Unexplainable Radio Waves Under Antarctica’s Ice Defy the Laws of Particle Physics

https://www.discovermagazine.com/the-sciences/unexplainable-radio-waves-under-antarcticas-ice-defy-the-laws-of-particle

Strange pulses that don’t seem to abide by the laws of particle physics have been detected in Antarctica. These radio waves, emanating from below the ice, could be evidence of dark matter and have been puzzling scientists since their discovery.

The new study, published in Physical Review Letters, provides details about these strange signals. In Antarctica, radio waves are often detected after being reflected off the ice. These recent waves, however, appear to be coming from beneath the ice, a location that can’t be explained by physics and may suggest a new, previously unseen type of particle.

“The radio waves that we detected were at really steep angles, like 30 degrees below the surface of the ice,” said Stephanie Wissel, associate professor of physics, astronomy, and astrophysics at Penn State, in a press release. “It’s an interesting problem because we still don’t actually have an explanation for what these anomalies are, but what we do know is that they’re most likely not representing neutrinos.”


Read More: What the Mysterious Bloop Taught Us About Antarctica


Detecting Strange Signals in Antarctica

The strange signals were detected by the Antarctic Impulsive Transient Antenna (ANITA) experiment. ANITA is a collection of scientific instruments flown high above the Antarctic on balloons. These instruments are designed to detect radio waves that occur as a result of cosmic rays hitting the atmosphere. 

Normally, the radio waves hoping to be detected by ANITA are made up of neutrinos. Neutrinos are very common and incredibly small, being the subatomic particle with the smallest mass. Due to them being so small, they are also famously hard to find and require sophisticated detection instruments like ANITA. 

“You have a billion neutrinos passing through your thumbnail at any moment, but neutrinos don’t really interact. So, this is the double-edged sword problem. If we detect them, it means they have traveled all this way without interacting with anything else. We could be detecting a neutrino coming from the edge of the observable universe,” said Wissel in the press release.

Although difficult to detect, the payoff is big. Even the tiniest signal from a neutrino contains tons of important information. Once a signal has been detected, you can follow it back to its source, and it can tell scientists more about the cosmos than even the most high-powered telescopes. 

Neutrinos Vs. Anomalies 

When it comes to the physics of it all, neutrino signals are easy to trace back to their origin because they work similarly to a bouncing ball — no matter what angle a ball is thrown, we can always predict that it will bounce back at that same angle. 

The newly detected signal does not behave in this predictable way, as its strange angle is much sharper than anything observed before. This led the ANITA team to declare that these signals were not neutrinos and are instead what is known as anomalous. 

Anomalous signals, like the ones picked up in Antarctica, do not behave in a way predictable or understandable through current models of particle physics. Although scientists have yet to figure out what these signals are or where they came from, there are some theories, including the idea that these signals could be hinting at the presence of dark matter.

The research team is currently working on the design process for an even bigger and better detector than ANITA. Their hope is that, once built, the new detector will be able to provide more information on the strange, anomalous signal from deep below the Antarctic ice.

“I’m excited that when we fly [the new detector], we’ll have better sensitivity. In principle, we should pick up more anomalies, and maybe we’ll actually understand what they are. We also might detect neutrinos, which would in some ways be a lot more exciting,” said Wissel in the press release.


Read More: The Deep Underground Neutrino Experiment Could Answer Profound Cosmic Questions


Article Sources

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As the marketing coordinator at Discover Magazine, Stephanie Edwards interacts with readers across Discover’s social media channels and writes digital content. Offline, she is a contract lecturer in English & Cultural Studies at Lakehead University, teaching courses on everything from professional communication to Taylor Swift, and received her graduate degrees in the same department from McMaster University. You can find more of her science writing in Lab Manager and her short fiction in anthologies and literary magazine across the horror genre.

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June 16, 2025 at 05:00PM

Tesla blows past stopped school bus and hits kid-sized dummies in Full Self-Driving tests

https://www.engadget.com/transportation/tesla-blows-past-stopped-school-bus-and-hits-kid-sized-dummies-in-full-self-driving-tests-183756251.html?src=rss

A revealing demonstration with Tesla’s Full Self-Driving mode is raising concerns about whether fully autonomous cars are ready to hit the streets. Tesla has reportedly pushed back the rollout of its upcoming all-electric, fully autonomous car called the Cybercab, while a recent demonstration in Austin, Texas showed a Tesla Model Y running through a school bus’ flashing lights and stop signs, and hitting child-size mannequins. The tests were conducted by The Dawn Project, along with Tesla Takedown and ResistAustin, and showed Tesla’s Full Self-Driving software repeating the same mistake eight times.

