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Today, most of us carry a fairly powerful computer in our hand—a smartphone. But computers weren’t always so portable. Since the 1980s, they have become smaller, lighter, and better equipped to store and process vast troves of data. Yet the silicon chips that power computers can only get so small.

“Over the past 50 years, the number of transistors we can put on a chip has doubled every two years,” said Kun Wang, assistant professor of physics at the University of Miami College of Arts and Sciences. “But we are rapidly reaching the physical limits for silicon-based electronics, and it’s more challenging to miniaturize using the we have been using for half a century.”

It’s a problem that Wang and many in his field of molecular electronics are hoping to solve. Specifically, they are looking for a way to conduct electricity without using silicon or metal, which are used to create computer chips today. Using tiny molecular materials for functional components, like transistors, sensors, and interconnects in electronic chips offers several advantages, especially as traditional silicon-based technologies approach their physical and performance limits.

About 20% to 35% of the population suffers from chronic sleep disorders—and up to half of all people in older age. Moreover, almost every teenager or adult has experienced short-term sleep deprivation at some point. There are many reasons for not getting enough sleep, whether it be partying, a long day at work, caring for relatives, or simply whiling away time on smartphones.

In a recent meta-study, Jülich researchers have now been able to show that the involved in the short-term and long-term conditions differ significantly. The results of the study were published in the journal JAMA Psychiatry.

“Poor sleep is one of the most important—but changeable—risk factors for in adolescents and ,” says Jülich researcher and Privatdozent Dr. Masoud Tahmasian, who coordinated the study. In contrast, long-term pathological sleep disorders, such as insomnia, obstructive sleep apnea, narcolepsy, and short-term sleep deprivation, are located in different parts of the brain.

Lightweight lithium metal is a heavy-hitting critical mineral, serving as the key ingredient in the rechargeable batteries that power phones, laptops, electric vehicles and more. As ubiquitous as lithium is in modern technology, extracting the metal is complex and expensive. A new method, developed by researchers at Penn State and recently granted patent rights, enables high-efficiency lithium extraction—in minutes, not hours—using low temperatures and simple water-based leaching.

“Lithium powers the technologies that define our modern lives—from smartphones to electric vehicles—and has applications in grid energy storage, ceramics, glass, lubricants, and even medical and nuclear technologies,” said Mohammad Rezaee, the Centennial Career Development Professor in Mining Engineering at Penn State, who led the team that published their approach in Chemical Engineering Journal.

“But its extraction must also be environmentally responsible. Our research shows that we can extract lithium, and other , more efficiently while drastically reducing energy use, greenhouse gas emissions and waste that’s difficult to manage or dispose of.”

A major breakthrough at POSTECH could dramatically boost AI speeds and device efficiency.

Researchers have, for the first time, decoded how Electrochemical Random-Access Memory (ECRAM) works, using a special technique to observe internal electron behavior even at extreme temperatures. This hidden mechanism, where oxygen vacancies act like shortcuts for electrons, could unlock faster AI systems and longer-lasting smartphones, laptops, and tablets.

Breakthrough at POSTECH: boosting AI efficiency.

This week, major AI breakthroughs were announced, including Microsoft’s new Copilot agents, Sand AI’s long video generation, and Baidu’s faster, cheaper ERNIE models. Perplexity launched a voice assistant for iPhone, ByteDance introduced screen-controlling AI, and UC San Diego showed GPT-4.5 passing a real Turing Test. DeepMind warned about AI hallucinations caused by rare words, while YouTube started testing AI-generated video clips in search results.

