代币化证券赛道初探及头部项目一览

tokeninsight_zhPubblicato 2025-06-02Pubblicato ultima volta 2025-06-03

本篇文章经分析师精选，并对其重点内容进行了总结。如果您对文章内容感兴趣，请移步英文版阅读全文。

  • 代币化证券是将现实世界的金融资产（如股票、债券）通过区块链技术转化为数字代币，1:1锚定真实资产，具备实际持有权。其核心流程包括资产托管、区块链发行（通常借助智能合约）以及可在交易所或DeFi平台上进行24/7全天候交易。
  • 代表性平台如 Backed Finance、Swarm、Dinari 和 Securitize，正通过合规托管、跨链部署与监管许可，推动全球投资者便捷获取美股和其他传统资产。稳定币（如USDC）与代币化证券的结合，为跨境支付与资产结算提供了低成本、高效率的解决方案。
  • 代币化证券仍面临托管方失信、智能合约漏洞及监管不确定性等风险。尤其是在缺乏统一法律框架的背景下，部分平台只能面向非美国投资者运营，合规性与资产安全仍是发展中关键问题。

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Sharplink adds $62.4M in Ethereum despite ETH’s weak demand – Here’s why

Sharplink, the second-largest Ethereum treasury company, purchased an additional 29,196 ETH for $46.7 million on June 27. Over the past three days, its Ethereum holdings increased by 39,196 ETH, worth $62.4 million. This marks Sharplink's second major purchase after an eight-month pause, bringing its total ETH holdings to 868,699, including staked tokens. Concurrently, Sharplink's stock price rose 5.48% to $4.81. In comparison, the largest Ethereum holder, Bitmine, acquired 52,203 ETH for $92 million on June 22 and plans steady growth through 2026. These institutional accumulations occur against a backdrop of weak Ethereum market demand. ETH's price recently hit $1,568.75, its lowest since April 2025, with on-chain data indicating diminished aggressive buying momentum and signs of buyer exhaustion compared to the previous year.

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Sharplink adds $62.4M in Ethereum despite ETH’s weak demand – Here’s why

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A Group of Suzhou Engineers Unexpectedly Attain Financial Freedom

In Suzhou, a group of engineers from Lianxun Instruments, a leader in optical communication testing equipment, have achieved remarkable wealth after the company's IPO. Listed just two months ago on the STAR Market, the company's stock price surged approximately 30 times, making it the only A-share stock priced above 2,000 yuan. This surge created substantial fortunes for nearly 100 technical employees who held a collective 15.91% stake through employee stock ownership platforms, valued at over 36 billion yuan at the current market cap. Among them, nearly 40 became billionaires, while even the smallest holdings exceeded 5 million yuan in value. Founded in 2017 by Hu Haiyang, Yang Jian, and Huang Jianjun, Lianxun Instruments was established to address China's reliance on foreign high-end testing instruments. The company grew rapidly with a strong focus on R&D, where technical staff make up nearly 80% of its workforce. Early implementation of employee stock plans helped retain this core talent. The company's explosive growth is fueled by booming AI computing demand, with clients including major global optical module leaders. Its revenue skyrocketed from 276 million yuan in 2023 to 1.194 billion yuan in 2025, turning a profit in 2024. The IPO has also generated massive returns for early investors, including Suzhou's state-owned capital, which saw a hundredfold return. This story reflects a broader trend in China's markets, where technology firms in AI, semiconductors, and optics are creating new wealth, rewarding engineers and technical teams who are now central to modern capital-driven success stories, marking a shift from previous eras dominated by internet and real estate tycoons.

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A Group of Suzhou Engineers Unexpectedly Attain Financial Freedom

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NVIDIA's Annual 'Most Dangerous' Paper: AI Self-Replicating Code, Unlimited Leveling and Evolution

