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Cardano ecosystem project Empowa disclosed that two interconnected unauthorized asset transfer incidents occurred involving its three project wallets. Between November 2025 and June 2026, approximately 143,710 ADA was transferred out in 18 transactions from one project treasury wallet, which was also registered and claimed by unknown individuals using the private key corresponding to the Midnight airdrop, of which about 36,000 NIGHT has been transferred away.From June to August 2026, approximately 4.24 million EMP was transferred out from the other two project wallets, some of which have been sold through Minswap, VyFi, and others. Empowa stated that the funds from the two incidents ultimately flowed to the same intermediary wallet, indicating control by the same party, but the identity of the individuals operating these private keys cannot currently be confirmed. The project team has hired a professional blockchain investigation agency and plans to seek KYC information through the centralized exchanges where the relevant funds ultimately entered.

According to official sources, consumer crypto product RealGo has announced the completion of a new $6 million strategic financing round, backed by UZ Capital, Greenwood Global Capital, and Infinite Alliance. The newly raised capital will be allocated toward core product development, global talent acquisition, and ongoing AI research and implementation, aiming to reinforce its Meme ecosystem applications and on-chain value framework as RealGo scales into a globally influential Meme 3.0 infrastructure and Meme AI powerhouse. RealGo is a consumer-facing Web3 ecosystem integrating AR, AI, LBS, social experiences, and on-chain asset infrastructure. The platform transforms Meme IPs into interactive and ownable digital assets that can be discovered, collected, connected, utilized, and traded across digital and real-world experiences.

Liquid Compute CEO Ronit Jain published an article introducing the hedging of computing power prices. Purchasing computing power, holding GPUs, or lending based on this has exposed them to computing power price fluctuations. Hedging is a cash-settled contract that locks in future prices against an index without the need to transfer GPUs.Companies can buy forwards to fix the cost of next year's capacity as a budget item while still being able to purchase from any supplier. Neocloud can sell forwards to convert uncontracted hours into fixed cash flow, making it easier for lenders to provide loans based on this. Regarding the residual value of sale-leaseback, recent forwards can be rolled over when entering a tradable range, or put options can be bought on forwards, with more liquid near-term options available to pay for the option premium.Hedging locks in prices rather than quantities, and does not completely match actual rates, nor is it free: it requires giving up favorable price movements or paying option premiums. Legally, it usually requires signing an ISDA Master Agreement with the counterparty, obtaining permission for the settlement index, and determining the ratio of hedging exposure.

Pantera Capital Junior Partner Jay Yu published an article titled "The Rise of Compute Markets," stating that computing power and data center spending have become a trillion-dollar category, but GPU procurement is still mainly done through group chats, over-the-counter brokers, and bilateral agreements. He noted that the financialization of computing power is still in its early stages, constrained by SKU, time, and location, but could become a commodity asset similar to electricity or oil in the next 5 to 10 years. Jay Yu believes that the computing power market may form a "hardware-supplier-cluster" structure similar to the electricity "grid-operator-node," with new cloud vendors being structural shorts on GPUs, while on-demand platforms and application layers are longs.He mentioned that for every $100 spent on inference at the application layer, about $45 flows to the on-demand layer, about $50 flows to the new cloud or GPU layer, and about $5 flows to routing layers like OpenRouter. NVIDIA can be seen as the "central bank" of computing power, having announced support for up to 25% residual value. He also stated that physical delivery has a more enduring moat, and indices, cash-settled exchanges, and financing tools will subsequently emerge, with participants including SF Compute, Vast AI, Runpod, Compute Exchange, and others. The computing power market does not have mandatory price transparency requirements, and basis risk may be greater.

According to the New York Times, OpenAI expects its computing power expenditure to reach $750 billion by 2030.

Indonesian AI infrastructure platform Zankore has received support from NVIDIA, signing a $3.1 billion loan agreement to purchase advanced chips, highlighting the surge in demand for computing power in Asia.Citigroup, Dutch International Bank, and others are underwriting this loan, with Citigroup as the sole debt advisor. This is one of the largest AI infrastructure financings in Asia.

