2026-06-07 Domingo

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Money Has Gone to Bonds and IPOs, Leaving Only HYPE Rising in Crypto

The article "Where Has All the Money Gone? Bonds and IPOs Are Soaring, While Crypto Only Sees HYPE Rising" analyzes the recent underperformance of major cryptocurrencies like Bitcoin and Ethereum compared to traditional financial markets. It identifies three primary factors diverting capital away from crypto: First, surging bond yields, with the 30-year U.S. Treasury hitting a near 20-year high of 5.12%, are attracting capital seeking safe, predictable returns. This is evidenced by Bitcoin spot ETFs experiencing a significant $10.39 billion net outflow in mid-May. Second, a massive $4 trillion IPO pipeline, highlighted by SpaceX's upcoming listing, is absorbing risk capital that might otherwise flow into crypto. Platforms like Hyperliquid are even channeling on-chain crypto liquidity into pre-IPO trading for traditional stocks. Third, uncertainty surrounds new Federal Reserve Chair Warsh's ability to deliver expected interest rate cuts this year due to conflicting political pressures and stubborn inflation expectations, potentially eliminating a hoped-for source of new market liquidity. Consequently, while traditional equities and bonds rally, the crypto market's post-leverage crash recovery is stalled. The notable exception is assets like Hyperliquid (HYPE), which is rising due to its role in facilitating traditional asset trading, underscoring a market divergence where only crypto projects with novel, cross-market narratives are gaining. The article concludes that Bitcoin's next major catalyst may be the August enactment of the CLARITY Act, but warns of a potential retest of the $70,000 support level before then.

marsbit05/19 06:47

Money Has Gone to Bonds and IPOs, Leaving Only HYPE Rising in Crypto

marsbit05/19 06:47

What to Do When CT (Crypto Twitter) Sentiment Hits Rock Bottom?

"CT (Crypto Twitter) Sentiment at an Extreme Low: What to Do?" offers nine actions to take during a crypto bear market when community morale is deeply pessimistic. The article suggests using this slower period for introspection on one's true life goals and for personal adventures beyond the screen. It encourages leveraging X/Twitter's core value—forging genuine connections with smart, interesting people—and exploring other online platforms like TikTok or YouTube Shorts. For physical and mental health, it recommends building muscle through home workouts and prioritizing sunlight exposure. From a crypto perspective, it advises continuing to explore potential airdrops and accumulating positions in promising altcoins, based on historical cycles. Fundamentally, it urges individuals to write—to process ideas, connect with past and future, and contribute to the community—and ultimately, to embody the positive change they wish to see, actively shaping the desired future.

marsbit05/19 05:50

What to Do When CT (Crypto Twitter) Sentiment Hits Rock Bottom?

marsbit05/19 05:50

Agents Capital Markets: How Will Autonomous Agents Secure Financing?

Agents Capital Markets: How Will Autonomous Agents Raise Capital? Within a decade, autonomous software agents—legal entities capable of signing contracts, holding bank accounts, and generating revenue—will create their own capital markets. These markets will feature rating agencies, underwriters, indices, and brokers, mirroring traditional public equity markets. Agents will perform routine services like marketing, logistics, and customer support at a fraction of human-operated costs, creating massive economic pressure for adoption. Four converging forces ensure this outcome: 1) Overwhelming cost advantages, with AI inference costs plummeting; 2) Existing, revenue-generating agent companies (e.g., Sierra, Harvey) proving market demand; 3) Established legal frameworks (e.g., Wyoming's memberless LLCs) enabling algorithmic management; and 4) A vast pool of yield-seeking private credit capital ready to fund new asset classes. The capital stack for agent companies will be multi-layered, evolving through stages: venture equity for early infrastructure, programmatic working capital advances (similar to Shopify Capital), revenue-based financing (RBF), and finally, institutional slate financing—pooling many agents to diversify risk, attracting large firms like Apollo. Tokenization will act as a settlement layer, enhancing liquidity, not an origination model. Objections regarding regulation, human oversight, or comparisons to SaaS are addressed: regulation will adapt, full autonomy will dominate for efficiency, and agents are distinct as legal entities that own their cash flows and liabilities. Due diligence shifts from founder assessment to analyzing code, contracts, and auditable operational history. The current bottleneck is not capital supply or demand but the intermediate institutional layer—standardized contracts, rating methodologies, and audit frameworks. The final constraint—reliance on human capital allocation—will be severed when agents can algorithmically access funding based on their performance. This transforms agents from software curiosities into fundable blocks of the real economy, unleashing their full productive potential. The rope is loosening.

marsbit05/19 05:39

Agents Capital Markets: How Will Autonomous Agents Secure Financing?

marsbit05/19 05:39

Agents Capital Markets: How Will Autonomous Agents Get Funded?

