On September 10, 2026, several seemingly unrelated news items emerged almost within the same time window: Nasdaq invested in the parent company of the cryptocurrency exchange Kraken, Payward, at an estimated valuation of about $21 billion; Xiaomi announced the full open-source release of the embodiment world model training framework and model weights for two sizes, 4B and 34B; meanwhile, across the ocean, it was revealed that the U.S. AI Safety Bill "may be submitted to Congress as early as next week," while the White House was still wavering on the issue of refined copper tariffs. On the capital front, important indices of traditional financial markets and the operators of trading platforms are reaching into cryptocurrency trading infrastructure; on the technology front, world models related to robotics and embodied intelligence research are being actively incorporated into the global open-source trend; on the policy front, the U.S. is repeatedly weighing security, costs, and industrial competition in AI safety legislation and tariffs on refined copper, a key raw material for electrical equipment, robotics, data centers, etc. The nearly simultaneous occurrence of these events reflects a common thread: traditional capital is accelerating its influx into crypto, the tech camp is betting on the diffusion of open-source, and U.S. policies are hesitating between safety, costs, and industrial competition. This article will observe the power dynamics and competitive directions in the current landscape along the intertwined narratives of capital, technology, and policy.
Nasdaq Bets on Kraken: Wall Street Opens the Door to Crypto
In the dramatic changes on the capital front, the most tangible piece of the puzzle is Nasdaq stepping directly into the core assets of cryptocurrency exchanges. According to market news, Nasdaq acquired a stake in Kraken's parent company Payward at an estimated valuation of around $21 billion, though specific investment amounts and equity percentages were not disclosed. This valuation itself is a signal: in a period of regulatory uncertainty and undefined policies, leading Wall Street exchanges are still willing to price crypto trading infrastructure close to that of top tech stocks, betting on its long-term value. Unlike past collaborations that maintained a "safe distance" over market data and custody services, this time they are appearing directly on the shareholder list, putting their brand and balance sheet on the line for a global cryptocurrency trading platform.
The direct expectation of traditional exchanges entering this space is compliance and image enhancement. Nasdaq's admission review, internal control processes, and reputation constraints will be viewed by institutional investors as a layer of "external due diligence." In a time of ambiguous regulatory attitudes, Kraken can use this to convey a message to banks, funds, and large corporate clients: this is an infrastructure carrier recognized by traditional financial giants, rather than a mere experimental product of the tech fringe. Naturally, the market will associate this with business expansion, with the expected direction being more institutional clients, higher compliance thresholds, and more complex product structures. However, until the terms are disclosed, any details regarding control arrangements, future business bindings, or exit pathways remain conjecture beyond the information boundary. A more cautious interpretation of this transaction is to first acknowledge its symbolic significance—the ownership proportion of traditional finance in crypto infrastructure is increasing—then await further disclosures and regulatory feedback to verify whether this symbolism can translate into concrete, measurable results in institutional entry and business data.
AI Safety Bill in Limbo: Technological Rush vs. Slow Regulation
While Nasdaq has placed its bet on crypto trading infrastructure at an estimated valuation of $21 billion, actions along another technological storyline in the U.S. have noticeably lagged behind. Citing reports from Semafor, the U.S. AI Safety Bill is still at the stage of being "possibly submitted to Congress as early as next week," with not even a formal text revealed, let alone details of any terms, sponsorship lineup, or paths to passage in both chambers. Regulators have recognized the need to set safety boundaries for AI, but the legislative process is still in its infancy, and this early stage of advancement itself is a signal of uncertainty.
From existing policy discussion experiences, it can be almost certain that AI safety legislation will unfold around several high-pressure points: categorization and assessment of high-risk models, special regulation for critical application scenarios such as finance, healthcare, and defense, and liability attribution when accidents, biases, or misuse occur. This means that model development, testing, and deployment will have to reserve more budget and time for compliance, and capital investment in large models and embodied intelligence must factor potential regulatory red lines into long-term return models. Especially in the U.S., a major global hub for AI R&D, once the safety bill takes shape, its spillover effects on the open-source ecology, cross-border cooperation, and computational facilities investment will likely extend beyond domestic boundaries.
In stark contrast, financial capital, represented by Nasdaq, has not waited for a "globally unified compliance framework" to mature in the crypto space, instead positioning itself at the infrastructure level first, and then adjusting risk exposure as regulation evolves. While crypto and AI are evolving technically, they share the same theme in their temporal sequence: capital and technology are running ahead, with policy lagging behind. The picture in the fall of 2026 thus becomes remarkably clear—on one side is the rapid establishment of exchange equity and open-source embodiment models, while on the other side is the still-forming AI safety bill. Market participants must reevaluate their technological routes and compliance costs amid this rhythm dislocation.
