Metrics Ventures Market Watch: The Brewing Storm

marsbitОпубліковано о 2026-05-26Востаннє оновлено о 2026-05-26

Анотація

In the past month, the market has been actively trading contrasting expectations, balancing global supply chain disruptions fueling re-inflation against both actual and anticipated (Walsh) interest rate hikes. This volatility has impacted commodities and most equities, though tech has temporarily benefited from concentrated short-term liquidity. Fundamentally, as previously analyzed regarding the Strait of Hormuz situation, the US faces deep-seated balance sheet issues beyond what any single Fed chair can resolve. Hypotheses around a figure like Walsh could only materialize if AI fundamentally reshapes production relations. Until then, most non-AI-leading nations (effectively all except the US and China) risk fiscal and monetary policy collapse, rendering the identity of the Fed chair ultimately irrelevant. For crypto assets, there is currently no clear role in these dominant narratives. The market remains strongly capped by the 200-day moving average. While trends may shift from "anything but AI" to "anything but mines," this phase is dominated by the silicon vs. carbon (AI vs. traditional) dichotomy, leaving little room for crypto—though its time will come. **Market Overview & Commentary** The crypto market lacks significant catalysts beyond hype, plagued by low volume and scarce innovation, with clear technical resistance. Currently, crypto struggles for attention as global focus lies elsewhere. Assets like gold, oil, and grains are more direct hedges against supply-cha...

1/ Over the past month, the market has been fervently trading expectations, on the one hand betting on re-inflation from damaged global supply chains, and on the other hand trading rate hikes, whether based on factual developments or on expectations surrounding Vice Chair for Supervision nominee Wash. These two forces are like fire and ice, causing commodities and most equity assets to fluctuate constantly. However, technology, which is actually impacted by both, still benefits from the concentration of short-term liquidity.

2/ On a factual level, as we previously analyzed regarding the Strait of Hormuz situation, the chronic issues with the US's bloated balance sheet have exceeded the scope of what any single Federal Reserve Chair can resolve. All of Wash's hypothetical scenarios could only become reality when AI fundamentally alters social production relations. Until that day arrives, the majority of non-AI-leading nations worldwide (almost all except China and the US) will be the first to fall into a collapse of fiscal and monetary policies. By then, who sits as the Fed Chair will no longer be of great importance.

3/ From a trading perspective, crypto assets currently see little possibility within all the narratives mentioned above. We also observe that the 200-day moving average continues to strongly suppress the price trends of these assets. Even if the "anything but AI" sentiment spreads to "anything but mines," it's unlikely to change this situation. In this current phase of silicon-based versus carbon-based competition, there is no stage for crypto, but there certainly will be in the future. Rest assured.

Review and Commentary on Overall Market Conditions and Trends

Aside from hype, there isn't much noteworthy to discuss in the crypto market. The lackluster trading volume and scarcity of innovation are old news, and technical resistance is very evident. In fact, crypto assets could potentially be good tools for hedging against global liquidity risks. At this moment, it's difficult for any major market focus to directly link to crypto. Meanwhile, inflation/stagflation caused by supply chain damage clearly has more definitive large-capacity investment targets like gold and other metals, petrochemicals, and food. Looking at token distribution, Bitcoin also needs more time to consolidate and absorb selling pressure. The development of this variable is crucial. We expect this correction to persist until at least Q4 2026.

Looking ahead, we believe three events will successively become the dominant drivers of future market volatility:

1. In the short term, the market will highly focus on whether Wash will repeat the missteps of Besant or Musk, turning his stance into the next "333" plan.

2. The market is significantly underestimating the severity of substantial damage to a large number of global supply chains and the time needed for future repair. In the medium term, the market will eventually realize that local resource shortages and price volatility will far exceed initial expectations, similar to the situation during the pandemic.

3. Nations like the UK and Japan, which represent "AI non-beneficiaries + inflation first to fall," will successively face severe fiscal and monetary policy crises. We should hope that AI substitution does not occur too rapidly; otherwise, the existing credit system and national welfare fiscal systems could collapse swiftly.

One day, the market may understand that the bursting of the AI bubble could trigger a contagious credit crisis for some sovereign nations. The monetary and fiscal responses at that time might be the ultimate ignition for Bitcoin's final major bull run.

Пов'язані питання

QAccording to the article, what are the two opposing forces causing volatility in commodity and equity markets over the past month?

AThe article states that markets have been trading on two opposing expectations: the re-inflation due to damaged global supply chains, and interest rate hikes, whether they are actual hikes or expectations stemming from Warsh. These two forces, likened to ice and fire, are causing significant volatility.

QWhat does the article suggest is the primary narrative or factor benefiting from current short-term liquidity concentration, despite the broader market volatility?

AThe article indicates that technology, specifically AI-related sectors, is benefiting from the concentration of short-term liquidity, even as it is simultaneously impacted by the opposing forces of supply-chain-driven re-inflation and interest rate hike expectations.

QWhat condition does the article claim must be met for all of Warsh's monetary policy assumptions to hold true, and what are the predicted consequences for most non-AI leading nations before that point?

AThe article claims that all of Warsh's assumptions can only hold true when AI fundamentally changes societal production relations. Before that day arrives, the majority of non-AI leading nations (almost all except China and the US) are predicted to fall into a collapse of fiscal and monetary policies.

QWhat is the article's main assessment of the current state of the cryptocurrency market in relation to broader global economic narratives?

