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The great search divide: How AI and traditional web searches differ

As anyone who uses the internet will know, the way we find information has fundamentally changed. For the last three decades, search engines have delivered ranked lists of links in response to our queries, and it was our job to search through them to find what we wanted. Now, major search engines use generative AI tools to deliver a single coherent answer, often embedded with a few links. But how does this approach compare with the traditional method? In a comprehensive new study, scientists compared these two approaches to see what we are gaining and losing.

To figure this out, researchers from Ruhr University Bochum and the Max Planck Institute for Software Systems compared traditional Google Search with four generative search engines: Google AI Overview (AIO), Gemini, GPT-4o-Search and GPT-4o with Search Tool. The team ran thousands of queries covering six main areas, including general knowledge, politics, science and shopping.

Then they made a detailed comparison of the two search styles based on three key metrics. First, they analyzed source diversity by checking the websites AI used against traditional search’s top links. Second, they measured knowledge reliance to see how much AI relied on its own rather than searching the web for fresh information.

Scalable approach to 6G wireless offers speed and reliability

A team from the University of California San Diego and Rensselaer Polytechnic Institute has invented a scalable technology that enables faster and more reliable 5G and 6G wireless communication.

“With our approach, we can support maybe 10 times more devices than before using the same bandwidth,” said Ish Kumar Jain, an assistant professor at Rensselaer Polytechnic Institute and alumnus of the UC San Diego Jacobs School of Engineering. “It also helps reduce latency (the delay in accessing the network) and maintains an extremely high data rate with all connected devices.”

The technique, dubbed FlexLink (patent pending), was co-developed by Dinesh Bharadia, associate professor with the Jacobs School of Engineering and affiliate of the Qualcomm Institute at UC San Diego, along with UC San Diego Ph.D. student Rohith Reddy Vennam.

Size doesn’t matter: Just a small number of malicious files can corrupt LLMs of any size

Large language models (LLMs), which power sophisticated AI chatbots, are more vulnerable than previously thought. According to research by Anthropic, the UK AI Security Institute and the Alan Turing Institute, it only takes 250 malicious documents to compromise even the largest models.

The vast majority of data used to train LLMs is scraped from the public internet. While this helps them to build knowledge and generate natural responses, it also puts them at risk from data poisoning attacks. It had been thought that as models grew, the risk was minimized because the percentage of poisoned data had to remain the same. In other words, it would need massive amounts of data to corrupt the largest models. But in this study, which is published on the arXiv preprint server, researchers showed that an attacker only needs a small number of poisoned documents to potentially wreak havoc.

To assess the ease of compromising large AI models, the researchers built several LLMs from scratch, ranging from small systems (600 million parameters) to very large (13 billion parameters). Each model was trained on vast amounts of clean public data, but the team inserted a fixed number of malicious files (100 to 500) into each one.

Cyber defense innovation could significantly boost 5G network security

A framework for building tighter security into 5G wireless communications has been created by a Ph.D. student working with the University of Portsmouth’s Artificial Intelligence and Data Center.

With its greater network capacity and ability to rapidly transmit huge amounts of information from one device to another, 5G is a critical component of intelligent systems and services—including those for health care and financial services.

However, the dynamic nature of 5G networks, the high volumes of data shared and the ever changing types of information transmitted means that these networks are extremely vulnerable to cyber threats and increasing risks of attack.

Streamlined method to directly generate photons in optical fiber could secure future quantum internet

With the rise of quantum computers, the security of our existing communication systems is at risk. Quantum computers will be able to break many of the encryption methods used in current communication systems. To counter this, scientists are developing quantum communication systems, which utilize quantum mechanics to offer stronger security. A crucial building block of these systems is a single-photon source: a device that generates only one light particle at a time.

These photons, carrying quantum information, are then sent through optical fibers. For to work, it is essential that single photons are injected into optical fibers with extremely low loss.

In conventional systems, single-photon emitters, like and rare-earth (RE) element ions, are placed outside the fiber. These photons then must be guided to enter the fiber. However, not all photons make it into the fibers, causing high transmission loss. For practical quantum communication systems, it is necessary to achieve a high-coupling and channeling efficiency between the and the emitter.

