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TSMC reduces peak power consumption of EUV tools by 44% — company to save 190 million kilowatt-hours of electricity by 2030

TSMC is also exploring the possibility of applying similar dynamic energy control mechanisms to other lithography equipment, including DUV scanners, as well as additional modules outside the lithography sector.

While TSMC did not reveal what, exactly, its EUV Dynamic Energy Saving Program involves, that it is applicable to DUV systems and other machinery means that it does not exploit EUV-specific peculiarities. For example, the program could implement adaptive power scaling based on real-time operational status. If wafers are not queued for immediate processing, the EUV tool could intelligently pause or shift to a low-power state rather than continuously consume full power. Such an approach would require real-time data exchange across the cleanroom as well as optimizations on process/production flow levels (though, we are speculating).

TSMC has been increasing the power efficiency of its EUV fab tools — which are notorious for their power consumption — for years, now. In mid-2024, the company announced that it had though without disclosing what exactly had been done…

‘Embodied’ AI in virtual reality improves programming student confidence

Researchers have found that giving AI “peers” in virtual reality (VR) a body that can interact with the virtual environment can help students learn programming. Specifically, the researchers found students were more willing to accept these “embodied” AI peers as partners, compared to voice-only AI, helping the students better engage with the learning experience.

“Using AI agents in a VR setting for teaching students programming is a relatively recent development, and this proof-of-concept study was meant to see what kinds of AI agents can help students learn better and work more effectively,” says Qiao Jin, corresponding author of a paper on the work and an assistant professor of computer science at North Carolina State University.

“Peer learning is widespread in the programming field, as it helps students engage in the . For this work, we focused on ‘pAIr’ learning, where the programming peer is actually an AI agent. And the results suggest that embodying AI in the VR environment makes a real difference for pAIr learning.”

Most effective digital interventions to stop smoking identified

Smoking remains one of the most deleterious habits for human health, as it is known to increase the risk of several life-threatening diseases, including lung and throat cancers, heart disease and strokes. While most smokers are well aware of its associated health risks, ceasing this habit can be a very difficult process.

Moreover, conventional programs for cessation, such as those based on psychotherapy or , are not financially or physically accessible for all individuals who wish to stop smoking. In recent years, behavioral scientists and psychologists have been working with engineers to create digital interventions that support people in their efforts to quit this unhealthy habit.

Researchers at Sichuan University in China have carried out a and meta-analysis of past research studies investigating the effectiveness of various digital interventions for smoking cessation. The results of their analyses, presented in a paper published in Nature Human Behavior, suggest that personalized and group-customized technology-based programs could be particularly beneficial for smokers who wish to quit, with middle-aged individuals responding better than younger populations.

Brain shape changes could offer early warning signs of dementia

A new study led by University of California, Irvine’s Center for the Neurobiology of Learning and Memory researchers found that aging changes the brain’s overall shape in measurable ways. Instead of focusing only on the size of specific regions, the team used a new analytic method to see how the brain’s form shifts and distorts over time.

The analysis revealed substantial alterations in brain shape, which were closely associated with declines in memory, reasoning and other cognitive functions. This suggests that the shape of the brain can serve as a reliable indicator of its overall health. The study appears in Nature Communications.

“Most studies of brain aging focus on how much tissue is lost in different regions,” said Niels Janssen, Ph.D., senior author and professor at Universidad de La Laguna in Spain and visiting faculty at the CNLM. “What we found is that the overall shape of the brain shifts in systematic ways, and those shifts are closely tied to whether someone shows cognitive impairment.”

TSMC Fast-Tracks Production of Cutting-Edge Nodes in The US, With A16 (1.6nm) To Now Debut a Year Earlier Amid US-Taiwan Parity Pressure

TSMC plans to accelerate US manufacturing, with its new Arizona fab now expected to introduce high-end nodes, such as the A16, significantly ahead of the original timeline.

For those unaware, there’s still a concern by the US administration around TSMC’s operations in the US and Taiwan, and according to Commerce Secretary Howard Lutnick, the USG is now demanding that TSMC produce ‘50% of its total chip capacity’ in America, to ensure that the nation is safeguarded from geopolitical tensions between China and Taiwan. According to a report by the Taiwan Economic Daily, the new Arizona Fab 3 is set to introduce 2nm and A16 in America by 2027, a year ahead of the original timeline.

TSMC is currently pursuing mass production of 4nm in its Arizona facility, and 3nm production lines are also being laid, with production expected to commence by year-end. More importantly, TSMC plans to introduce both 2nm and A16 (1.6nm) with TSMC’s fourth Arizona fab by 2027, which means that relative to Taiwan, the US will just be a year behind, which is a considerable progress in just a span of ‘few months’. In general, TSMC’s 2nm production is slated for next quarter, while A16 will be introduced around H2 2026.

Teams with budding researchers are more likely to drive scientific disruption, new study finds

Scientific research apparently has its own share of beginner’s luck. According to a study by Mahdee Mushfique Kamal and Raiyan Abdul Baten, teams with a larger number of newbies take the cake when it comes to transformative scientific research. Their study examined 28 million articles spanning five decades of scientific publications to understand how beginner authors drive scientific advancement.

The duo developed what they call a disruption score, ranging from-1 to +1. A score closer to-1 indicates that a paper mainly reinforces existing knowledge and builds directly on established work. On the other end of the spectrum lies +1, which signals a disruptive paper which has the ability to shift the direction of science by opening new paths and making previous work less central.

They observed a universal phenomenon known as the “beginner’s charm,” where teams with higher fractions of beginner authors systematically produced more disruptive and innovative scientific work. Teams with more senior members produce less disruptive work, and this negative correlation was strong.

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