Toggle light / dark theme

TSMC officially begins 2nm chip volume production in Q4 2025

Taipei, Dec. 30 (CNA) Taiwan Semiconductor Manufacturing Co. (TSMC), the world’s leading advanced chipmaker, officially began volume production of its 2-nanometer chips in the fourth quarter of 2025, according to a recent update on the company’s website.

The low-key announcement confirms that TSMC met its original roadmap for the next-generation technology. Production is currently centered at Fab 22 in Kaohsiung, utilizing the company’s first-generation nanosheet transistor technology. The new architecture achieves “full-node strides in performance and power consumption,” the website said.

The company described the 2nm process as the most advanced in the semiconductor industry in terms of transistor density and energy efficiency, adding that it is designed to “address the increasing need for energy-efficient computing,” particularly for AI and mobile applications.

Study Explores Cancer-Like Traits in Endometriosis Including Abnormal Cell Growth and Tissue Invasion

Recent studies have examined the connection between endometriosis and cancer, revealing that the condition may exhibit several traits commonly associated with malignant tumors. Researchers have identified specific characteristics of endometriosis that align with established hallmarks of cancer, prompting a reevaluation of how this chronic gynecological disorder is understood and approached in medical research.

The investigation highlights parallels between endometriosis and cancer, including features such as abnormal cell growth, resistance to cell death, and the ability to invade surrounding tissues. These findings suggest that while endometriosis is not classified as a form of cancer, it shares biological behaviors typically observed in malignancies. The study underscores the complexity of endometriosis and its potential implications for treatment strategies and further research into its underlying mechanisms.

Newsflash | powered by geneonline AI.

Tesla Cybercab is changing the look of Austin’s roads, and it’s not even in production yet

Even before entering production, Tesla’s Cybercab is already transforming the appearance of Austin’s streets, with multiple prototypes spotted testing in downtown areas recently.

Videos and photos showed the sleek, two-seat autonomous vehicles navigating traffic. Interestingly enough, the vehicles were equipped with temporary steering wheels and human safety drivers.

Over the weekend, enthusiasts captured footage of two Cybercabs driving together in central Austin, their futuristic silhouettes standing out amid regular traffic. While the vehicles featured temporary steering wheels and side mirrors for now, they retained their futuristic, production-intent exterior design.

AI models stumble on basic multiplication without special training methods, study finds

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to four-digit multiplication, a task taught in elementary school, even state-of-the-art systems fail. Why?

A new paper posted to the arXiv preprint server by University of Chicago computer science Ph.D. student Xiaoyan Bai and faculty co-director of the Data Science Institute’s Novel Intelligence Research Initiative Chenhao Tan finds answers by reverse-engineering failure and success.

They worked with collaborators from MIT, Harvard University, University of Waterloo and Google DeepMind to probe AI’s “jagged frontier”—a term for its capacity to excel at complex reasoning yet stumble on seemingly simple tasks.

Traditional Security Frameworks Leave Organizations Exposed to AI-Specific Attack Vectors

In December 2024, the popular Ultralytics AI library was compromised, installing malicious code that hijacked system resources for cryptocurrency mining. In August 2025, malicious Nx packages leaked 2,349 GitHub, cloud, and AI credentials. Throughout 2024, ChatGPT vulnerabilities allowed unauthorized extraction of user data from AI memory.

The result: 23.77 million secrets were leaked through AI systems in 2024 alone, a 25% increase from the previous year.

Here’s what these incidents have in common: The compromised organizations had comprehensive security programs. They passed audits. They met compliance requirements. Their security frameworks simply weren’t built for AI threats.

/* */