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According to the Goldman Sachs report on "China's AI Computing Power" disclosed by P Equity Research, China is accelerating the construction of a national computing power network, with related infrastructure projects expected to attract 7 trillion yuan in investment by 2026. In the next five years, investment in data centers is projected to reach about 2 trillion yuan. Currently, funds and technology are being massively transferred to western computing power hubs, while data centers in first-tier cities are transforming to focus on ultra-low latency computing, edge nodes, and AI inference. Although GW-level clusters with over 100,000 chips remain scarce domestically, in typical GW-level computing power parks, workloads are primarily composed of inference, which accounts for more than half, as well as training and full-stack R&D.The report predicts that by 2026, the market share of domestically produced AI acceleration chips is expected to exceed 50%. Among them, Huawei and Alibaba's Pingtouge lead the domestic camp with shares of 20% and 7%, respectively, but Nvidia currently maintains overall market dominance with a 55% share. In terms of cost and performance, domestic chips have capital expenditures on IT power consumption that are 40% to 50% lower than imported chips, but due to performance gaps, their capital expenditures per unit of computing power are 2 to 4 times that of imported chips, and the computing power generated per unit of power consumption is only 10% to 30% of that of imported chips. Additionally, the daily average token output of Huawei's 910B/910C servers is about one-sixth to one-third of that of Nvidia's H800, resulting in significantly lower API profit margins based on that hardware compared to peers using Nvidia hardware.

According to the Financial Times, the UK's Financial Conduct Authority (FCA) has warned that regulation of artificial intelligence in the financial sector is facing an "arms race" and urged for new powers to regulate ChatGPT, Claude, and Gemini.

Tether CEO Paolo Ardoino posted on the X platform, stating that large AI tech companies are acquiring users through subsidized computing power and continuously investing in high-cost infrastructure and capital expenditures, but related assets face rapid depreciation pressure of about 3 to 5 years.He pointed out that there are multiple mismatches in the current industry, including the mismatch between token prices, profit timelines, and the maturity of capital costs; meanwhile, open-source AI is also continuously eroding the industry's growing revenue share.

According to reports from Jiemian News, Kingsoft Cloud will accelerate the construction of GPU computing clusters in the second half of the year to meet the explosive growth in computing power demand from major clients. Among them, Xiaomi's demand for Kingsoft Cloud's GPU computing power has upgraded from a ten-thousand-card cluster, with the related budget significantly increasing from nearly 4 billion yuan to over 10 billion yuan. In addition, Alibaba's large model team has signed a 5-year computing power leasing contract with Kingsoft Cloud, involving more than 3,000 eight-card GPU servers. Based on the contracted price, the annualized revenue after full delivery will exceed 4 billion yuan.To meet the surging customer demand, Kingsoft Cloud's capital expenditure plan for 2026 has been raised to 15 billion yuan, with an annual revenue target of 12.5 billion to 13.5 billion yuan. It is reported that due to tight upstream supply, Kingsoft Cloud is currently only accepting long-term contracts from clients for 3 to 5 years, and some orders are facing delivery delays. Due to concerns about the risk of impairment of high-level card assets, Kingsoft Cloud is currently pausing aggressive hardware expansion, anticipating that the prices of computing hardware may reach a turning point for decline in the third quarter of this year.

Jurrien Timmer, Global Macro Director at Fidelity Investments, stated that Bitcoin is approaching the long-term Power Law model support level, or facing a critical technical test. Currently, the support line of this model is at $58,237, while $60,000 is seen as an important psychological and technical threshold. In addition, Jurrien also pointed out that due to the slowdown in global liquidity growth and speculative funds continuing to flow into technology stocks and other risk assets, Bitcoin currently lacks the macro catalysts necessary to drive a trend reversal. Although this model support level has historically become a market bottom multiple times, Bitcoin may still oscillate in this area for a while, waiting for a more favorable macro environment to drive a new round of increases.

Due to Meta CEO Mark Zuckerberg revealing that the company is considering leasing excess AI computing power, concerns have arisen in the market about the "shift from buying to leasing" AI infrastructure. South Korean semiconductor giant SK Hynix and the South Korean stock market (KOSPI) experienced a sharp decline. According to data from the Gate platform, SK Hynix (SKHYNIX) is currently priced at $1,538.3, with an intraday drop of nearly 10%. The volatility in the stock market has led to increased activity in related contract trading. According to CoinGlass data, the contract position for Gate SK Hynix (SKHYNIX) exceeds $26.29 million, and the 24-hour contract trading volume exceeds $34.41 million, both ranking among the top in the industry.

