex financial instruments on-chain and deeply integrating them into composable, internet-native financial infrastructure.

Odaily星球日报3 год тому

a16z: How Tokenization is Transforming the Nature of Assets in 7 Charts

Odaily星球日报3 год тому

The Revived Codex, Carrying OpenAI's Hopes for IPO

This article analyzes the intense recent development of OpenAI's Codex, positioning it as a crucial component for OpenAI's impending IPO. Over the past two months, Codex has seen a rapid series of major updates focused on integrating into real enterprise workflows. Key new features include enhanced context capture (Appshots, file previews, built-in browser), long-running task execution ("Goal Mode"), remote operation (phone control, lock-screen access), and enterprise management tools (plugin sharing, access tokens, automated risk review). These updates aim to make Codex a comprehensive AI workbench that can "see the scene, push tasks, and manage risks." The author argues that while ChatGPT proves OpenAI's massive user base and API provides foundational revenue, Codex represents OpenAI's clearest path to demonstrating tangible, high-value commercial viability. It targets developers and engineering teams—a segment already accustomed to paying for efficiency gains in costly software development cycles. This is critical because, despite higher overall revenue, OpenAI's adjusted operating margins remain deeply negative, highlighting the challenge of outrunning immense compute costs. The pressure is amplified by competitor Anthropic's success with Claude Code, which has shown that a focused approach on high-value enterprise and developer workflows can lead to a path toward profitability. Codex's aggressive evolution is thus seen as OpenAI's strategic move to capture a similar enterprise-ready, revenue-generating narrative essential for its market debut. In essence, "ChatGPT proved OpenAI has users. Codex needs to prove OpenAI is a business that can make money."

marsbit4 год тому

The Revived Codex, Carrying OpenAI's Hopes for IPO

marsbit4 год тому

Торгівля

Спот
Ф'ючерси
活动图片