It’s worth noting that Tesla’s autonomous driving feature is formally known as Full Self-Driving (Supervised) and "requires a fully attentive driver and will display a series of escalating warnings requiring driver response." Tesla even has a warning that says, "failure to follow these instructions could cause damage, serious injury or death." However, it’s not the first time that Tesla’s FSD software has found itself in hot water. The Dawn Project, whose founder Dan O’Dowd is the CEO of a company that offers competing automated driving system software, previously took out ads warning about the dangers of Tesla’s Full Self-Driving and how it would fail to yield around school buses. In April 2024, a Model S using Full Self-Driving was involved in a crash in Washington, where a motorcyclist died.

With anticipation building up for an eventual Cybercab rollout on June 22, the company’s CEO posted some additional details on X. According to Elon Musk, Tesla is "being super paranoid about safety, so the date could shift." Beyond that, Musk also posted that the "first Tesla that drives itself from factory end of line all the way to a customer house is June 28."

This article originally appeared on Engadget at https://ift.tt/W8wsFJV

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June 15, 2025 at 01:45PM

The Viral Storm Streamers Predicting Deadly Tornadoes—Sometimes Faster Than the Government

https://www.wired.com/story/the-viral-storm-streamers-predicting-deadly-tornadoes-sometimes-faster-than-the-government/

Storm streamers are using radars and AI robots to predict extreme weather for millions of YouTube subscribers, in some cases faster than the National Weather Service, which has been gutted by DOGE.

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June 11, 2025 at 06:37AM

These Hyundai Robots Park Cars Like Ballerinas, But With More Lifting Power!

https://www.geeksaresexy.net/2025/06/07/these-hyundai-robots-park-cars-like-ballerinas-but-with-more-lifting-power/

Robots Park Car

Hyundai’s parking robots may not be new, but they’re still stealing the show like it’s opening night of Fast & the Fabulous. In this video from their smart office building in Seoul, these little machines prance around the parking lot like they just graduated from robot ballet school with honors, parking cars better than most humans can. Check it out!

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June 7, 2025 at 05:18AM

You can use an iPhone as a Nintendo Switch 2 camera

https://www.engadget.com/gaming/nintendo/you-can-use-an-iphone-as-a-nintendo-switch-2-camera-142622005.html?src=rss

Maybe you’ve just picked up a Nintendo Switch 2 and want to try GameChat features with your friends in Mario Kart World, but can’t quite swing $55 for the official camera right now after plopping down $500 for the console and game bundle. The solution might be in your pocket.

The Switch 2 supports third-party USB-C webcams. However, you might be able to use your phone instead. YouTube channel Will It Work? has demonstrated how to use an iPhone as a camera for the console.

Unfortunately, it’s not quite as simple as opening the iPhone’s Camera app, plugging a USB-C cable into both devices and setting up the phone (perhaps on a MagSafe charger) so it points at your mug. I tried that, and nope, no dice. Instead, if you plug the cable into a USB-C to HDMI adapter, and that into an HDMI capture cable and hook the daisy chain into your Switch 2, your new console should recognize your phone as a camera. This process may work for Android devices too.

Since doing this will pipe whatever’s on your phone’s screen into your Switch 2, you might want to use an app that hides all of the on-screen camera controls and only shows what the selfie lens or rear-facing array picks up. There are a few free options in the App Store that can do the trick. You can check that this all works by opening up the Settings on your Switch 2 and going to Controllers & Accessories > Test USB Camera.

Links in the YouTube video that demonstrates this workaround point to Amazon listings where you can pick up the two cables for $31, but you may be able to find cheaper versions. Of course, that’s moot if you already have both cables. A regular capture card and HDMI to USB-C cable might work too. Naturally, if you have a USB-C webcam handy, that’s an easier way to go about all this.

There is one downside to note before you use your iPhone as a Switch 2 camera, as Will It Work? points out. There may be some lag, which could affect lip sync. But if you can live with that, this might be an option for you.

There’s another accessory you might already have on hand that could save you from buying an official Nintendo or third-party one. The Switch 2 fits into the Steam Deck’s case. You might want to add some padding, as the Switch 2 is a smaller device than the Steam Deck and might shift around in the case otherwise, but it’s still perhaps worth considering.

