传统金融巨鳄再落子!景顺挖角摩根大通区块链悍将,16亿加密ETF帝国换帅

marsbitPublicado em 2025-06-11Última atualização em 2025-06-11

这家管理着1.8万亿美元资产的全球资管巨头迎来凯瑟琳·瑞恩(Kathleen Wrynn),由其负责管理加密ETF及其他代币化资产组合。

全球资产管理公司景顺(管理规模达1.8万亿美元)宣布任命摩根大通区块链领域资深专家凯瑟琳·瑞恩领导其数字资产业务。该公司加密ETF与代币化资产组合规模达16亿美元。此次人事变动正值机构加速接纳数字资产之际。

景顺集团(管理资产1.8万亿美元)任命摩根大通区块链业务老将凯瑟琳·瑞恩执掌其超十亿美元规模的数字资产组合,这一举措凸显金融机构对加密货币日益增长的兴趣。

瑞恩将担任景顺全球数字资产主管——这是新设立的职位,负责监督各类代币化资产与加密货币投资的管理工作。

景顺发言人周三向Decrypt提供的声明表示,瑞恩还将主导资产代币化基金、加密货币融入投资策略等创新项目。声明显示,景顺目前管理着16亿美元的数字资产ETF,包括三只区块链与加密生态系统ETF及三只全球现货加密货币ETF。

瑞恩此前主管摩根大通区块链业务,主导Web3生态系统相关的产品开发。这项人事任命将助力景顺拓展数字资产业务,当前正值各类机构投资者积极探索加密货币及其底层技术之时。

Coinbase最新报告显示,在百家《财富》500强企业的调研中,60%表示已投资或正在开展区块链相关项目。另据数据提供商Chainalysis《2024加密货币地理报告》,北美近期约70%的加密交易涉及超百万美元大额转账,凸显美国等主要市场机构对加密货币的强烈兴趣。

Bitcointreasuries.net数据显示,过去一年已有120余家上市公司(多数此前与加密行业无关联)建立比特币储备。与此同时,多家上市企业也表露出囤积以太坊、Solana、XRP等其他数字资产的意向。

这一趋势形成之际,美国总统特朗普正推动多项联邦层面的加密友好政策,接连发布行政令要求保护比特币矿工权利,并指示财政部建立战略比特币储备。

Leituras Relacionadas

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbitHá 19m

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbitHá 19m

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbitHá 1h

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbitHá 1h

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbitHá 1h

This is How God Karpathy Uses Claude?

marsbitHá 1h

Trading

Spot
活动图片