How do you trust a robot you’ve never met?

Many of the environments where human-facing universal robots can provide benefits — homes, hospitals, schools — are sensitive and personal. A tutoring robot helping your kids with math should have a track record of safe and productive sessions. An elder-care assistant needs a verifiable history of respectful, competent service. A delivery robot approaching your front door should be as predictable and trustworthy as your favorite mail carrier. Without trust, adoption will never take place, or quickly stall.

Trust is built gradually and also reflects common understanding. We design our systems to be explainable: multiple AI modules talk to each other in plain language, and we log their thinking so humans can audit decisions. If a robot makes a mistake — drops the tomato instead of placing it on the counter — you should be able to ask why and get an answer you can understand.

Over time, as more robots connect and share skills, trust will depend on the network too. We learn from peers, and machines will learn from us and from other machines. That’s powerful but just like parents are concerned about what their kids learn on the web, we need good ways to audit and align skill exchange for robots… Governance for human–machine societies isn’t optional; it’s fundamental infrastructure.

Super-thin semiconductor overcomes trade-off between speed and thermal stability

A team led by academician Huang Ru and Professor Wu Yanqing from the School of Integrated Circuits at Peking University has developed a super-thin, high-performance semiconductor with enhanced heat conductivity, enabled by a silicon carbide (SiC) substrate. The research, published in Nature Electronics under the title “Amorphous indium tin oxide transistors for power amplification above 10 GHz,” marks a significant step forward in next-generation radio-frequency (RF) electronics.

Amorphous oxide semiconductors (AOS) enable low-temperature, large-area, and chip-compatible processing with . However, their inherently low thermal conductivity leads to self-heating effects, which limit top-gate scaling and high-frequency operation in applications such as 5G communications and the Internet of Things. Overcoming this trade-off between speed and thermal stability remains a central challenge.

This breakthrough using a SiC substrate overcomes the trade-off between speed and in AOS, paving the way for low-cost, flexible, and chip-compatible RF electronics. It demonstrates how combining high-frequency design with effective thermal management can deliver both performance and reliability in high-speed devices.

The Dyson Sphere Economy — Mega Structures, Mega Markets, and Mega-Wealth

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A Dyson Swarm isn’t just power—it’s prosperity. See how humanity could turn a star’s energy into a solar-scale economy of trillions.

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Credits:
The Dyson Economy — Mega-Structures, Mega-Markets, and Mega-Wealth.
Produced, Narrated & Written: Isaac Arthur.
Editor: Jonathan Maltz.
Editor: Thomas Owens.
Graphics: Bryan Versteeg, Jeremy Jozwik, Ken York, Sergio Botero, Udo Schroeter.
Select imagery/video supplied by Getty Images.
Music Courtesy of Stellardrone & Epidemic Sound http://epidemicsound.com/creator.

Chapters.
0:00 Intro.
0:09 The Vision of the Space Elevator.
2:46 The Rope That Reaches the Sky.
9:08 Manufacturing the Megastructure.
12:58 Tether Design and Variants.
19:57 PIA
21:52 Defects and Composites: Strength in Layers.
22:48 Power and Payload.
25:20 Safety, Scaling, and the Road Ahead.

Harnessing GeSn semiconductors for tomorrow’s quantum world

An international team of researchers from Forschungszentrum Jülich (Germany), Tohoku University (Japan), and École Polytechnique de Montréal (Canada) has made a significant discovery in semiconductor science by revealing the remarkable spin-related material properties of Germanium-Tin (GeSn) semiconductors.

Semiconductors control the flow of electricity that power everyday technology all around us (such as cars and computers). However, technology is progressing at such a breakneck speed that it is straining current technologies.

“Semiconductors are approaching their physical and energy-efficiency limits in terms of speed, performance, and ,” says Makoto Kohda from Tohoku University. “This is a huge issue because we need semiconductors that can keep up as we shift to more demanding needs such as 5G/6G networks and the increased use of artificial intelligence.”

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