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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 underlying engineering and compiler capabilities for large models, in response to the structural shortage of computing power and high-concurrency inference challenges brought about by the explosive growth 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, Cambrian, 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 officially claimed to reduce large model inference latency by up to 74 times.Recently, Zhipu's Coding Agent business has experienced explosive growth. The newly released GLM-5.2 large model saw an average daily Token call volume surge 27 times in the first week of its launch 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 will also provide core underlying compiler technology support for its previously rumored self-developed custom AI inference chip plan.

Goldman Sachs and JPMorgan Chase released their Q2 financial reports, with hundreds of billions in credit flowing into adjacent sectors of cryptocurrency

According to BBX data, yesterday the two flagship institutions on Wall Street released their Q2 2026 financial reports on the same day, forming an important institutional narrative anchor regarding AI infrastructure and digital assets. The core dynamics are as follows:The Goldman Sachs Group, Inc. (NYSE: $GS) released its Q2 2026 financial report on July 14, with CEO David Solomon providing the strongest institutional endorsement of AI infrastructure to date during the earnings call: "AI infrastructure is in the early innings of a multi-year investment cycle," and stated that the company expects to finance most of the AI infrastructure development, driving growth in mergers and acquisitions, debt and equity issuance, and lending opportunities. This assessment highly resonates with Goldman’s ongoing positioning in the crypto ecosystem: Q1 2026 13F shows the company holds approximately $700 million in iShares Bitcoin Trust ($IBIT) positions, while simultaneously liquidating all positions in XRP ETF and Solana ETF, and increasing holdings in Circle ($CRCL), Galaxy Digital ($GLXY), and Coinbase ($COIN) stocks; the company applied to the SEC for a Bitcoin Premium Income ETF (covered call option structure) on April 14; and on June 12, completed a $75 billion fundraising as the lead underwriter for SpaceX's largest IPO in history. Solomon's "early innings" assertion is a public confirmation that Goldman views AI infrastructure investment and crypto asset allocation as part of the same long-term narrative.JPMorgan Chase & Co. (NYSE: $JPM) also released its Q2 2026 financial report on July 14. According to CoinDesk Live Updates, CEO Jamie Dimon identified the rapid construction of AI computing infrastructure as a core driver of corporate investment and financing demand during the earnings call, forming a rare cross-institutional consensus with Goldman and BofA. JPMorgan has previously maintained a cautious stance on crypto regulation, but its statements in the AI data center financing sector are becoming a foundation for its entry into adjacent crypto tracks (including loans to AI mining companies and tokenized bond underwriting). Notably, JPMorgan has previously issued multiple warnings of "time running out" during the CLARITY Act legislative process, and this financial report did not provide a new legislative timeline assessment, but the strong qualitative outlook for AI infrastructure indicates that the bank will continue to provide financing services to AI mining clients such as TeraWulf and IREN, further deepening its balance sheet exposure to the crypto ecosystem.
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