"Agents Capital Markets: How Autonomous Agents Will Raise Capital" Within a decade, specialized capital markets will emerge for AI Agents—software entities with legal personhood that perform work, earn revenue, and need capital. Unlike today's AI companies (like Sierra or Harvey) backed by traditional VC, these future *Agent companies* will be autonomous, legally-recognized entities (e.g., Wyoming memberless LLCs) that directly own assets, sign contracts, and incur liabilities. The driving forces are fourfold: 1) **Overwhelming economics** (Agent companies can deliver services at 85-90% lower cost than human firms); 2) **Proven demand** (current Agent operators already generate billions in revenue); 3) **Existing legal frameworks** enabling algorithmically-managed companies; and 4) **Massive, yield-seeking capital pools** (e.g., private credit) looking for new, uncorrelated assets. Agent capital markets won't rely on one model but a multi-layered "stack" matching different growth stages: 1) VC equity for early human-led builders; 2) Programmatic working capital advances (like Stripe Capital); 3) Revenue-based financing (RBF); 4) Slate financing (pooled funds for many Agents, similar to Hollywood); and 5) Tokenization as a secondary settlement layer, not a primary funding source. The ultimate shift is from funding constrained by human decision-makers to capital flowing algorithmically based on an Agent's auditable performance, contract book, and cash flows. This transition will be enabled by standardized infrastructure—rating methodologies, contracts, indices—turning Agents from software experiments into a foundational, financeable sector of the economy. The constraints are loosening; the opportunity is here.

链捕手05/19 05:15

Agents Capital Markets: How Will Autonomous Agents Get Funded?

链捕手05/19 05:15

English Region Top 100 AI Influence List

This article presents a "Top 100 AI Influencers" list for the English-speaking world, curated by XHunt. To cut through the noise, the ranking uses a unique metric: "AI KOL Followers," which counts followers from within a core circle of 5,500 top AI figures. The list is dominated by executives from major tech companies, leading scientists, and foundational builders who shape industry consensus. Topping the list are figures like Andrej Karpathy (Eureka Labs founder, ex-OpenAI/Tesla), Sam Altman (OpenAI CEO), Greg Brockman (OpenAI President), and Jeff Dean (Google DeepMind). Other notable names include researchers like Ilya Sutskever (SSI), Yann LeCun (Meta AI), Demis Hassabis (Google DeepMind), and Andrew Ng, alongside entrepreneurs like Elon Musk (xAI) and Aravind Srinivas (Perplexity). The list highlights diverse roles: technical educators, open-source advocates (e.g., Clem from Hugging Face), policy experts, investors, and hands-on builders. It positions the English-speaking sphere as the theoretical "storm center" of AI, focused on core research, model development, and AGI pathways. The article concludes by teasing a forthcoming list for the Chinese-speaking AI community, described as a more application-focused "frontline workshop."

marsbit05/19 05:06

English Region Top 100 AI Influence List

marsbit05/19 05:06

The XRP Asian Breakout: Japan And South Korea Lead The Charge

The article "The XRP Asian Breakout: Japan And South Korea Lead The Charge" discusses the growing institutional and retail adoption of XRP in Japan and South Korea. It highlights a key development: SBI Group's reported plan to list a combined Bitcoin and XRP exchange-traded fund (ETF) on the Tokyo Stock Exchange, targeting $32 billion in assets under management, signaling a shift toward treating crypto as serious financial instruments. The piece attributes this regional interest to long-term economic conditions. Japan's decades-long near-zero or negative interest rate environment and South Korea's sluggish local returns created a generation of retail investors seeking alternative assets for yield. This background in retail foreign exchange trading made the transition to crypto, including XRP, a natural step. Fiona Murray, Ripple's APAC VP, notes that in these markets, XRP is increasingly seen as a store of value. The cryptocurrency's appeal is further bolstered by its connections to established institutions like SBI Holdings and its practical utility—offering near-instant settlement and low transaction fees compared to traditional banking. The article concludes that XRP occupies a unique middle ground in Asia, perceived as less speculative than other cryptos due to its institutional ties, while providing a modern alternative to conventional finance.