According to a report by the Financial Associated Press, Nvidia announced a new AI infrastructure collaboration model on July 1 local time. Through revenue-sharing and credit-support mechanisms, it will jointly build large-scale, multi-tenant AI factories with AI cloud service providers, helping startups, model developers, enterprises, and research institutions to access AI computing power more quickly, while creating a sustainable revenue stream for Nvidia linked to computing power usage.According to the plan, AI cloud vendors will deploy AI factories based on the Nvidia DSX AI Factory architecture to provide cloud computing services. The first batch of partners includes Sharon AI and Firmus. Among them, Sharon AI plans to deploy up to 40,000 NVIDIA Grace Blackwell GB300 GPUs; Firmus will build a DSX AI factory park on Batam Island, Indonesia, with plans to expand to a power scale of 360 megawatts and deploy up to 170,000 Nvidia GPUs.

According to Jinshi reports, Meta Platforms' pre-market stock price rose by more than 8%, as the company is building a cloud business to sell excess AI computing power.

B.AI officially announced that its team-level AI collaboration product "B.AI Team" has entered the first phase of gray testing and is simultaneously launching a public recruitment for the first batch of experience teams globally.This version focuses on the pain points of enterprise-level AI collaboration, launching a shared Credits pool to achieve unified scheduling of team computing resources and cost visualization management; it also provides a flexible multi-level member permission system, supporting refined configuration of model usage strategies by role, truly allowing AI capabilities to adapt to the collaboration processes of different teams.Starting today, teams interested in seizing the opportunity can submit their requirements through the official application link and briefly describe their core usage scenarios; after approval, the B.AI team will connect with them promptly and grant priority access rights when the official version goes live, helping teams to be the first to enjoy a new experience in intelligent collaboration.

With the European Union's Markets in Crypto-Assets Regulation (MiCA) officially coming into full effect on July 1, 2026, it marks the beginning of a new era of unified regulation in the European digital asset market. As the global regulatory framework continues to improve, stablecoin payments are evolving from a focus on "pure efficiency" to "compliance, transparency, and trust," accelerating their transformation into core infrastructure for enterprise-level payments.As a provider of enterprise-level stablecoin payment infrastructure, WasabiCard consistently practices a "compliance first" development philosophy. By continuously strengthening core risk control capabilities such as AML (Anti-Money Laundering), KYC (Know Your Customer), and KYB (Know Your Business), it is committed to building a secure, transparent, and sustainable foundation for global payments.As stablecoins rapidly penetrate core business scenarios such as enterprise treasury management, cross-border payments, and B2B settlements, compliance capability has become the primary consideration for enterprises when choosing payment channels. In the future, WasabiCard will leverage its core capabilities of "global issuance, stablecoin payments, global remittance, and fund distribution" to deeply integrate a comprehensive compliance system with business scenarios, helping global enterprises confidently navigate the evolving regulatory environment and significantly enhance the security and compliance efficiency of their global operations.

According to a report by 21 Finance, Huang Zhenxin, the head of Kimi B-end at Moonshot AI, stated in a recent communication meeting that there is indeed a bubble in the current AI industry, but the fundamentals are very solid. Enterprises can now clearly calculate the return on investment (ROI), and the substantial transformation in productivity brought by AI has already occurred.Regarding the recent phenomenon of widespread price increases among model vendors, Huang Zhenxin pointed out that the core reason lies in the rising global computing power costs, and chip production capacity cannot meet the explosive growth in Token demand. He emphasized that evaluating the cost-performance ratio of models should not only look at the unit price of input and output but should also focus on the Cache hit rate. It is reported that Kimi's original factory Cache hit rate has reached over 90%, significantly reducing actual computing costs.In addition, Huang Zhenxin revealed that Kimi will continue to challenge innovations in underlying architecture to sustain the Scaling Law, and its Muon optimizer, which has been validated on a large scale, is now widely adopted by several mainstream large models in the industry. Regarding the "last mile" of enterprise AI implementation, he believes that as the foundational capabilities of models continue to strengthen, the technical paradigms at the application layer will also continue to simplify.

