A Minor Adjustment to the “For You” Algorithm Can Rapidly Foster Political Polarization.

Studies indicate that altering the tone of posts on X can escalate political polarization within just a week, a shift that traditionally would have taken about three years.

An innovative study examining the impact of Elon Musk’s social media platforms on political polarization discovered that even minor increases in posts featuring anti-democratic sentiments or partisan aggression led to a marked rise in negative sentiments toward the opposing political faction among Democrats and Republicans.


The level of division, termed “emotional polarization,” reached in just one week due to the modifications made to the feeds of a specific number of X users equated to what would typically take an average of three years from 1978 to 2020.

Most of the over 1,000 participants in the experiment during the 2024 U.S. presidential election remained unaware of the changes in the tone of their feeds.

The campaign featured divisive viral content on X, including a fake image of Kamala Harris with Jeffrey Epstein and an AI-generated depiction from an image Musk posted showing Harris as a communist dictator, which garnered 84 million views.

Researchers observed that consistent exposure to posts reflecting anti-democratic views or partisan animosity significantly affected users’ feelings towards polarization, inducing heightened emotions of sadness and anger.

Musk acquired Twitter in 2022, rebranded it as X, and introduced a “for you” feed that presented content aimed at maximizing user engagement rather than just displaying posts from accounts that users actively follow.

The finding that increasing anti-democratic content heightens hostility towards political adversaries underscores the “power of algorithms,” noted Martin Savesky, an assistant professor at the University of Washington’s School of Information and a co-author of the study alongside colleagues from Stanford University, Johns Hopkins University, and Northeastern University. This research is published in Science magazine.

“While the adjustments in users’ feeds were subtle, they reported marked changes in their sentiments toward others,” explained Tiziano Picardi, an assistant professor in the Johns Hopkins University School of Computer Science and co-author of the study. “These shifts align with approximately three years of polarization trends seen in the U.S.”

The study also indicated that even slight alterations in users’ feed content could substantially diminish political hostility between Republicans and Democrats, implying that X could foster political unity if Musk opts to implement such changes.

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“The intriguing aspect of these findings is that platforms can implement measures to mitigate polarization,” added Savesky. “This offers a new perspective for algorithm design.”

Mr. X was reached out for comment.

According to Pew Research, eight in ten American adults believe there’s an inability among Republicans and Democrats to agree on not only policies, but also on fundamental facts. Additionally, over half the British population perceives political differences as dangerously divisive, as revealed by a recent Ipsos poll.

The evolution of political polarization caused by exposure to posts on X was evaluated using an innovative methodology. Initially, researchers utilized AI to analyze posts in X’s “for you” feed in real time. The findings indicated that some groups were exposed to more divisive content while others faced less, demonstrating X’s predominant influence. Divisive posts included support for undemocratic practices, partisan violence, a lack of bipartisan consensus, and skewed interpretations of politicized facts.

After a week of reading these subtly modified feeds, researchers prompted users to evaluate their political opponents’ warmth or coldness, favorability or unfavorability. Changes in “emotional deflection” were rated at two degrees or higher on a scale from 0 to 100 on a “feeling thermometer.” This level of increase in polarization matched the typical trend observed in the U.S. over the past four decades leading to 2020. Conversely, reducing posts with anti-democratic views and partisan hostility led to a corresponding decline in political polarization.

Social media platforms have long faced criticism for amplifying divisive content to boost user engagement and thereby increase advertising revenue. Nevertheless, the study revealed that when divisive posts were deprioritized, users tended to like and share more frequently, despite a slight decrease in overall engagement in terms of time spent on the platform and posts viewed.

“The effectiveness of this approach illustrates its potential for integration into social media AI, aimed at mitigating detrimental personal and societal impacts,” the authors argue. “Simultaneously, our engagement analysis indicates a notable trade-off; implementing such measures could decrease short-term engagement levels, posing challenges to engagement-driven business models, supporting the idea that content that elicits strong reactions tends to generate more engagement.”

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Source: www.theguardian.com

Quantum-Inspired Algorithm May Uncover Hidden Cosmic Objects

Galaxy clusters create gravitational lenses, bending light around them

NASA, ESA, Michael Gladders (University of Chicago); Acknowledgment: Judy Schmidt

Quantum physics might hold the key to unraveling the mysteries of celestial objects that remain undetectable or poorly observed through telescopes.

In our quest to comprehend the universe, we gather and scrutinize light emitted by stars and various celestial entities. However, this light often doesn’t travel in a straight path. When passing near massive entities like planets or black holes, the light’s trajectory can curve, resulting in a distorted image, akin to having an additional lens in the process.

Considering smaller objects that lack significant mass, traditional imaging strategies often fall short when dealing with “microlensing” effects. Researchers including Liu Zhenning at the University of Maryland have demonstrated that light analysis protocols that respect the quantum aspects may yield superior results.