This article originally appeared on Engadget at https://ift.tt/j9VuxgI

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June 6, 2025 at 09:34AM

100-Year-Old Math Problem Broken, Helping to Improve Wind Turbine Efficiency

https://www.discovermagazine.com/the-sciences/100-year-old-math-problem-broken-helping-to-improve-wind-turbine-efficiency

An undergraduate student at Penn State University discovered a new approach to a century-old problem, and in doing so made it easier for engineers to develop more efficient wind turbines.

The real world is frighteningly complex, and physicists like to start with this simplest approximation to the problem to make headway, and then add refinements as needed. In the case of wind turbines, the first attempt to determine their optimization was made by Hermann Glauert, a British aerodynamicist, in the early 20th century.

Optimization is crucial for wind turbines because for a given set of materials with certain properties like stiffness and weight, we want the turbines to get the maximum amount of electricity possible out. Glauert’s solution gave an answer, but it essentially assumed that wind turbines were solid discs and did not respond to the myriads of forces that they encountered in actual operation.

Since then there have been many attempts to refine Glauert’s model, but recently an undergraduate student at Pennsylvania State, Divya Tyagi, made a radical leap. In a paper appearing in Wind Energy Science, Tyagi found a much simpler way to add more complexity and more sophistication to the solution.

Calculus of Variations

Tyagi employed a technique called the calculus of variations. In normal calculus, you take some unknown parameter of the problem and vary it to see how the problem responds. This can help you find optimal solutions for that problem. But what if you don’t know the problem ahead of time?

That’s where the calculus of variations come in. Instead of varying a single perimeter of the problem, you vary the entire mathematical function that describes whole range of possible problems. The goal is to end up with a single equation that is the optimal answer for as broad a class of situations as possible.


Read More: Mathematical Solution Found For Jigsaw Problem We’ve All Faced


Improving Wind Turbines

Using this technique, Tyagi rewrote Glauert’s original solution. Plus, it allowed Tyagi to extend that solution to more complicated scenarios. In particular, Tyagi included the effects of the air wind blowing on the rotor turbine blades, known as downwind thrust. Tyagi’s result also includes the effects of the rotor blades bending at their roots due to that wind pressure.

Tyagi was able to create a derive a single equation that folds in multiple components that matter to real life turbines. This straightforward solution allows engineers out in the field to design as efficient a turbine as possible. This is absolutely crucial for wind power, as even a one percent improvement can make a tremendous difference.

And, as an added bonus, wind turbines aren’t solid discs anymore.


Read More: Low-Toxic Technique Could Help Recycle Wind Turbine Blades


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Our writers at Discovermagazine.com use peer-reviewed studies and high-quality sources for our articles, and our editors review for scientific accuracy and editorial standards. Review the sources used below for this article:


Paul M. Sutter is a theoretical cosmologist, NASA advisor, host of the "Ask a Spaceman" podcast, and a U.S. Cultural Ambassador. He is the author of Your Place in the Universe and How to Die in Space.

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June 6, 2025 at 09:30AM

Manus has kick-started an AI agent boom in China

https://www.technologyreview.com/2025/06/05/1117958/china-ai-agent-boom/

Last year, China saw a boom in foundation models, the do-everything large language models that underpin the AI revolution. This year, the focus has shifted to AI agents—systems that are less about responding to users’ queries and more about autonomously accomplishing things for them. 

There are now a host of Chinese startups building these general-purpose digital tools, which can answer emails, browse the internet to plan vacations, and even design an interactive website. Many of these have emerged in just the last two months, following in the footsteps of Manus—a general AI agent that sparked weeks of social media frenzy for invite codes after its limited-release launch in early March

These emerging AI agents aren’t large language models themselves. Instead, they’re built on top of them, using a workflow-based structure designed to get things done. A lot of these systems also introduce a different way of interacting with AI. Rather than just chatting back and forth with users, they are optimized for managing and executing multistep tasks—booking flights, managing schedules, conducting research—by using external tools and remembering instructions. 

China could take the lead on building these kinds of agents. The country’s tightly integrated app ecosystems, rapid product cycles, and digitally fluent user base could provide a favorable environment for embedding AI into daily life. 