NVIDIA's "Red Queen Gödel Machine" (RQGM) paper proposes a potentially groundbreaking AI self-evolution framework. It breaks from the long-stalled concept of the "Gödel Machine," which required mathematically proven beneficial self-modifications, by adopting an evolutionary approach. The core, and most striking, innovation is that the AI does not just evolve its own code in a static environment. Instead, it co-evolves both the "student" (the task-performing agent) and the "examiner" (the evaluation system that judges it). This creates a dynamic, recursive self-improvement loop inspired by the biological "Red Queen Hypothesis"—where continuous adaptation is needed just to maintain relative fitness. The mechanism operates in epochs. Within an epoch, a fixed examiner evaluates all candidate code variants. At epoch boundaries, a new, potentially more rigorous examiner can replace the old one, but only if it proves statistically superior on a held-out "ground truth" dataset. This "controlled utility evolution" aims to ensure progress is measurable and grounded. The paper demonstrates RQGM's effectiveness across three domains: 1. **Code Generation:** It achieved a 71.7% test-set pass rate (improving over a 69.9% SOTA) while using 1.35-1.72x fewer computational tokens. 2. **Paper Writing:** In a subjective task, the co-evolved writer and reviewer achieved a 40.5% acceptance rate by a fixed human panel, up from 21.8%. 3. **Math Proofs:** It evolved more accurate graders (at 3x lower cost) and higher-scoring provers. Notably, RQGM also mitigated a known LLM bias where AI reviewers favor AI-generated content. By specifically rewarding reviewers that correctly rejected AI-written papers from a historical pool, the evolved system achieved impartiality while maintaining 80% accuracy. The research has sparked significant discussion about the acceleration of Recursive Self-Improvement (RSI). Some, like Anthropic's Jack Clark, have predicted a high probability of highly autonomous, self-evolving AI emerging by 2028. The paper suggests that when an AI begins to design its own evaluators and push itself toward ever-higher standards in a recursive loop, it may be taking a fundamental step toward redefining intelligence and autonomy.

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NVIDIA's Annual 'Most Dangerous' Paper: AI Self-Replicating Code, Unlimited Leveling and Evolution

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Apple and the Power Rebalancing with 'The Microns': Dissecting the Profit Ledger Behind the iPhone

The article analyzes the shifting profit dynamics and power balance between Apple and memory suppliers like Micron within the iPhone supply chain. It highlights a social media post criticizing Apple for raising iPhone prices while blaming memory chip cost increases, despite historically paying suppliers like Micron very little. An estimated iPhone 18 cost breakdown is referenced. Historically, memory was a minor cost component. In 2017's iPhone X, memory accounted for only about 1.6-2.3% of the price, with Apple capturing nearly 50% net profit. Over time, memory's share of the Bill-of-Materials (BOM) cost has grown significantly, reaching an estimated 12-15% for the iPhone 17 series. The core driver of this change is soaring demand for memory from the AI industry, particularly for High Bandwidth Memory (HBM) and AI servers, which is diverting production capacity and squeezing supply for consumer electronics. Memory manufacturers, after enduring periods of low profits, now hold greater pricing power. This is reflected in their recent strong financials, like Micron's 84.6% gross margin. Apple CEO Tim Cook initially described the memory price pressure as unprecedented in his 40-year career, later calling it a "once-in-a-century flood," before Apple announced price hikes across several product lines, causing a significant stock drop. Elon Musk echoed Cook's sentiment about the dramatic cost surge. The article concludes that the era of memory suppliers being at the mercy of Apple's pricing power has temporarily reversed, thanks to AI-driven demand. It notes Apple is reportedly seeking to diversify its supply chain, including exploring chips from China's CXMT.

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Apple and the Power Rebalancing with 'The Microns': Dissecting the Profit Ledger Behind the iPhone

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Can BTC whales save Bitcoin after $4.06B ETF outflows?

Institutional demand for Bitcoin shows signs of weakening, with U.S. Spot Bitcoin ETFs experiencing seven consecutive days of net outflows, totaling roughly $4.06 billion in monthly outflows and reducing total ETF assets to $72.82 billion. This decline removes a key source of structural spot buying. However, large Bitcoin holders (whales) have shown increased accumulation activity as prices dipped below $60,000, with a significant spike in high-value transactions, suggesting they view the correction as a buying opportunity. This whale demand could help cushion near-term selling pressure. Conversely, Long-Term Holders are showing signs of capitulation, with metrics indicating realized losses and eroding conviction, which may eventually reduce future selling pressure. For a sustained recovery, broader spot market participation remains essential.

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Can BTC whales save Bitcoin after $4.06B ETF outflows?

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