• Reflexivity now operates directly within social media. Markets react to collective expectations rather than objective facts. An interpretation gaining critical mass on platforms like X becomes a self-fulfilling reality, forcing institutional action and generating new data. • Traditional verification filters like editors and analysts have vanished. The gap between information and consequence has collapsed. Speed has defeated accuracy, as the first voiced interpretation sets the framework for all subsequent actions. • AI generates compelling, sophisticated analysis at an industrial scale, not just spam. Thousands of accounts can manufacture an illusion of independent consensus before facts are verified. Attention and credibility are now weaponized. • The strategic battle is no longer about acquiring facts first. It is about whose interpretation shapes collective expectations earliest. • The primary function of modern analytical tools is to answer a single critical question. They must determine if a narrative emerged organically or was artificially coordinated to manipulate markets and public opinion. • Because digital interpretations now carry tangible legal and market consequences, governments and regulators will increasingly attempt to strictly control these new layers of global coordination.

The reason is rooted in a major strategic business move. In 2026, SpaceX acquired Cursor, reportedly in a deal valued at $60 billion, to integrate advanced AI coding technologies into its SpaceXAI team and further develop the Grok model. Since Rishabh Yadav played a key role in building the technology at Cursor and transitioned to work on SpaceXAI projects following the acquisition, Elon Musk added him to his list of followed accounts. Musk is known for following only about 1,400 to 1,500 accounts, which primarily consist of key employees, partners, and individuals who directly impact his technological goals.

Schwarzman did not take Ma's words at face value. He leveraged his academic connections, specifically the head of MIT, to conduct technical due diligence. This is a classic best practice. Visionaries sell the future, but only deep technical experts can confirm that this future is physically and scientifically sound. The phrase "we invented AI at MIT" served as his trigger for action. By becoming the largest lessor to all six major hyperscalers (Amazon, Microsoft, Google, Meta, and others), Blackstone gained a unique macro perspective of the market. They can see where capacity is expanding, which regions are becoming bottlenecks, and where the industry is heading long before this data appears in public reports.

open source, open weights, can't lose @Melt_Dem

Behind this meaningful cultural gesture lies a serious strategy. Kazakhstan is ambitiously building its AI ecosystem, while NVIDIA gains a loyal partner in a key Eurasian region. The Order of Dostyk in exchange for technological vision represents an ideal mutually beneficial outcome cemented by mutual respect.

Everyone thinks Terafab is trying to build a 2nm foundry from scratch. They are wrong. The equipment they are actively sourcing (TC bonders, hydrogen annealing tools, test sockets) points to one specific target: Advanced Packaging. Musk knows building a leading edge fab is a decade long money pit. The real bottleneck for custom AI chips like Dojo is no longer the silicon substrate. It is 2.5D and 3D chiplet integration. Terafab is playing a much smarter game: 1. Buy base wafers from Intel or TSMC as a commodity. 2.Vertically control the final and most critical assembly phase in house. Do not build the whole stack. Just own the bottleneck. That is how you win at hardware.

The current situation within the artificial intelligence infrastructure lending market represents not a spontaneous collapse but rather an anticipated and managed response to direct signals from macroeconomic regulators. The Bank for International Settlements and national financial authorities have explicitly highlighted the necessity of stress testing banking portfolios associated with data centres, owing to well founded concerns regarding the formation of a localised bubble. Financial institutions are acting in advance by conducting internal audits and actively hedging their positions. It is absolutely crucial to distinguish between a systemic credit crisis, wherein liquidity vanishes across the entire economy, and a prudent reassessment of risk within a specific overheated segment. Capital is not evaporating from the technology sector; rather, it is ceasing to be inexpensive for projects lacking a transparent and demonstrable business model. In the long term, this dynamic merely fortifies the resilience of the financial system against technological shocks. The primary rationale for the sudden caution exhibited by creditors lies in a fundamental mismatch between traditional banking collateral models and the harsh realities of artificial intelligence infrastructure. Equipment designed for artificial intelligence, particularly graphics processing unit clusters, is subject to exceptionally rapid technological and physical obsolescence. Whereas in traditional real estate lending collateral retains or even appreciates in value over time, within the sphere of computing power the monetary value of hardware may plummet faster than the loan can be repaid, particularly against the backdrop of announcements concerning novel chip architectures. Banks are acutely aware of this risk of evaporating collateral value. Consequently, they are not ceasing to lend per se but are radically altering the terms of such financing. They are tightening financial covenants, demanding higher margins, and linking repayment schedules to genuine extended offtake agreements for computing capacity, rather than to the hypothetical future liquidation value of the physical assets.

1. Tomorrow I will march into my boss's office and ask for a triple advance on my "rapidly devaluing" salary. 2. With that money, I will buy a couple of acres of fertile land, a small nuclear power plant, a server rack, and a little Bitcoin for change. 3. I will become an "asset owner" and condescendingly watch everyone else cry in 2036. The only slight catch in this flawless logic is that you need money to buy assets. To get money, you need a job. But according to the author, jobs will soon become useless. Therefore, I propose a new life hack: paying for power plants and land with "exposure", "faith in a bright future", and three reposts of this post.

📊 SGI generated immense revenue from $50,000 workstations. When a product yields extraordinary profits, a company becomes psychologically and structurally incapable of cannibalizing its own business to build a $300 alternative. Management inevitably optimizes the current model rather than preparing for a paradigm shift. Founder Jim Clark thought in paradigms and technological shifts five to ten years ahead. Conversely, the hired CEO from HP thought in quarterly reports and risk mitigation. His directive to stop disrupting what is already working serves as the ultimate epitaph for hundreds of technological giants, including Kodak, Blockbuster, and Nokia. Clark’s prediction materialized with frightening accuracy. The computational power that required a $50,000 supercomputer to render dinosaurs in 1993 now fits onto a $300 graphics card or even a smartphone. Moore’s Law and economies of scale invariably defeat closed, expensive proprietary systems. The critical question remains: what works for your enterprise today but will be obsolete in five years? This demands a radical audit of your business models, core competencies, and infrastructure dependencies. The most effective defense against technological extinction is the readiness to disrupt your own comfortable model before the market forces you to do so. Nvidia did not defeat SGI by building superior premium workstations. It prevailed because it architected the future that SGI refused to acknowledge.

The divestment from US Treasury securities is a verified fact. China has been consistently and aggressively reducing its holdings of US government debt. By the middle of 2026, China's holdings of US bonds had dropped to approximately $618 billion. The share of Treasuries in China's total reserves has indeed plummeted compared to the peak levels of previous years. Gold reserves of the PBOC (People's Bank of China): China is accumulating gold at a massive pace. Official reserves reached 2,346 metric tons by the second quarter of 2026. At the same time, many analysts believe that China's actual unreported reserves could be significantly higher, potentially already exceeding the 5,000 metric ton mark. Gold surpassing the dollar as a reserve asset: During 2025 and 2026, leading financial publications and the World Gold Council released reports indicating that, by total value, gold held in global central bank reserves had surpassed US Treasury securities. It is worth noting that in September 2026, the US Federal Reserve issued a research note attempting to challenge this framing and point out nuances in the calculation methodology. Nevertheless, the broader trend of dedollarization remains undeniable.