Subida acentuada de USD.AI (CHIP)

AI chip startup Groq has raised $350 million in a funding round that values the company at $3.5 billion, nearly half its peak valuation of $6.9 billion from September last year. The company was originally founded in 2016 to build hardware to compete with Nvidia but faced a significant setback after Nvidia licensed its technology and poached its founder, Jonathan Ross, along with other senior staff. This leadership loss forced Groq into a period of restructuring. The new funding round was led by Dallas-based investment firm Disruptive, with Nvidia also participating as an investor. Groq has pivoted its business model from selling chips to operating data centers, aiming to meet the demand for AI inference computing power. The company plans to use part of the new capital to expand its data center infrastructure, targeting over 200 megawatts of total capacity by next year.

**Market Overview:** On August 18th, U.S. stock indices declined for a second consecutive day. The S&P 500 fell 0.52%, the Dow dropped 0.51% to a two-week low, and the Nasdaq slipped 0.32%. The decline was driven by heightened geopolitical risk as U.S.-Iran negotiations reached a key deadline without an extension, dimming the prospect of a long-term agreement. **Key Drivers:** * **Geopolitics & Oil:** The failure to extend the U.S.-Iran memorandum led to a surge in oil prices, with Brent crude closing above $90/barrel for the first time in three weeks. * **Treasury Yields:** The 30-year U.S. Treasury yield hit a high not seen since 2007, driven by heavy corporate issuance (notably for AI investments) and ongoing fiscal deficits. * **Sector Performance:** While the "Magnificent Seven" tech giants all closed lower, semiconductor stocks bucked the trend. The Philadelphia Semiconductor Index rose 1.6%, led by memory chipmakers (e.g., SanDisk, Micron) and optical communication companies, as investors focused on the strong demand outlook for AI-related hardware. * **Currency & Safe Havens:** The U.S. Dollar Index fell for a third day, while the offshore Chinese Yuan hit a three-year high. Gold prices rose to a two-month peak, supported by safe-haven demand outweighing pressure from rising yields. Bitcoin also gained. **Outlook:** Market focus remains on potential escalation in the Middle East and its impact on oil, alongside continued scrutiny of AI-related earnings and demand signals.

**Title:** Trade.xyz Captures Over Half of Hyperliquid's Trading Volume with AI Chip Stocks and Oil Perpetuals **Summary:** Driven by the launch of AI chip stock and oil perpetual contracts, Trade.xyz has become the dominant builder on Hyperliquid following its HIP-3 upgrade, now accounting for over 55% of the platform's trading volume. The HIP-3 proposal shifted market creation from validator votes to a staking and auction model, allowing builders like Trade.xyz to deploy their own perpetual futures markets. Trade.xyz's focus on traditional assets like AI/Compute equities, crude oil, and major indices has attracted significant on-chain trading activity. In the past month alone, it generated approximately $5 million in fees, which are split 50/50 with Hyperliquid. A significant portion of this revenue is used for open-market buybacks of the HYPE token, reducing its circulating supply and creating a direct link between platform activity and token value capture. This growth highlights both the potential for ecosystem concentration around a single major builder and the evolving mechanisms for HYPE's value accrual.

Kao, the renowned Japanese consumer goods giant known for laundry detergent and facial cleansers, has quietly become a leader in the semiconductor precision cleaning agent market, as revealed in its recent financial report. The company's chemical business, which includes semiconductor precision cleaning agents, achieved net sales of 2472 billion yen (approx. RMB 104.4 billion) in the first half of fiscal 2026, growing 9.4% year-on-year and becoming its fastest-growing segment. Notably, Kao holds about a 60% market share in cleaning agents for package substrates and is also a leader in specific chemicals for NAND flash manufacturing processes. Its products have entered the supply chains of major chipmakers like TSMC, Samsung, and Kioxia. Kao's journey into semiconductors began with its core expertise in surface science, developed from its origins in soap and detergent manufacturing. The 1987 Montreal Protocol, which phased out ozone-depleting solvents like Freon, created a demand for alternative cleaning solutions. Leveraging its deep knowledge of surfactants and purification, Kao launched its "CLEANTHROUGH" aqueous cleaning agent in 1991, entering the precision cleaning market. Over the past three decades, Kao has expanded its product line to cover both front-end (wafer fabrication) and back-end (packaging) semiconductor processes. Its "precision interface control technology" addresses key challenges like particle removal, photoresist stripping, and cleaning complex structures in advanced packaging without damaging delicate materials. Beyond cleaning, Kao's portfolio extends to adjacent processes like dry film photoresist stripping. A key to Kao's success is its customer-centric business model. The company operates "Fine Cleaning Centers" in Japan and Taiwan, where it collaborates directly with clients on process development. This deep integration, coupled with the high cost and risk of switching validated materials in semiconductor production, creates strong customer loyalty. As the AI boom drives demand for complex chip packaging like CoWoS, which requires more numerous and difficult cleaning steps, Kao is strategically positioned. The company plans to defend its back-end dominance while expanding into DRAM and logic semiconductor markets. Kao's story mirrors that of other Japanese firms like Ajinomoto (ABF film) and TOTO (electrostatic chucks), which leveraged deep-rooted core technologies from seemingly unrelated industries to achieve leadership in critical, niche segments of the semiconductor supply chain.

Shanghai-based automotive-grade millimeter-wave radar chip unicorn Calterah Microelectronics Technology (Shanghai) Co., Ltd. has filed for an IPO on Shanghai's STAR Market, aiming to raise 3.49 billion yuan. Founded in 2014 by Chen Jiashu, a UC Berkeley PhD graduate, and his professor Ali Niknejad, Calterah pioneered CMOS technology for 77GHz radar chips, breaking the decades-long monopoly of international giants like Texas Instruments. Its low-cost, highly integrated solutions enabled millimeter-wave radar to move from luxury to mass-market vehicles. By 2025, Calterah captured a 31.1% share in China's automotive millimeter-wave radar chip market (second domestically, fourth globally), with cumulative shipments exceeding 30 million units. Its client list includes BYD, Geely, Nio, and Volvo. The company has undergone 11 funding rounds, attracting high-profile investors such as the National Integrated Circuit Industry Investment Fund Phase II, China Capital Management, and GD Capital. Its valuation has reached tens of billions of yuan, with a projected post-IPO valuation of approximately 14 billion yuan. Despite rapid revenue growth—increasing from 206 million yuan in 2023 to 632 million yuan in 2025 with a 75.28% CAGR—Calterah remains unprofitable. It reported net losses of 323 million yuan, 334 million yuan, and 193 million yuan from 2023 to 2025, accumulating over 900 million yuan in losses over three and a half years. These losses are primarily attributed to heavy R&D investment, which totaled over 1.039 billion yuan in the reporting period, often exceeding annual revenue. The company faces significant risks, including high customer concentration (its top five customers accounted for over 99% of revenue from 2023-2025, with BYD alone representing over 50% in 2025) and supply chain concentration. Revenue pressure from key customers and dependencies on overseas suppliers for EDA tools and IP pose challenges to sustainable growth. The IPO is seen as crucial for securing capital to expand production, diversify its customer base, and reduce supply chain dependencies.