According to Decrypt, the Mexican federal prosecutor, in conjunction with the Navy and Puebla state police, conducted a raid on a property in the remote mountainous area of Tlaola, Puebla, seizing approximately 300 cryptocurrency mining machines, as well as transformers, medium-voltage terminals, and satellite internet antennas.The investigation revealed that the mining operation illegally tapped into the grid of the Nuevo Necaxa hydroelectric power station, and authorities have filed charges for "theft of electricity." Currently, forensic accountants are tracing the source of the hardware funding, and money laundering suspicions have not been ruled out. Data from the Mexican Federal Electricity Commission shows that from January to July 2024, non-technical electricity losses reached up to 6,346 gigawatt-hours, valued at approximately 13.8 billion pesos (about 817 million USD).

Pequity Research cited FundaAI stating that the training computing power used by GPT-6 is approximately 10 times that of GPT-5.FundaAI indicated that based on industry discussions, the total computing power consumed by experiments, reinforcement learning, synthetic data generation, and supporting infrastructure could be several times that of the main pre-training run, potentially reaching up to ten times. Once TPU 8t and Vera Rubin are shipped on a large scale, the next round of pre-training acceleration can begin, with large-scale interconnection and optics benefiting the most during this cycle.

The Ministry of Industry and Information Technology of China released the "14th Five-Year Plan for the Development of the Information and Communication Industry," setting the national intelligent computing power target at 9800 EFLOPS by 2030. According to data from the National Bureau of Statistics, as of the end of July, the national intelligent computing scale was approximately 2450 EFLOPS (FP16), indicating that it needs to expand by about 4 times in the next four years based on this standard.The plan proposes an orderly deployment of intelligent computing clusters with tens of thousands and hundreds of thousands of cards, building inference computing power for different scenarios, and increasing the adaptation of domestic computing power chips. Currently, 52 intelligent computing facilities with more than ten thousand cards have been established nationwide. The Ministry of Industry and Information Technology disclosed that the intelligent computing power scale at the end of June was 2185 EFLOPS, a year-on-year increase of 177%. The plan uses 1590 EFLOPS in 2025 as a benchmark, aiming to reach 9800 EFLOPS by 2030, which is an expansion of about 6.2 times. During the same period, the cumulative investment target for information infrastructure in the information and communication industry is 3.8 trillion yuan, which also includes communication networks and is not all allocated for AI computing power.

According to the official announcement, Bitget has launched the pre-market perpetual contracts for retail users, H100 and B200, which are linked to the rental price index of NVIDIA H100 and B200 GPUs, respectively, quoted in USD per GPU hour.Bitget's pre-market perpetual contracts further extend the trading targets into the AI computing power field. By tracking the GPU rental market index price, users can participate in the price discovery of global GPU rental prices and the AI infrastructure market in advance, capturing potential trading opportunities brought by changes in demand for high-performance GPUs such as H100 and B200. The product adopts a perpetual contract model settled in USDT, supports up to 10x leverage, and allows trading 24/7.

According to statistics from The Information, Anthropic has signed at least 14.8GW of computing power in the past 11 months, which can be gradually utilized in the coming years. Based on currently public contracts, the potential total cost could reach up to $517 billion, with most expenditures occurring over the next decade. In addition to the 1-2GW already secured before October last year, the total computing power signed by Anthropic is approximately 16GW.This round of expansion is primarily driven by the demand for Claude. This year, the growth of Claude Code and Cowork has exceeded Anthropic's expectations, prompting the company to focus on acquiring computing power. The new agreement with Amazon provides up to 5GW, while Google and Broadcom offer another 5GW, and Microsoft and NVIDIA provide approximately 1GW. Anthropic has also rented all computing power from SpaceX's Colossus 1, acquiring over 220,000 NVIDIA GPUs, including H100, H200, and GB200.Anthropic has secured about 16GW, with many contracts extending beyond 2030. OpenAI has set a target for investors to reach 30GW by 2030, expecting to invest approximately $750 billion in computing power by that year. The $517 billion figure is the potential maximum cost estimated by The Information based on existing cloud services, chip, and data center contracts, with some computing power potentially being delayed or unused, and some contracts allowing for early cancellation.

