Deutsche Bank заявил, что мировые ЦБ включат биткоин и золото в качестве основных резервных активов к 2030 году

cryptonews.ruPublished on 2025-07-12Last updated on 2025-10-13

Биткоин может стать новой опорой финансовой безопасности, подобно той роли, которую золото играло в 20 веке.

Об этом Deutsche Bank написал в своем отчете, объясняя это растущим институциональным принятием биткоина и продолжающаяся дедолларизация.

В отчете подчеркивается, что

1. Оба актива (биткоин и золото) войдут в резервы центробанков к 2030 году

2. Биткоин = современный аналог золота 20-го века

3. Не замена доллару, а дополнение для диверсификации.

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Century-Old Interlocking Director Law Revived, a16z Faces Antitrust Investigation

The US Department of Justice has reportedly launched an antitrust investigation into venture capital firm Andreessen Horowitz (a16z). The probe focuses on whether a16z's investment partners have improperly held board seats at competing artificial intelligence companies, specifically Databricks Inc. and Fivetran Inc. a16z co-founder Ben Horowitz sits on Databricks' board, while partner Martin Casado is a board member at Fivetran. Both companies are direct competitors in the business of collecting, organizing, and analyzing large-scale enterprise data. The investigation has run parallel to the DOJ's review of Fivetran's acquisition of a similar company, dbt Labs, which was completed last year and ultimately approved. A potential resolution could require the a16z partners to resign from one of the competing boards, a common remedy in similar cases during the Biden administration. The probe highlights the enforcement of a 1914 law against "interlocking directorates," where individuals or entities serve on the boards of rival firms. This case is notable as the alleged conflict involves multiple partners from the same firm, rather than a single individual. a16z, managing $90 billion in assets, is a major political donor and has significant influence in AI policy. The investigation's outcome remains uncertain, and the DOJ may ultimately take no action.

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Century-Old Interlocking Director Law Revived, a16z Faces Antitrust Investigation

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Token Economy Surges, Have Ordinary People Got a Slice of the Pie?

Token Frenzy: Is the Average Person Getting a Piece of the Pie? As AI adoption soars in China, daily Token consumption—the basic unit for AI text processing—has skyrocketed, exceeding 140 trillion. This "Token economy" is often measured like GDP, touted as a sign of progress. However, this metric primarily reflects supply-side activities: corporate investment, infrastructure scaling, and platform revenues. The crucial question of whether this growth translates into tangible benefits for ordinary citizens—higher wages, better jobs, improved public services, or increased leisure—remains largely unanswered. The article argues there's a fundamental mismatch. Policy, exemplified by subsidies in Beijing's Yizhuang district, often stimulates "demand" by incentivizing companies to consume more Tokens (an intermediate business cost), rather than by boosting household income or final consumer spending. This creates a closed loop where growth in Token usage justifies further production capacity expansion, without necessarily extending value to the broader population. Several disconnects are highlighted. High Token usage doesn't equal completed tasks, increased profits, or macroeconomic productivity gains. Even when corporate efficiency improves, the benefits may not trickle down due to existing economic structures favoring investment over household consumption. The risk is that AI, a genuinely productive technology, becomes another tool for supply-side expansion within a system adept at measuring output (like server capacity and call volumes) but less focused on distributing the gains widely. Drawing a parallel to Henry Ford's assembly line, the piece notes that Ford's revolution combined ruthless production efficiency with a social compact (higher wages, stability) that enabled mass consumption. Today's "Token economy" narrative enthusiastically champions the first part—process re-engineering and cost reduction—but lacks a credible mechanism for the second: ensuring that productivity gains lead to broader societal welfare. The ultimate challenge is not whether Tokens have value, but whether their economic benefits can escape a system that excels at building supply but struggles to cultivate its own demand.

marsbit29m ago

Token Economy Surges, Have Ordinary People Got a Slice of the Pie?

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Overnight Global Shock: Why Did AI Stocks Plunge Across the Board?