They aimed to utilize the quantum features of light to deduce the mass of objects responsible for microlensing. According to Liu, microlensing is detectable when light brightness increases, signaling the presence of an object obscuring our view. However, if this object doesn’t possess substantial mass, its weight remains indeterminate from the light characteristics already measured by the telescope. Such bodies could encompass solitary small black holes or wandering planets.

Given that light consists of photons—quantum particles—there’s valuable information embedded in the quantum nature of its journey to Earth. Notably, when a photon encounters multiple paths around an object, the travel time discrepancies impact its quantum properties. Due to the wave-like characteristics of quantum particles, these photons can traverse both paths simultaneously, mimicking a water wave around a rock. The team’s methodology is adept at analyzing the time differences of both routes, which can be transformed into mass estimates for the objects.

Liu mentions that while planets and black holes inducing microlensing may not be completely imperceptible by other means, these techniques could necessitate more light collection, implying the need for larger telescopes. Quantum methods, however, can function effectively even with smaller photon counts.

For instance, his team’s mathematical assessments indicate that their protocol is particularly effective for stars located in the galactic bulge, a section of the Milky Way where dark matter candidates have been previously identified using gravitational lensing techniques. Because this new approach doesn’t demand a sophisticated quantum computer and can be employed with more conventional devices combined with classical computers to capture and analyze individual photons, it’s poised for real-world testing in the near future.

Daniel Oy, a professor at the University of Strathclyde in the UK, asserts that quantum methodologies significantly enhance the extraction of time-delayed data from light, an enhancement he characterizes as a pivotal advancement in quantum technology. He posits that since quantum theory sets limits on measurement precision in physics, it aligns perfectly with the challenge of detecting faint astronomical signals like those from a limited number of photons.

reference: arXiv, DOI: 10.48550/arXiv.2510.07898

topic:

  • astrophysics/
  • quantum physics

Source: www.newscientist.com

Young Children Develop Problem-Solving Skills with a Sorting Algorithm from Birth

Complex problem solving can arise sooner in child development than previously believed

PlusOnevector/Alamy

Research reveals that four-year-olds can devise efficient strategies for complex challenges, such as independently creating sorting methods akin to those used by computer scientists. The researchers assert that these abilities appear much earlier than once thought, warranting a reevaluation of developmental psychology.

Past experiments led by Swiss psychologist Jean Piaget popular in the 1960s, required children to physically arrange sticks by length. His findings indicated that structured strategies didn’t emerge until around age seven, as children tended to experiment haphazardly through trial and error.

Contrarily, recent work by Huiwen Alex Yang and his team at the University of California, Berkeley, shows that a notable fraction of four-year-olds can create algorithmic solutions for the same task, with more than a quarter exhibiting these skills by age five.

“Perhaps we haven’t given our children enough credit,” Yang states. “We must delve deeper into their reasoning capabilities.”

In a study involving 123 children aged 4-9, researchers asked them to sort digital images of bunnies by height. Initially, they could view groups of bunnies and directly compare their heights, allowing all children to sort them aptly using straightforward methods.

However, once the heights were obscured, the children had to compare only two bunnies at a time while being informed whether their order was correct. This approach necessitated the development of new strategies, as they couldn’t see the entire group simultaneously.

The researchers examined the children’s application of these new strategies, looking for evidence of known solutions and demonstrated instances where children utilized established algorithms. It was found that overall, children frequently outperformed random chance. Remarkably, they independently identified at least two efficient sorting algorithms recognized in computer science: Selection Sort and Shaker Sort.

In 34% of trials, children employed various comparisons, signaling their use of known sorting algorithms for a portion of the time. Out of a total of 667 tests run, the children utilized selection and shaker sorting in 141 instances, with some employing combinations of both strategies. Notably, 67 out of 123 children demonstrated at least one recognizable algorithm, and 30 children used both at different stages in the experiment.

Nonetheless, the age of the children directly influenced how many used algorithms. Only 2.9% of four-year-olds applied identifiable methods, while this rose to 25.5% among five-year-olds and 30.7% for six-year-olds. By age nine, over 54% were using identifiable algorithms.

“This has long been a challenge to Piaget,” remarks Andrew Bremner from the University of Birmingham, UK. He acknowledges Piaget’s groundbreaking contributions to developmental psychology in setting stages for learning but emphasizes that Piaget often designed experiments without proper controls. “Critics have been eager to illustrate that children can achieve more than Piaget claimed.

Essentially, while Piaget initially had a correct understanding of child development, his assessments of the ages at which children achieve certain milestones were overly pessimistic. This latest study strengthens the evidence supporting earlier development stages. Interestingly, it revolves around sorting. Bremner indicates this as the last bastion of Piaget’s work, proving applicable to younger children than once believed.

