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Asian Tech Stocks Retreat As AI Sell-Off Spreads

Technology stocks across Asia fell on Thursday, extending the weakness seen on Wall Street as investors continued to reassess valuations in the AI sector.

The sharpest losses came from semiconductor companies. South Korea’s SK Hynix dropped nearly 10%, while Samsung Electronics fell more than 6%. In Japan, SoftBank Group lost 4.4%, Tokyo Electron declined more than 5%, Advantest fell 2.1%, and memory chipmaker Kioxia slid almost 9%. Taiwan Semiconductor Manufacturing Co. (TSMC), the world’s largest contract chipmaker, also traded lower.

The decline followed a strong rally a day earlier, highlighting the heightened volatility that has become a defining feature of AI-related stocks.

AI Investment Outlook Remains Intact

Despite the market pullback, analysts say the sector’s long-term fundamentals remain unchanged.

J.P. Morgan said recent selling across Asian technology shares does not signal a weakening AI investment cycle. While investors have questioned whether major technology companies can sustain record levels of AI spending, the bank does not expect hyperscalers to scale back their capital expenditure.

“Stepping away from the share price moves, we do not see any fundamental indicators that signal meaningful weakness in the next 6-12 months,” the bank said.

Demand Continues To Support The Sector

A separate report from S&P Global pointed to continued strength in technology demand, driven largely by artificial intelligence and defence spending.

According to the report, global output in the technology equipment sector expanded in July at its fastest pace since May 2021, while software and IT services also recorded their strongest growth in ten months.

The latest market moves suggest investors remain sensitive to short-term shifts in sentiment. Even so, analysts continue to view AI as one of the strongest long-term drivers of demand for semiconductor manufacturers and technology companies.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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