Overnight, U.S. AI-related stocks fell sharply, with the Nasdaq down 1.33% and the Philadelphia Semiconductor Index plunging nearly 5%. Panic spread globally, dragging down Asia-Pacific markets. Key negative drivers included: 1. **Geopolitical Tension & Macro Pressure:** Escalating U.S.-Iran tensions pushed oil prices higher, fueling inflation fears and expectations of prolonged high interest rates. Rising bond yields pressured high-valuation, capital-intensive AI stocks, especially as soaring AI infrastructure financing costs became evident. 2. **AI Commercialization Concerns:** OpenAI's Q2 results showed slowing revenue growth and widening losses, dampening market optimism about near-term AI application profitability. This shifted investor focus from pure capital expenditure narratives to actual commercial returns. 3. **Supply Chain Uncertainty:** U.S.-South Korea semiconductor investment disputes intensified. Market fears that Korean memory giants (Samsung, SK Hynix) face a dilemma—either divert capital to costly U.S. production or risk trade barriers—disrupted the critical HBM memory sector, amplifying sell-offs via leveraged ETFs. While long-term AI demand remains, the market is now scrutinizing real profitability, financing costs, and supply chain stability rather than paying premiums for unchecked growth stories. For markets like China's A-shares, the impact is primarily sentiment-driven, requiring distinction between short-term panic and fundamental deterioration.

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From 'Little Brain' to 'Big Brain': Unitree Robotics Raises 60 Billion Yuan in IPO, Focusing Efforts on Robot AI Models

Unitree Robotics plans to allocate approximately half of the funds raised from its IPO to the research and development of AI models for robots. AI will function similarly to the human cerebrum (perceiving surroundings and making decisions) and cerebellum (controlling complex movements and maintaining balance).

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Q2 Wall Street Institutional Crypto Holdings: Most Institutions Increased Positions Against the Trend, ETH Exposure Outperformed BTC Across the Board

In Q2 2024, despite a roughly 14.2% decline in Bitcoin's price, many Wall Street institutions increased their crypto holdings, revealing a divergence from ETF flow trends. Overall institutional Bitcoin exposure grew by 7.5% to ~536k BTC, while aggregate spot Bitcoin ETF holdings declined. Notably, exposure concentration increased, with fewer reporting institutions holding larger positions. A key trend was the significant outperformance of Ethereum (ETH) exposure growth over Bitcoin (BTC) among major banks. For instance, JPMorgan's ETH exposure surged 67.3% versus 12.2% for BTC, and Morgan Stanley's ETH exposure grew 18.6% versus 3.7%. Individual bank holdings of Ethereum ETFs like ETHA saw dramatic increases, even as the overall Ethereum ETF market experienced net outflows during the quarter. Trading firms like Jane Street significantly rebuilt its iShares Bitcoin Trust (IBIT) position, while several hedge funds, including Brevan Howard and Graham Capital, reduced spot ETF holdings but added substantial option positions (both calls and puts), indicating more complex strategies. Institutions showed diverging views on crypto-related equities: some sold shares of MicroStrategy (MSTR) after its announced Bitcoin sales, while others like Renaissance Technologies and BlackRock were buyers. New entrants like Spain's Santander Bank disclosed initial crypto ETF positions. Meanwhile, long-term holders like Abu Dhabi's sovereign wealth funds paused their accumulation, and Harvard's endowment maintained a flat Bitcoin position. Key signals include the deepening institutionalization of crypto assets, a clear institutional preference for accumulating Ethereum, and growing divergence in views on crypto equities. This institutional buying in Q2 preceded a price recovery and renewed inflows into Ethereum ETFs in July and August.

marsbit49m ago

Q2 Wall Street Institutional Crypto Holdings: Most Institutions Increased Positions Against the Trend, ETH Exposure Outperformed BTC Across the Board

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What is $BANK

Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalised services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalisation of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualisation of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasises these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalised Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.

404 Total ViewsPublished 2024.04.06Updated 2024.12.03

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