Xiaomi Releases Embodied World Models: Open-Source Camp Accelerates Robotics Development
In the gaps of the capital and regulatory battle, Xiaomi's technical team chose to stake their claim on "opening the world to robots." They announced the full open-source release of the training framework and model weights for the Xiaomi-Robotics-U0 embodied world model, releasing both 4B and 34B parameter versions to align with different computational and application needs: the smaller model is more suitable for resource-constrained rapid experimentation, while the larger model targets systems with ample computing power that demand complex scene comprehension. The core task of the embodied world model is to allow robots and embodied intelligence systems to "reconstruct" the physical world within abstract representations, learning and predicting their interactions with the environment—such as grasping objects, navigating spaces, and cooperating with humans—requires such an underlying world hypothesis. As the official briefing did not provide specific technical indicators and performance evaluations for Xiaomi-Robotics-U0, this release feels more like an ecological declaration: not focusing on ranking but first handing over tools to the community.
Open-source here is not just a research methodology but also a strategy for industrial displacement. Globally, the open-sourcing of large models has already proven to significantly lower research barriers, allowing university labs, startup teams, and even individual developers to participate in the iteration of embodied intelligence. By releasing the training framework along with the models, Xiaomi is inviting external forces to continue building on its technological foundation. In the context of domestic tech camps, this is a strategy to contend for the "operating system for the robotic era" through open standards: whoever's world model is most widely used stands a better chance of dominating subsequent interface standards and safety baselines. In contrast, the U.S. AI Safety Bill remains at the stage of "possibly submitted to Congress as early as next week," and the regulatory terms constraining embodied intelligence are still unclear, while the tech community has already pulled experimental and iterative rhythms ahead of policy through proactive open-sourcing, exploring the boundaries of future safety rules in real robotic scenarios.
Refined Copper Tariffs Still Undecided: Tug-of-War Between Manufacturing Costs and Industrial Protection
As the open-source offensive in embodied intelligence pushes the pace of technology ahead of regulation, another seemingly more traditional battle within the White House remains unresolved—according to two sources who spoke to Reuters, there has been no final decision on whether to impose tariffs on refined copper. Officials are caught between two sets of numbers, constantly simulating outcomes: on one hand, rising copper prices transmit along the supply chain, ultimately pushing up manufacturing costs for electrical equipment, robotics, data center infrastructure, and raising capital expenditures for new energy-related industries; on the other hand, imposing tariffs could improve the relative returns of domestic mining and upstream refining, resulting in a more "localized" supply chain layout and better manufacturing employment data. This is not a simple economic equation; it is directly connected to voter perceptions of prices and job opportunities, and any parameter adjustment could leave its mark on ballot boxes.
As of the time of reporting, the outside world does not know the final tax rate, nor the specific coverage and implementation timeline; they can only infer the White House's hesitation from these public weighing logics. In a sense, this mirrors the still-unfolding AI safety bill: on one side is the worry that overly stringent model regulation could stifle innovation, while on the other side is the concern that excessively high copper prices could hinder the expansion of robotics, data centers, and new energy hardware. The U.S. has similarly chosen a slow-motion approach between safety, costs, and industrial competition. With capital and technology already a step ahead, this deliberate slowing of decision-making signals a cautious adjustment of power and market relations at the intersection of old and new industries in the U.S.
Capital Inflows, Technology Open-Sourcing, Policy Wavering: Current Landscape and Potential Paths
Nasdaq's bet on Payward, Xiaomi-Robotics-U0's full open sourcing, Congress mulling the AI Safety Bill, and the White House's reluctance to finalize refined copper tariffs—these four events have nearly coalesced into a clear triangle within the same time window: capital continues to delve deeper into cryptocurrency trading infrastructure, technological frontiers choose maximum openness in embodied world models and robotics, while regulation and industrial policy repeatedly weigh safety, costs, and competitive pressures, deliberately slowing their actions. Capital and technology have evidently sprinted ahead; the deepening trust and layout of traditional finance in cryptocurrency and Xiaomi's pursuit of discourse power in the open-source ecosystem for embodied intelligence precede the final determinations of U.S. AI legislation and copper tariffs, laying pathways of dependence for future dynamics. For readers, the medium- to long-term main line must be filtered through uncertainty: one is to observe whether more institutions like Nasdaq will continue to embrace crypto infrastructure; two is to track how the embodied intelligence and robotics open-source communities evolve into new industrial collaborations and standards; three is to closely watch the pacing of the AI Safety Bill and refined copper tariffs, and how U.S. policy reshapes the boundaries of technology, capital, and industry through the interplay of these three directions.
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