According to Woofun AI, capital expansion in the field of artificial intelligence is reshaping the market pattern on an unprecedented scale. Anthropic's listing declaration and Meta (META.US)'s huge funding move set the industry trend, while the crypto industry is finding a new balance in the game between operational risk and capital efficiency.
On October 26, Anthropic submitted an S-1 registration statement to the US Securities and Exchange Commission to officially launch the IPO process. It plans to list on the NASDAQ under the code ANT, marking the beginning of Frontier Model companies undergoing continuous testing in the open market. According to the prospectus, the company's revenue for the first half of this year was US$16.286 billion, with a net loss of US$80.748 billion for the same period — of which US$72.388 billion came from changes in the fair value of financial instruments such as convertible notes, not cash expenses. Operating losses were US$693 million, and computing power and infrastructure expenses were approximately US$8.945 billion. The number of shares to be issued and the price range have not been disclosed. The public declaration brought the operating data into the investor review stage. The listing time, financing scale, and valuation still have to wait for subsequent documents, and media predictions cannot be regarded as the results of the issuance. Analytically, corporate customer growth needs to be viewed in conjunction with inference costs, computing power commitments, and cash returns. The model is capable of leading the way and can help obtain orders, but it cannot individually explain whether each order creates sustainable profits.
For chip and cloud vendors, the listing of major customers will also make the investment, procurement, and revenue relationships in the industry chain more transparent. The next key is whether growth can be converted into operating leverage, and whether public disclosure can explain how capital is being used. On the same day, Meta announced the commencement of an underwriting offering of approximately $35 billion, including approximately $225 billion in common shares and $12.5 billion in depositary shares representing mandatory convertible preferred shares. The company also plans to launch a market-wide issuance plan of about 60 billion US dollars after Class C stock trading begins. It is expected to start as early as the first quarter of 2027, but the relevant agreement has not yet been signed.
The two parts together amount to about $95 billion, and the funds have yet to be fully credited. The financing structure shows that AI infrastructure expansion is simultaneously using operating cash, debt, and equity. Analytically, equity financing reduces the pressure to repay new fixed debts and also brings potential dilution, while forced conversion arrangements delay part of the impact. Compared to the capital operations of crypto reserve companies, both need to explain how additional capital increases value per share, but the underlying business and sources of cash are different. What investors really want to compare is the return on cash after expansion and the cost of capital, not just the total amount of financing.
According to data compiled by Woofun AI, in terms of technology implementation, Cadence (CDNS.US) launched a Maestro specific model portfolio for chip and system design on October 26, and plans to provide early access to some customers in the fourth quarter of this year. The company said the portfolio is partly based on Nvidia's Nemotron open source weighting model and can be combined with design agents, EDA tools, and reinforcement learning processes to support cloud and customer local deployments. The company said that preliminary tests showed that the quality of the results was improved by up to 30%, and the efficiency of the token was increased by up to 5 times, which is superior to the general basic model, but the test items and comparison benchmarks have not been disclosed, and the benefits of all design projects cannot yet be extrapolated. It brings AI competition into an environment where feedback is more clear. Analytically, chip design can use tools to check whether timing, power consumption, and constraints are met, so that agents can improve based on engineering results, rather than just comparing whether answers are like experts. Allowing local deployment also responds to customer concerns about design data and trade secrets. For the industry, the depth of the combination of models and existing tools may be more valuable than a single generic competency ranking. In the future, it is still necessary to observe whether verification costs, error handling, and delivery cycles in actual projects have improved.
At the risk level of crypto operations, it was reported on October 26 that CoinDCX confirmed losses of approximately 15.99 million USDT. According to the company, some users are still depositing funds to previously decommissioned wallet addresses, and the service responsible for collecting funds failed for a period of time, causing funds to accumulate. The address in question was affected by a security incident in July 2025. This confirmation comes only a few days after the company's initial denial — CEO Sumit Gupta once called the on-chain change a “false surprise,” and on-chain researcher ZachXBT later indicated that at least one of these addresses was still collecting funds from April to May 2026 before the company posted a blog acknowledgement. The announcement did not fully explain how the funds were transferred and who operated it. The problem was revealed in the old infrastructure's exit process. Analytically, stopping showing a deposit address does not mean that the on-chain address stops receiving funds. As long as the system continues to charge and account for incoming payments, it is necessary to continuously check the collection, balance, and permission status. The exchange stated that user balances and active systems were unaffected, which is still the company's disclosure. For the escrow business, monitoring, abnormal upgrades, and timely disclosure of retired wallets are just as important as the security of new wallets. Historical risk may continue to generate new losses if the clean-up is not completed. Meanwhile, Bitmine (BMNR.US) announced on October 26 that it had repurchased approximately 2.04 million shares in the past week, at an average price of $22.48, or USD 45.9 million.
Meanwhile, the company bought 10,452 ETH. Its disclosed position reached 6,051,933 ETH on October 25. The amount of coins purchased during the same period was about US$24.6 million, less than half of the buyback investment; in addition, the weekly increase in ETH holdings has declined from 12,535 to 10,452, and has been slowing for two consecutive weeks. The capital is actually trending towards repurchases rather than being distributed evenly between the two types of uses. This provides a concrete example of the reserve company capital constraints discussed yesterday. Analytically, management believes that when stocks are undervalued, repurchases may be more attractive than direct coin purchases, but the effect depends on the repurchase price, net asset value, and funding source. It also reduces the amount of cash available for subsequent purchases or other expenses. To determine the value of a reserve company, it is necessary to simultaneously observe the total amount of coins held, number of shares in circulation, and financing obligations. Looking only at the increase in the number of assets, it is easy to overlook whether the equity per share has improved and whether the cash buffer has thinned.
In terms of regulatory and security dynamics, the OCC encourages community banks to participate in stablecoin payments. On October 26, the US Monetary Authority called on community banks to apply directly or through subsidiaries to become approved stablecoin issuers. This is a policy statement to promote banks' participation; specific institutions still need to complete application and compliance procedures. South Korea is discussing delaying taxes on crypto gains again until 2029. On October 26, Korean media reports were quoted as saying that insufficient access to data on cross-border transactions was one of the main obstacles in discussions. Delaying implementation still requires the National Assembly to amend the law; it cannot currently be regarded as an effective arrangement. The NBA and CFTC signed a memorandum of understanding on predictive market information. On the same day, Kalshi and Polymarket were also designated as the league's “preferred prediction market exchange”, and required league and team personnel not to trade NBA event contracts.
The US Commodity Futures Trading Commission announced on October 26 that the two sides will regularly communicate and share information to prevent issues such as insider trading and fraud. Information cooperation does not automatically resolve regulatory disputes between states and the Commonwealth. Electrum fixes a fund theft vulnerability in the transaction acceleration process. The October 26 report noted that malicious servers can falsify transactions to be confirmed to induce users to sign transactions to pay attackers when increasing processing fees. The developer publicly disclosed on the 24th that the 4.8.3 release included fixes and confirmed that at least one user lost money as a result.