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first_img TSMC and others' expansion has driven the top five semiconductor foundries' engineering orders to exceed 880 billion yuan

Taiwan Semiconductor Manufacturing Company, Micron, and other companies are increasing capital expenditures to expand production, driving the combined orders of the top five semiconductor engineering firms—HanTang, Axiom, FanXuan, Yankee, and ShengHui—to exceed 880 billion yuan, a record high. Taiwan Semiconductor Manufacturing Company recently stated at a semiconductor exhibition that it is building up to 20 wafer fabs, with the overall capacity expansion scale increasing multiple times compared to the past, but it still cannot meet customer demand. The U.S. tariff policy has driven the demand for manufacturing plants in the United States. Axiom has the largest order amount of 440.73 billion yuan, and Chairman Yao ZuXiang pointed out that the cumulative amount of turnkey projects undertaken in Singapore over the past four years has reached 600 billion yuan, with expectations for new projects to follow. HanTang's order amount is approximately 193.937 billion yuan, setting a new record, benefiting from continued plant construction by major clients like Taiwan Semiconductor Manufacturing Company and Micron.FanXuan's order amount reached a new high of 135.1 billion yuan, and Chairman Gao XinMing revealed that order visibility extends at least to 2028, with related projects for clients planned for 2029 and 2030. FanXuan has deployed materials, manpower, and local construction teams to support clients in Taiwan, Arizona in the United States, Japan, and Germany in synchronizing production expansion needs, and is investing in the development of technologies such as CoPoS. ShengHui's order amount exceeds 60 billion yuan, with Taiwan accounting for 68% and semiconductor orders accounting for 63%. In the first half of the year, the after-tax net profit was 2.944 billion yuan, with earnings per share of 23.73 yuan, setting a new high for the same period. Yankee's after-tax net profit in the first half of the year was 2.317 billion yuan, with earnings per share of 17.46 yuan, and the order amount is approximately 51.77 billion yuan, with order visibility reaching the end of 2027.

hot_img Zhipu has acquired AI Infra company Zhongke Jiahe for hundreds of millions, fully addressing the shortcomings in underlying heterogeneous computing power engineering

According to "AI Technology Review," China's leading large model company Zhipu has invested hundreds of millions of yuan to acquire the AI heterogeneous computing power software infrastructure company Zhongke Jiahe. This move aims to completely address Zhipu's shortcomings in the underlying engineering and compiler capabilities of large models, in response to the structural shortage of computing power and high-concurrency inference challenges caused by a surge in user numbers.Zhongke Jiahe's technology originates from the Compiler Laboratory of the Institute of Computing Technology, Chinese Academy of Sciences, founded by Dr. Cui Huimin. Its core team has been deeply involved in the development of compilers for several domestic chips, including Loongson, Sunway, Cambricon, and Huawei Ascend. Zhongke Jiahe's core advantage lies in its virtual instruction set technology, which can unify different brands and models of chip ecosystems through middleware software, assembling scattered domestic chips into a unified ultra-large-scale cluster, thereby significantly improving overall computing power utilization; its SigInfer inference engine is claimed by the official source to reduce the inference latency of large models by up to 74 times.Recently, Zhipu's Coding Agent business has experienced explosive growth. The newly released GLM-5.2 large model saw a 27-fold increase in daily Token call volume during its first week on the aggregation platform, leading to the exposure of systemic engineering bottlenecks in its inference infrastructure under high concurrency and long context scenarios. After being placed on the U.S. Entity List, Zhipu has actively promoted domestic alternatives and has now completed inference adaptation for eight major domestic computing power platforms, including Huawei Ascend, PingTouGe, and Moore Threads. The acquisition of Zhongke Jiahe will not only directly improve Zhipu's unit Token inference cost and output quality but also provide core underlying compiler technology support for its previously rumored self-developed custom AI inference chip plan.

ZachXBT: Indian scam gang suspected of social engineering to steal coins and self-reported to the police to trace and freeze funds

"On-chain detective" ZachXBT published a case analysis stating that in a cryptocurrency asset case involving an Indian scam gang, the relevant individuals reported the case to law enforcement after their assets were frozen, drawing attention. The incident began when a user sought help, claiming that approximately 5.73 BTC (about $475,000) was frozen on Changelly in March 2025.Subsequent on-chain analysis revealed that these funds could be traced back to multiple social engineering attacks and theft cases related to Bitcoin ATMs targeting U.S. users, with a total amount involved exceeding $1 million and several elderly victims. The investigation showed that the individual provided multiple changing explanations for the source of the funds, including "loan," "boss transfer," and "investment from 2014-2015," and there were significant contradictions in the evidence chain.More concerning is that this user had previously filed a police report in India in December 2025, attempting to recover the frozen funds (case number 3207-P/2025). Subsequent on-chain evidence collection and email data analysis indicated that they might be a "mule" for transferring funds, with some bank documents inconsistent with their identity information. ZachXBT noted that such cases demonstrate that social engineering attacks and cross-border fund transfers continue to occur and remind users to avoid interacting with funds from suspicious sources to prevent triggering compliance freezes or legal risks.
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