AThe article's main assessment is that cryptocurrency assets currently see little possibility within the dominant global economic narratives. It notes low trading volume, a lack of innovation, clear technical resistance (like the 200-day moving average), and that market attention is focused elsewhere, such as on commodities like gold, oil, and grain as inflation hedges.

QWhat does the article identify as the potential catalyst for a future major bull run in Bitcoin?

AThe article suggests that a future contagion of sovereign credit crises, potentially triggered by an AI bubble burst, and the subsequent monetary and fiscal policy responses from governments could serve as the ultimate ignition for Bitcoin's next major bull run.

Пов'язані матеріали

After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

The stock price of Marvell Technology surged 32.5% on June 2nd, driven by NVIDIA CEO Jensen Huang highlighting its custom ASICs and optical interconnects as core to AI data center architecture. This event brought attention to the Chinese semiconductor family behind Marvell: the Dai siblings. The story centers on three siblings, all UC Berkeley graduates, whose three-decade entrepreneurial journey aligns with major semiconductor industry shifts. In 1995, youngest sister Dai Wei Li co-founded Marvell with her husband Sehat Sutardja and his brother, focusing on storage controllers. Eldest brother Dai Wei Min founded EDA company Ultima, later sold to Cadence, and later founded VeriSilicon (芯原) in China, becoming a leading semiconductor IP provider. Second brother Dai Wei Jin co-founded EDA firm Silicon Perspective (sold to Cadence) and GPU IP company Vivante, later acquired by VeriSilicon. The combined "Dai-Sutardja" family network extends beyond Marvell. Their ventures and investments form a comprehensive ecosystem for the post-Moore's Law, chiplet era. Key holdings include: Dream Big Semiconductor (AI SuperNICs, acquired by Arm), Alphawave (high-speed SerDes IP, acquired by Qualcomm), and Silicon Box (a chiplet advanced packaging foundry). VeriSilicon itself thrives on the AI ASIC and IP boom in China. Collectively, the family's AI infrastructure-related portfolio is estimated at over $22 billion. Their strategy represents a distinct path: building critical components for open standards and key manufacturing capacity in the chiplet era, rather than pursuing standalone AI chip dominance. While this path may not create the next NVIDIA, it has enabled repeated successful exits and sustained influence within the global semiconductor industry.

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Microsoft is Afraid of Being Marginalized by AI Giants

Microsoft, once the defining force of the PC era, now faces a familiar challenge in the AI age: the risk of being relegated to a profitable but invisible infrastructure provider. This anxiety was laid bare at Build 2026, where CEO Satya Nadella unveiled a major strategic pivot. The catalyst was a quiet April agreement that dissolved Microsoft's exclusive licensing and cloud-hosting deal with OpenAI, its once-vital partner. This erased Microsoft's key AI moat. With OpenAI and Anthropic defining AI applications and gaining enterprise traction—even within Microsoft's own ranks—Nadella had to answer: without exclusivity, what is Microsoft's role? The answer was a suite of seven in-house AI models, a developer-focused AI workstation (Surface RTX Spark Dev Box), and, most crucially, the Agent 365 platform for enterprise AI governance. The models, notably targeting Anthropic's strengths in coding and enterprise, signal a defensive move. However, the broader strategy is to make the models themselves less decisive. Financially, Microsoft's AI revenue is strong, driven largely by Azure running others' models. Yet its user-facing products like Copilot show weak penetration and engagement. Microsoft earns infrastructure money but lacks direct user mindshare. Nadella's core fear is being "hollowed out." As OpenAI and Anthropic prepare for IPOs and gain financial independence, they may build their own infrastructure, threatening Azure's lucrative AI revenue stream. Microsoft's window is to entrench itself deeper: not as the model creator, but as the indispensable platform for securely deploying, managing, and governing all AI models within the enterprise through Agent 365. Build 2026 revealed Microsoft's bet: in the AI era, the ultimate power lies not in any single model, but in the enterprise "operating system" that controls them. Nadella is determined to ensure Microsoft is the driver of this new era, not just a passenger.

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CPU, Quietly Returning to the Center of the AI Computing Power Stage

Over the past three years, AI computing power narratives have been dominated by GPUs. However, starting in 2026, this story began to shift. While training large models remains GPU-intensive, the rapid growth of inference and AI agent workloads, which require high levels of task orchestration, concurrency, and data flow management, has highlighted a renewed critical role for CPUs. These are tasks GPUs are not designed to handle. Intel's recent launch of the Xeon 6+ processor, built on its Intel 18A process and featuring up to 288 efficiency cores (E-cores), exemplifies this strategic pivot. It is positioned not as a mere companion to GPUs but as the essential "control plane" for AI infrastructure, optimized for high-density, energy-efficient, and high-throughput workloads characteristic of AI agents and inference. This "CPU resurgence" is not about CPUs outperforming GPUs in raw computation. It reflects a systemic bottleneck: as AI scales from training single models to deploying countless intelligent agents, the demand for coordination and data handling surges. Major cloud providers are also developing their own high-density ARM-based server CPUs for similar workloads. However, Intel's success with this strategy faces significant challenges. Competition includes NVIDIA's integrated CPU-GPU solutions, the expanding adoption of cloud vendors' in-house ARM CPUs, and the crucial market test of Intel's 18A manufacturing process against rivals like TSMC's N2. In conclusion, CPUs are indeed reclaiming a central, though redefined, role in AI compute—managing the complex orchestration that enables massive-scale AI deployment. While the trend is clear, which company will ultimately lead this CPU resurgence remains an open question to be decided in the data centers of 2027 and beyond.

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