For now, its leading AI agent startups are focusing their attention on the global market, because the best Western models don’t operate inside China’s firewalls. But that could change soon: Tech giants like ByteDance and Tencent are preparing their own AI agents that could bake automation directly into their native super-apps, pulling data from their vast ecosystem of programs that dominate many aspects of daily life in the country. 

As the race to define what a useful AI agent looks like unfolds, a mix of ambitious startups and entrenched tech giants are now testing how these tools might actually work in practice—and for whom.

Set the standard

It’s been a whirlwind few months for Manus, which was developed by the Wuhan-based startup Butterfly Effect. The company raised $75 million in a funding round led by the US venture capital firm Benchmark, took the product on an ambitious global roadshow, and hired dozens of new employees. 

Even before registration opened to the public in May, Manus had become a reference point for what a broad, consumer?oriented AI agent should accomplish. Rather than handling narrow chores for businesses, this “general” agent is designed to be able to help with everyday tasks like trip planning, stock comparison, or your kid’s school project. 

Unlike previous AI agents, Manus uses a browser-based sandbox that lets users supervise the agent like an intern, watching in real time as it scrolls through web pages, reads articles, or codes actions. It also proactively asks clarifying questions, supports long-term memory that would serve as context for future tasks.

“Manus represents a promising product experience for AI agents,” says Ang Li, cofounder and CEO of Simular, a startup based in Palo Alto, California, that’s building computer use agents, AI agents that control a virtual computer. “I believe Chinese startups have a huge advantage when it comes to designing consumer products, thanks to cutthroat domestic competition that leads to fast execution and greater attention to product details.”

In the case of Manus, the competition is moving fast. Two of the most buzzy follow?ups, Genspark and Flowith, for example, are already boasting benchmark scores that match or edge past Manus’s. 

Genspark, led by former Baidu executives Eric?Jing and Kay?Zhu, links many small “super agents” through what it calls multi?component prompting. The agent can switch among several large language models, accepts both images and text, and carries out tasks from making slide decks to placing phone calls. Whereas Manus relies heavily on Browser Use, a popular open-source product that lets agents operate a web browser in a virtual window like a human, Genspark directly integrates with a wide array of tools and APIs. Launched in April, the company says that it already has over 5 million users and over $36 million in yearly revenue.

Flowith, the work of a young team that first grabbed public attention in April 2025 at a developer event hosted by the popular social media app Xiaohongshu, takes a different tack. Marketed as an “infinite agent,” it opens on a blank canvas where each question becomes a node on a branching map. Users can backtrack, take new branches, and store results in personal or sharable “knowledge gardens”—a design that feels more like project management software (think Notion) than a typical chat interface. Every inquiry or task builds its own mind-map-like graph, encouraging a more nonlinear and creative interaction with AI. Flowith’s core agent, NEO, runs in the cloud and can perform scheduled tasks like sending emails and compiling files. The founders want the app to be a “knowledge marketbase”, and aims to tap into the social aspect of AI with the aspiration of becoming “the OnlyFans of AI knowledge creators”.

What they also share with Manus is the global ambition. Both Genspark and Flowith have stated that their primary focus is the international market.

A global address

Startups like Manus, Genspark, and Flowith—though founded by Chinese entrepreneurs—could blend seamlessly into the global tech scene and compete effectively abroad. Founders, investors, and analysts that MIT Technology Review has spoken to believe Chinese companies are moving fast, executing well, and quickly coming up with new products. 

Money reinforces the pull to launch overseas. Customers there pay more, and there are plenty to go around. “You can price in USD, and with the exchange rate that’s a sevenfold multiplier,” Manus cofounder?Xiao?Hong quipped on a podcast. “Even if we’re only operating at 10% power because of cultural differences overseas, we’ll still make more than in China.”

But creating the same functionality in China is a challenge. Major US AI companies including OpenAI and Anthropic have opted out of mainland China because of geopolitical risks and challenges with regulatory compliance. Their absence initially created a black market as users resorted to VPNs and third-party mirrors to access tools like ChatGPT and Claude. That vacuum has since been filled by a new wave of Chinese chatbots—DeepSeek, Doubao, Kimi—but the appetite for foreign models hasn’t gone away. 

Manus, for example, uses Anthropic’s Claude?Sonnet—widely considered the top model for agentic tasks. Manus cofounder?Zhang?Tao has repeatedly praised Claude’s ability to juggle tools, remember contexts, and hold multi?round conversations—all crucial for turning chatty software into an effective executive assistant.

