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Is ASML nearing a growth ceiling or gearing up for another breakthrough?

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Shares of Dutch chip-equipment maker ASML have surged to record levels, reigniting debate among investors over whether the company is approaching its growth limits or entering a new phase of expansion fueled by artificial intelligence demand. The stock initially jumped after strong fourth-quarter results before reversing course, highlighting how stretched expectations around the company have become.

ASML has been one of the biggest beneficiaries of the AI boom, as its extreme ultraviolet lithography machines are essential for producing advanced chips used by companies such as TSMC and Nvidia. Shares are up sharply this month and trade at elevated valuation multiples, reflecting optimism about future growth but also raising concerns that much of the good news is already priced in.

The company’s order backlog stands at nearly 39 billion euros, yet each machine can take up to a year to build, prompting questions about capacity constraints. ASML management has said it does not expect to become a bottleneck for the semiconductor industry, even as customers plan major capacity expansions over the coming years.

Supporters argue that long-term demand from AI, data centers, and advanced manufacturing will continue to drive growth, while skeptics caution that high valuations leave little room for disappointment. The debate underscores ASML’s central role in the global chip supply chain and the fine balance between exceptional growth prospects and lofty investor expectations.

US software stocks slide as AI disruption fears intensify

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U.S. software stocks fell sharply on Thursday as disappointing outlooks from major players deepened investor concerns that traditional software providers are being overtaken by artificial intelligence-driven competitors. Weak sentiment was triggered after Germany-based SAP issued an underwhelming cloud outlook, while ServiceNow shares dropped despite forecasting stronger subscription revenue.

Investors are increasingly worried that advances in AI, including the rapid and low-cost generation of software code and applications, could undermine the subscription-based software-as-a-service business model. Several high-profile U.S. firms saw steep losses, including Salesforce, Adobe, and Datadog, as the sell-off spread across the sector.

The pressure was compounded by concerns over heavy AI spending. Microsoft reported record AI investment alongside slower cloud growth, sending its shares sharply lower. Analysts said markets are pricing in a worst-case scenario in which AI fundamentally reshapes the software industry faster than incumbents can adapt.

Software stocks were among the biggest decliners on the Nasdaq, while chipmakers and memory firms continued to benefit from AI-driven demand, highlighting a widening divide between hardware and software winners in the AI race.

Open-source AI models exposed to criminal misuse, researchers warn

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Open-source artificial intelligence models are increasingly vulnerable to criminal misuse, as hackers can take control of computers running large language models outside the safeguards used by major AI platforms, according to new research released on Thursday. Researchers warned that compromised systems could be used for spam campaigns, phishing, disinformation, fraud, and other illicit activities while evading standard security controls.

The study was conducted over 293 days by cybersecurity firms SentinelOne and Censys, and examined thousands of internet-accessible deployments of open-source large language models. The researchers identified a wide range of potentially harmful use cases, including hacking, harassment, hate speech, theft of personal data, scams, and in some instances severe illegal content. They said hundreds of models appeared to have safety guardrails deliberately removed.

While thousands of open-source AI variants exist, a significant share of publicly accessible systems were based on models such as Meta’s Llama and Google DeepMind’s Gemma. The analysis focused on models deployed using Ollama, a tool that allows organizations to run their own AI systems. System prompts were visible in about a quarter of observed deployments, and 7.5% of those prompts could potentially enable harmful activity.

Researchers said roughly 30% of the identified systems were hosted in China and about 20% in the United States. Industry experts stressed that responsibility for mitigating risks must be shared across developers, deployers, and security teams, warning that unchecked open-source capacity poses growing global security concerns.