Silicon Valley angel investor Liron Shapira posted on X this morning, stating: "I assert (with 50% confidence): due to AI shaking the security and stability guarantees that people once believed Bitcoin had, the price of BTC will plummet more than 50% within the next two years."Ethereum co-founder Vitalik Buterin rebutted this, saying: "I hold the completely opposite view. My fundamental reason is that, in the long run, I am quite optimistic about network security, and I believe the main challenge is how to smoothly transition through the transition period. Moreover, I believe BTC can at least properly handle all issues that do not require social consensus to resolve (for example, upgrading clients, mining pools, etc., to deal with network layer attacks fall into this category). Additionally, I believe the probability of hash algorithms or proof-of-work mechanisms being truly compromised is extremely low. I wanted to make a bet with you, but considering my current asset allocation (I guess you have the same view on Ethereum ETH), I have already staked about 90% of my wealth on this bet."

South Korea plans to integrate five public power companies in October 2027 to accelerate investment and meet the energy demands brought about by the growth of the country's artificial intelligence and chip manufacturing industries.Seoul also plans to streamline public enterprises in the oil, gas, and port sectors.

According to Xinhua News Agency, the Bank of China Inner Mongolia Branch recently issued the first "Computing Power Token Loan" in the Inner Mongolia Hohhot New Area. By innovating the credit evaluation system, it incorporates the scale of enterprise token usage, computing power cooperation orders, core technology qualifications, and scientific research and development capabilities into the core credit indicators, while weakening traditional mortgage guarantee requirements.Currently, Hohhot's computing power scale reaches 150,000 P, of which intelligent computing accounts for 146,000 P, and the green computing power index ranks first in the country. The local area also promotes "Computing Power Loans" and medium-to-long-term technological transformation loans, using policy financial tools and syndicated loans to address capital and large fund needs, and has launched "Computing Chain Insurance" and cybersecurity insurance to provide diversified risk control guarantees for heavy asset projects such as data centers against fire, water damage, machine failure, and more.

The Korea Electric Power Corporation is negotiating a multi-billion dollar electricity prepayment plan with Samsung Electronics and SK Hynix to raise funds for the power grid needed to build a new semiconductor industry cluster. According to the current plan, Samsung Electronics will prepay 200 trillion won, and SK Hynix will prepay 50 trillion won, totaling 250 trillion won, which is approximately equivalent to the electricity costs for the next five years.In a statement, Korea Electric Power said that the large-scale electricity prepayment system is a mechanism that meets the needs of companies urgently needing to expand the power grid and Korea Electric Power, which requires investment funds. Specific details, including the amount of prepayment and the coverage period, have not yet been finalized.

On Wednesday, local time in the United States, NVIDIA CEO Jensen Huang appeared at the G20 Innovation Ministerial Meeting and engaged in a fireside chat with U.S. Secretary of Commerce Gina Raimondo. Huang stated that AI is evolving into a national economic infrastructure similar to electricity and the internet, and the biggest risk countries face is not sufficiently investing in and adopting AI, ultimately being left behind by the industrial revolution.Huang mentioned that currently, building 1 gigawatt of AI infrastructure requires an investment of about $50 billion to $60 billion, and he expects that from now until the end of this decade, the scale of related construction will reach approximately 100 gigawatts. He also referenced the "five-layer cake" model of energy, chips, infrastructure, models, and applications, indicating that every country needs to build AI infrastructure and decide which aspects they wish to participate in.Huang anticipates that in the coming years, AI will essentially achieve AGI, and the next phase will transition from large language models to intelligent agents and embodied intelligence. He believes that AI is more likely to replace tasks rather than completely replace jobs, with operational tasks such as writing and information processing potentially becoming gradually automated.