Join our free AI content course here 👉 https://www.skool.com/ai-content-acce… the best AI news without the noise 👉 https://airevolutionx.beehiiv.com/ 🔍 What’s Inside: •⁠ ⁠Microsoft’s Copilot Wave Two introduces powerful AI agents like Researcher and Analyst •⁠ ⁠Sand AI and Sky Reels revolutionize video generation with long-form and infinite content breakthroughs •⁠ ⁠Baidu’s ERNIE Turbo models offer faster performance at lower costs, challenging OpenAI’s dominance 🎥 What You’ll See: •⁠ ⁠How AI now creates live sports commentary, animates 3D faces, and controls computers from screenshots •⁠ ⁠Why DeepMind warns about hidden risks in AI training and how UC San Diego’s research changes Turing tests •⁠ ⁠How YouTube’s AI-generated video clips and Perplexity’s new iPhone assistant could reshape online content 📊 Why It Matters: This wave of AI advancements shows how fast technology is evolving, with smarter agents, endless video creation, cheaper high-end models, and new challenges in AI reliability, content creation, and human-like behavior. DISCLAIMER: This video covers major AI updates from Microsoft, Sand AI, Baidu, Perplexity, DeepMind, and others, highlighting the rapid shifts in AI capabilities, risks, and opportunities across real-world applications. #ai #microsoft #deepmind.
Get the best AI news without the noise 👉 https://airevolutionx.beehiiv.com/

🔍 What’s Inside:
• ⁠ ⁠Microsoft’s Copilot Wave Two introduces powerful AI agents like Researcher and Analyst.
• ⁠ ⁠Sand AI and Sky Reels revolutionize video generation with long-form and infinite content breakthroughs.
• ⁠ ⁠Baidu’s ERNIE Turbo models offer faster performance at lower costs, challenging OpenAI’s dominance.

🎥 What You’ll See:
• ⁠ ⁠How AI now creates live sports commentary, animates 3D faces, and controls computers from screenshots.
• ⁠ ⁠Why DeepMind warns about hidden risks in AI training and how UC San Diego’s research changes Turing tests.
• ⁠ ⁠How YouTube’s AI-generated video clips and Perplexity’s new iPhone assistant could reshape online content.

📊 Why It Matters:
This wave of AI advancements shows how fast technology is evolving, with smarter agents, endless video creation, cheaper high-end models, and new challenges in AI reliability, content creation, and human-like behavior.

DISCLAIMER:

Lithium-ion batteries have been a staple in device manufacturing for years, but the liquid electrolytes they rely on to function are quite unstable, leading to fire hazards and safety concerns. Now, researchers at Penn State are pursuing a reliable alternative energy storage solution for use in laptops, phones and electric vehicles: solid-state electrolytes (SSEs).

According to Hongtao Sun, assistant professor of industrial and manufacturing engineering, solid-state batteries—which use SSEs instead of liquid electrolytes—are a leading alternative to traditional . He explained that although there are key differences, the batteries operate similarly at a fundamental level.

“Rechargeable batteries contain two internal electrodes: an anode on one side and a cathode on the other,” Sun said. “Electrolytes serve as a bridge between these two electrodes, providing fast transport for conductivity. Lithium-ion batteries use liquid electrolytes, while solid-state batteries use SSEs.”

In a new Nature Communications study, researchers have developed an in-memory ferroelectric differentiator capable of performing calculations directly in the memory without requiring a separate processor.

The proposed differentiator promises energy efficiency, especially for edge devices like smartphones, autonomous vehicles, and security cameras.

Traditional approaches to tasks like image processing and motion detection involve multi-step energy-intensive processes. This begins with recording data, which is transmitted to a , which further transmits the data to a microcontroller unit to perform differential operations.

Until now, Google’s Android XR glasses had only appeared in carefully curated teaser videos and limited hands-on previews shared with select publications. These early glimpses hinted at the potential of integrating artificial intelligence into everyday eyewear but left lingering questions about real-world performance. That changed when Shahram Izadi, Google’s Android XR lead, took the TED stage – joined by Nishtha Bhatia – to demonstrate the prototype glasses in action.

The live demo showcased a range of features that distinguish these glasses from previous smart eyewear attempts. At first glance, the device resembles an ordinary pair of glasses. However, it’s packed with advanced technology, including a miniaturized camera, microphones, speakers, and a high-resolution color display embedded directly into the lens.

The glasses are designed to be lightweight and discreet, with support for prescription lenses. They can also connect to a smartphone to leverage its processing power and access a broader range of apps.