But the company’s use of Sonnet has made its agent functionally unusable inside China without a VPN. If you open Manus from a mainland IP address, you’ll see a notice explaining that the team is “working on integrating Qwen’s model,” a special local version that is built on top of Alibaba’s open-source model. 

An engineer overseeing ByteDance’s work on developing an agent, who spoke to MIT Technology Review anonymously to avoid sanction, said that the absence of Claude?Sonnet models “limits everything we do in China.” DeepSeek’s open models, he added, still hallucinate too often and lack training on real?world workflows. Developers we spoke with rank Alibaba’s Qwen series as the best domestic alternative, yet most say that switching to Qwen knocks performance down a notch.

Jiaxin?Pei, a postdoctoral researcher at Stanford’s Institute for Human?Centered AI, thinks that gap will close: “Building agentic capabilities in base LLMs has become a key focus for many LLM builders, and once people realize the value of this, it will only be a matter of time.”

For now, Manus is doubling down on audiences it can already serve. In a written response, the company said its “primary focus is overseas expansion,” noting that new offices in San Francisco, Singapore, and Tokyo have opened in the past month.

A super?app approach

Although the concept of AI agents is still relatively new, the consumer-facing AI app market in China is already crowded with major tech players. DeepSeek remains the most widely used, while ByteDance’s Doubao and Moonshot’s Kimi have also become household names. However, most of these apps are still optimized for chat and entertainment rather than task execution. This gap in the local market has pushed China’s big tech firms to roll out their own user-facing agents, though early versions remain uneven in quality and rough around the edges. 

ByteDance is testing Coze?Space, an AI agent based on its own Doubao model family that lets users toggle between “plan” and “execute” modes, so they can either directly guide the agent’s actions or step back and watch it work autonomously. It connects up to 14 popular apps, including GitHub, Notion, and the company’s own Lark office suite. Early reviews say the tool can feel clunky and has a high failure rate, but it clearly aims to match what Manus offers.

Meanwhile, Zhipu?AI has released a free agent called AutoGLM?Rumination, built on its proprietary ChatGLM models. Shanghai?based Minimax has launched Minimax?Agent. Both products look almost identical to Manus and demo basic tasks such as building a simple website, planning a trip, making a small Flash game, or running quick data analysis.

Despite the limited usability of most general AI agents launched within China, big companies have plans to change that. During a May?15 earnings call, Tencent president Liu?Zhiping teased an agent that would weave automation directly into China’s most ubiquitous app, WeChat. 

Considered the original super-app, WeChat already handles messaging, mobile payments, news, and millions of mini?programs that act like embedded apps. These programs give Tencent, its developer, access to data from millions of services that pervade everyday life in China, an advantage most competitors can only envy.

Historically, China’s consumer internet has splintered into competing walled gardens—share a Taobao link in WeChat and it resolves as plaintext, not a preview card. Unlike the more interoperable Western internet, China’s tech giants have long resisted integration with one another, choosing to wage platform war at the expense of a seamless user experience.

But the use of mini?programs has given WeChat unprecedented reach across services that once resisted interoperability, from gym bookings to grocery orders. An agent able to roam that ecosystem could bypass the integration headaches dogging independent startups.

Alibaba, the e-commerce giant behind the Qwen model series, has been a front-runner in China’s AI race but has been slower to release consumer-facing products. Even though Qwen was the most downloaded open-source model on Hugging Face in 2024, it didn’t power a dedicated chatbot app until early 2025. In March, Alibaba rebranded its cloud storage and search app Quark into an all-in-one AI search tool. By June, Quark had introduced DeepResearch—a new mode that marks its most agent-like effort to date. 

ByteDance and Alibaba did not reply to MIT Technology Review’s request for comments.

“Historically, Chinese tech products tend to pursue the all-in-one, super-app approach, and the latest Chinese AI agents reflect just that,” says Li of Simular, who previously worked at Google DeepMind on AI-enabled work automation. “In contrast, AI agents in the US are more focused on serving specific verticals.”

Pei, the researcher at Stanford, says that existing tech giants could have a huge advantage in bringing the vision of general AI agents to life—especially those with built-in integration across services. “The customer-facing AI agent market is still very early, with tons of problems like authentication and liability,” he says. “But companies that already operate across a wide range of services have a natural advantage in deploying agents at scale.”

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June 5, 2025 at 02:05PM