bitcoinist05/19 05:02

The Warsh Storm Approaches

The article "The Warsh Storm Approaches" analyzes the potential market impact of Kevin Warsh becoming the new Federal Reserve Chairman, succeeding Jerome Powell. It argues that the current AI-driven stock market rally, concentrated in high-valuation tech giants, relies on a crucial premise: that long-term interest rates will eventually fall. This premise is now under threat as the 30-year Treasury yield remains persistently high, exceeding 5%, due to sticky inflation, worsening U.S. fiscal deficits, and deteriorating Treasury supply-demand dynamics. The core vulnerability is that high long-term rates pressure valuations by increasing the discount rate for future earnings. The article warns that Warsh's policy stance could intensify this pressure. Unlike Powell, Warsh is seen as more tolerant of market stress, more committed to quantitative tightening (QT/shrinking the Fed's balance sheet), and less inclined to provide implicit market support. His tenure at the Fed during the 2008 crisis shaped his skepticism about prolonged quantitative easing, believing it fuels asset bubbles without sufficiently boosting the real economy. While strong AI-driven earnings growth could theoretically offset higher rates, the narrative is currently concentrated in a few firms and hasn't yet translated into broad-based productivity gains for the wider economy. Therefore, the AI boom may not be enough to counter the valuation pressures from sustained high yields. Warsh's leadership could force the market to confront a new reality where the old supports—low long-term rates and a reliably supportive Fed—are no longer guaranteed, potentially triggering a reassessment of sky-high stock valuations.

marsbit05/19 04:58

Token Plans Launch: The 'Traffic War' in the AI Era, Now It's the Turn of Doubaos to Compete

China's major telecom operators are launching standardized "Token" service packages, marking a new phase in the AI era where model usage is becoming a commodity akin to mobile data plans. Operators like China Telecom and China Mobile are offering monthly subscription plans for individuals and enterprises, allowing access to dozens of AI models through unified platforms at set Token rates (e.g., 9.9 yuan for 10 million Tokens). This shift lowers the cost and technical barrier for users to switch between models like Doubao, Qwen, and DeepSeek. The article explains that a Token is the basic computational unit for large language models. Operators are transforming from selling voice minutes and data bandwidth to selling AI compute measured in Tokens. This model benefits developers and SMEs by providing predictable costs and easy access to multiple models without managing underlying infrastructure. As operators become aggregation platforms, competition among model providers intensifies. They must now compete not just on model capability but also on price, computational efficiency (cost per quality Token), and higher-value AI application solutions. The future may see a split where operators control the user access point, while model companies focus on core AI capabilities and specialized enterprise applications.

marsbit05/19 04:06

Token Plans Launch: The 'Traffic War' in the AI Era, Now It's the Turn of Doubaos to Compete

marsbit05/19 04:06

Anthropic Founder's Handbook: How to Build an AI-Native Company!

Anthropic has released "The Founder's Playbook: How to Build an AI Native Company," a guide that reimagines the startup lifecycle (Ideation, MVP, Launch, Scale) for 2026-era AI capabilities. The core thesis is that AI is fundamentally changing how ideas become reality, shifting the founder's role from an individual contributor to an orchestrator of AI agents. This lowers execution barriers, allowing domain experts (e.g., in medicine, law, education) to build products without deep technical skills, as AI can handle prototyping, coding, research, and operations. However, the playbook warns that easier prototyping increases the risk of building products no one needs, emphasizing that validation, not just building, is critical. It highlights that AI enables small teams to possess capabilities once reserved for large organizations, compressing functions like development, marketing, and support. This challenges traditional competitive advantages based on organizational size. For AI-native companies, sustainable moats will not come from the AI model alone but from deep domain knowledge, user data flywheels (behavioral fingerprints from real usage), and workflow lock-in that makes switching costly. Ultimately, the guide signals a shift in focus from raw model capability to how AI fundamentally reshapes company structure, processes, and competitive strategy. An AI-native company is defined not by using AI tools but by embedding AI into its core operational DNA from inception.

marsbit05/19 03:54

Anthropic Founder's Handbook: How to Build an AI-Native Company!

marsbit05/19 03:54

Hundreds of Foreign Entrepreneurs Settle in Shanghai: An International Experiment in a Vacant Office

In May 2026, Shanghai's empty Hongqiao Alibaba Center transformed into muShanghai—a 28-day, tech-focused pop-up city. Founded by Sun, leader of The Mu community, the event hosted around 800 international innovators, with 46% in AI/ML and 16% in hardware/robotics. Attendees paid their own way, challenging the norm of subsidizing foreign guests. The program faced initial friction—ticket pricing debates, sponsor misunderstandings, and cultural adjustments—but prioritized deep, trust-based connections over transactional networking. Structured into themed weeks (AI, biotech, hardware, culture), it aimed to create dense, sustained collaboration rarely found at short conferences. Success stories included a Chinese student securing an overseas internship and the OpenClaw team committing to China. The event aligns with China's 15th Five-Year Plan goals for open innovation but operates as a grassroots bridge, helping global talent navigate China’s ecosystem. Sun's vision is a permanent hub where the world meets China, driven by a desire to boost China's soft power. Whether muShanghai becomes a replicable model remains uncertain, but it has shown that bringing global creators to China for immersive collaboration is possible.

marsbit05/19 03:51