Bitcoin Bonds Explained: The Key Driver to Bitcoin Price in the Post-Era of Trump’s Tariffs

TheNewsCryptoОпубликовано 2025-04-11Обновлено 2025-04-11

Bitcoin (BTC) Nears $87K: Will Strong Demand Propel It Further? Bitcoin News

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Gold, Fiat, or Bitcoin: Which Will Dominate Global Finance in 10 Years?

In an increasingly multipolar world moving away from the post-1991 unipolar era dominated by the US dollar, the global monetary system is shifting towards multipolarity. Gold remains a key non-sovereign store of value due to its size, liquidity, and immunity from devaluation or seizure. Diversification into multiple fiat currencies is a practical but inefficient option. Bitcoin presents a novel, decentralized, and fast-settling digital ledger, though its widespread adoption faces challenges of security, network effects, and volatility. Its success depends on whether individuals value financial sovereignty enough to overcome adoption barriers. By 2036, gold and major fiat currencies will likely remain significant, but Bitcoin has the potential to rival their scale if it maintains security and gains broader acceptance for its unique attributes of self-custody and permissionless transactions.

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Consumer Confidence Hits Bottom, Macro Correlations Simultaneously Break Down: How Much Longer Can the U.S. Stock Market's Solo Rally Last?

The U.S. stock market is exhibiting a rare divergence: while consumer confidence hits historic lows and traditional macro asset correlations break down, major indices like the Nasdaq 100 and S&P 500 continue reaching record highs, fueled primarily by AI and semiconductor momentum. The rally is now highly concentrated, with strength rotating from giants like Nvidia to higher-beta plays within semiconductors, particularly memory chips. This surge occurs despite a significant split between pessimistic consumer sentiment and still-resilient actual spending behavior, partially supported by fiscal stimulus. Goldman Sachs traders highlight a critical structural fissure: correlations between the S&P 500 and key macro assets (rates, gold, VIX, oil) have deviated extremely from long-term historical norms. Concurrently, the market is in a negative Gamma regime, making it more sensitive to price moves, and hedge fund positioning in momentum and semiconductors is at crowded levels. The sustainability of this "solo rally" faces three main constraints: 1) Oil price volatility linked to Middle East geopolitical risks, 2) Extreme crowding in semiconductor and momentum trades, increasing vulnerability to disappointments, and 3) The breakdown of traditional macro correlations, suggesting the rally reflects a specific mix of factors rather than broad-based risk appetite. The key question is not if indices can rise further, but which variable—oil, rates, or semiconductor momentum—might trigger a repricing of the current fragile logic.

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Consumer Confidence Hits Bottom, Macro Correlations Simultaneously Break Down: How Much Longer Can the U.S. Stock Market's Solo Rally Last?

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Lost the 75,000 Mark, Is Bitcoin About to Experience Its Final Drop?

Bitcoin fell below the $75,000 support level on May 28th, trading near $74k amid a broader market correction. Major altcoins like ETH, NEAR, WLD, and ONDO also declined, with the market fear index dropping to 34. Over $470 million in liquidations occurred in 24 hours, mostly long positions. The downturn is linked to external pressures. Geopolitical tensions flared as the US conducted new strikes on an Iranian military base, impacting risk assets. Simultaneously, US spot Bitcoin ETFs shifted to consistent net outflows in May, indicating institutional profit-taking, with funds potentially rotating into outperforming AI and tech stocks. Analysts note BTC's long-term fundamentals remain sound. However, short-term price action depends on capital flows, which are currently negative. Key support is identified between $75k-$76k; a break below could lead to a test of $70k-$72k. On-chain data suggests short-term trading activity has plummeted to levels typical of bear market bottoms, signaling either a bottoming phase or a potential final decline before a reversal. Experts advise a diversified strategy as Bitcoin appears to be in a bottoming area.

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Will OpenAI Swallow the Application Layer? a16z Says Real Opportunities Lie Outside General Models

As large language models (LLMs) from companies like OpenAI and Anthropic become more powerful, many fear they will dominate the AI application layer, leaving no room for startups. However, this article argues that the real opportunity lies not on the "Yellow Brick Road"—the high-profile, general-purpose tasks like code and text generation that model labs are directly pursuing—but in the "rest of Oz": complex, vertical-specific applications. On the Yellow Brick Road, model companies have inherent advantages: control over the model, better margins, pricing power, and strong distribution. Startups building generic, horizontal "co-pilot" tools for standard tasks are competing directly on this path and are vulnerable. True defensibility and value are found in specialized, vertical applications. These involve deep integration into messy, multi-step business workflows (e.g., sales, insurance, legal), handling legacy systems, data quality issues, compliance, and governance. The "scaffolding" around the model—the specialized tools, automations, workflows, and industry knowledge—becomes more critical than the raw model power itself. Vertical AI companies can build defensible moats through: * **Data & Learning Flywheels:** Capturing unwritten industry practices and specific customer feedback not found in public training data. * **Managing Model Complexity:** Routinely evaluating and routing queries across multiple models (including open-source) to optimize for performance and cost, and absorbing the migration burden of model upgrades for clients. * **Cost Optimization:** Using cheaper, fine-tuned models for specific sub-tasks instead of always calling the most expensive, general-purpose model. * **Governance & Compliance:** Providing the control plane for permissions, auditing, and ensuring compliance with industry-specific regulations (e.g., HIPAA, FINRA). Examples from sales (11x) and insurance (FurtherAI) illustrate that clients pay for systems that drive specific business outcomes (e.g., sales pipeline, policy underwriting), not for generic intelligence. These systems become the "operational memory" of a business, a layer that is hard to replace, even as the underlying LLMs commoditize and improve. To test if a startup is building in the "rest of Oz," it should pass checks like the **Tool & Steps Test** (requires complex, multi-step workflows), the **System Test** (owns the end-to-end workflow, not just a tool on top), and the **Hedge Fund / P&L Test** (measured by client business outcomes, not benchmark scores). Both model labs and vertical application companies will win. The next generation of enterprise software will be built in the specialized, complex, and high-value territory beyond the Yellow Brick Road.

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'ASIC Giant' Marvell Sets Record Quarterly Revenue, Raises Guidance Again, CEO Says Data Center Business Is 'On Fire'

Marvell Technology, a leading player in custom AI chips and data center connectivity, reported record revenue for its fiscal Q1 2027, driven by explosive demand in its data center business. Revenue reached $2.418 billion, slightly surpassing expectations, though GAAP net income fell year-over-year due to acquisition-related costs. Crucially, data center revenue hit $1.83 billion, making up 76% of the total and growing 27% YoY. The company significantly raised its full-year and next-year guidance, citing "exceptionally strong AI-related orders." Revenue is now projected at ~$11.5 billion for FY2027 and ~$16.5 billion for FY2028. CEO Matt Murphy emphasized that growth in the data center segment is accelerating. The AI Interconnect business, now expected to grow over 70% annually, saw its forecast lifted again due to rising network demands in complex AI models. Additionally, Marvell's custom chip (XPU) business is on a steep growth path, with FY2028 revenue anticipated to double and a target of over $10 billion by FY2029. The company also expanded its strategic collaboration with NVIDIA, focusing on silicon photonics, system integration, and AI-RAN solutions. To secure supply for surging demand, Marvell plans about $1 billion in supplier prepayments this fiscal year, highlighting its long-term capacity planning. Despite the strong results, the stock dipped slightly in after-hours trading.

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