According to C114 Communication Network, China Mobile has recently established a "Token Office" at the group level, directly led by the core leadership of the group, with the general manager of the Strategic Development Department serving as the executive deputy director, a position higher than the previous Computing Power Office.It is reported that this department aims to streamline the entire process of "creating Tokens, delivering Tokens, and applying Tokens," breaking the previous situation where multiple secondary departments such as the Computing Power Office, Mobile Cloud, Digital Intelligence Business Unit, Marketing Department, and Government and Enterprise Business Unit operated independently. Its core mission is to promote the implementation of two underlying capabilities in the intelligent era of China Mobile: first, to introduce the MobileClaw intelligent framework with a rich "skill package," and second, to gather over 300 mainstream models on the Mobile MoMA model platform, to accelerate the commercial implementation and large-scale operation of operators in the dimensions of AI network infrastructure and model application.

CITIC Construction Investment Research Report points out that the following factors will determine the trend of the third quarter market: In terms of fundamentals, AI computing power remains at a high level of prosperity, with mid-year performance and overseas financial reports worth paying attention to. At the same time, since April, under pressure from the macro economy, the economic measures from the Politburo meeting in July are quite important; In terms of liquidity, external disturbances have increased, while internal conditions remain neutral; In terms of risk appetite, geopolitical events and the listing of industry giants will cause short-term fluctuations in the market. Considering the global tech stock correlation effect, major overseas computing powers such as Japan, South Korea, and the United States also need to be continuously monitored.In terms of industry allocation, although the logic of AI computing power remains unchanged, volatility has intensified. It is recommended to be cautious about chasing highs and to position during pullbacks; lithium batteries are expected to welcome a peak season, and energy storage demand continues to warm up, while new energy presents opportunities for phased valuation recovery; dividends are expected to rebound from oversold conditions, with relatively high cost-performance ratios. Key areas to focus on: banks, coal, public utilities, AI, optical modules, storage, chips, industrial metals, lithium battery materials (VC), etc.

According to a report by the Financial Times cited by Jinshi, Google has imposed limits on Meta's use of its Gemini AI model, as Meta's computing power exceeds what Google can provide.The report states that Google informed Meta around March that it could not meet all of the Gemini computing power that Meta sought to purchase, adding that this gap disrupted and delayed some of Meta's internal AI projects. The report also noted that several other clients of Google were affected, but to a lesser extent. The Financial Times stated that Meta was particularly severely impacted due to its exceptionally high demand for Google's models.

According to monitoring by Catcher Predict, in the market prediction event "Dota 2 Power Rangers vs Yellow Submarine European Qualifiers" on Polymarket, the "Yes" option for the sub-market "Both Defeat Roshan" has experienced a dramatic fluctuation in win rate, soaring from 50% an hour ago to the current 90% (a fluctuation of 40%). Please note the impact of related breaking news.

According to WEEX TradFi data, the US stock market has been fluctuating recently, with funds continuously focusing on AI infrastructure-related directions, among which the AI power and energy sector has shown strong performance. Among them, Eaton (ETNON, a leader in data center power management) rose by 3.15%, Vistra (VSTON, an AI power and generation company) rose by 2.22%, and GE Vernova (GEVON, a leader in grid equipment and generation facilities) rose by 1.65%. WEEX Labs believes that the expansion of AI computing power continues to increase the power demand of data centers, and power management and energy infrastructure are becoming important supporting links in the AI industry chain, with increasing attention on related assets.

According to official news, the computing power market infrastructure company Ornn announced the completion of a $33 million seed round financing, led by a16z Crypto, with participation from Galaxy Ventures, Nordstar, and SV Angel, while Vine Ventures, Crucible Capital, Link Ventures, and Box Group continue to support.Ornn stated that a mature commodity market first requires reliable pricing data, which leads to price discovery, and price discovery then supports risk transfer, which in turn enables more efficient capacity allocation. The OCPI it launched is a transaction-based computing power index aimed at providing a unified and trustworthy price benchmark for settlement in the computing power market. Partners like ICE can promote risk transfer by directly referencing OCPI's futures and options contracts.Additionally, Ornn announced the launch of Ornn Compute, a physical capacity layer for the computing power market that can aggregate dedicated GPU capacity from multiple neoclouds onto a single platform, providing a unified access process, a secondary transfer market, and on-demand subleasing capabilities. Operators can obtain diversified demand from multiple tenants through a single underwriting contract, while buyers can view the sites, hardware configurations, and terms of the reserved clusters. This platform will make dedicated GPU capacity a liquid asset and allow previously idle capacity to be utilized.