“Children can successfully navigate this particular problem much sooner than we anticipated,” states Bremner. “They do not approach the world as mere blank slates, but rather implement strategic techniques in problem-solving.”

Sam Wass from the University of East London points out that Piaget contended that children needed a comprehensive grasp of complex systems before they could devise strategies to engage with them, a notion he is finding increasingly unnecessary.

“This research signifies a significant trend in psychology that contests the assumption that intricate thoughts and understanding are prerequisites for executing complex behaviors,” notes Wass. “The study illustrates that complex behaviors may emerge from a far simpler array of rules.”

Topics:

Source: www.newscientist.com

Trump Hails TikTok Deal as Beijing Proposes Chinese Algorithm Use for Apps

Donald Trump contends that, in light of the uncertainty surrounding the final agreement, Tiktok is aiming to keep operating in the US while Beijing retains control over the algorithms that govern the platform’s video feed.

“There’s a deal concerning Tiktok. A number of major companies are interested in purchasing it,” Trump stated on Tuesday, though he did not provide further specifics.

The agreement, reportedly negotiated between US Treasury Secretary Scott Bescent and a Chinese deputy prime minister in Madrid, is said to involve transferring US assets of the social media platform from Chinese ownership to new American proprietors.


A key concern revolves around the fate of Tiktok’s influential algorithms that contribute to its status as one of the top online entertainment sources globally.

At a press briefing in Madrid, the deputy head of China’s cybersecurity regulator indicated that the framework for the agreement would entail “algorithm licenses and other intellectual property rights.”

Wang Jingtao noted that Bytedance will “contract Tiktok’s US user data and content security operations.”

Some analysts interpret these remarks to mean that the US spinoff of Tiktok may still possess the Chinese algorithm.

During a discussion at the Supreme Court in January, Tiktok’s lawyer informed the judge of the challenges in selling the platform to US companies, citing Chinese laws that restrict the sale of its algorithms, which are critical to the success of social media platforms.

US officials have previously expressed concerns that the algorithms determining user content could be susceptible to manipulation by the Chinese government.

Tiktok has countered that the US has not presented any evidence suggesting that China has sought to manipulate content on American platforms.

According to China’s House Selection Committee, any agreement between Beijing and Washington must adhere to laws requiring Tiktok’s sale to avoid a ban in the US.

“If the algorithm remains Chinese, it does not meet compliance. There is no algorithm shared with the US,” a spokesman for China’s House Selection Committee stated.

On Tuesday, Trump further postponed the enforcement of the Tiktok ban until December 16th, marking the fourth delay of legislation aimed at compelling Chinese owners to divest from the app. The latest delay was set to conclude on Wednesday, aligning with a law enacted in 2024 by then-President Joe Biden that aimed to close Tiktok in the US due to its Chinese ownership.

This law aims to address national security concerns linked to Tiktok’s Chinese parent company and its possible connections to the Chinese government.

Nonetheless, the 2024 election campaign heavily relies on social media, with Trump, who has expressed a fondness for Tiktok, continuing to delay the ban.

The app is under scrutiny from US officials worried about data collection practices and content manipulation. Tiktok has consistently denied sharing user data with Chinese authorities and has contested various restrictions in federal courts.

“We have a significant pool of companies interested in acquiring it,” Trump remarked.

China also confirmed what was described as a “framework” for transactions on Monday following phone calls between the two leaders.

After a Reuters inquiry, a senior White House official commented that specifics regarding the framework were “speculation unless disclosed by this administration.”

Reuters and Assen France Press

Source: www.theguardian.com

Taking a Break from Spotify: My Month Away from the Algorithm and What I Discovered About Khruangbin

I Music serves as a remarkable tool for adjusting your mood, and Spotify excels in this regard. Feeling down? Check out your custom “Depress Sesh Mix.” Navigating a romantic dilemma? You’ll find a curated “situational mix.” As I write this, I’m tuned into Spotify’s daylist—a compilation that refreshes every few hours based on my listening preferences. Today’s vibe is the “Funky Beat Roller Skate Early Morning Tuesday Mix.” At a brisk 120bpm, the algorithm gets that an energetic soundtrack is essential for transitioning from bed to desk.

The downside of this tailored listening experience is its overly familiar AI-driven intimacy, where the same tracks loop predictably. Spotify’s algorithm has dulled the novelty of artists I once loved. I find myself hitting Skip every time Kluang Bin’s slippery, psychedelic bass enters my playlists or seamlessly flows from another artist’s radio.

A decade ago, Spotify championed human-curated playlists crafted by artists, celebrities, and music enthusiasts. However, by 2021, streaming platforms started pivoting toward machine learning, with computer-generated models creating nearly half of daily events. Nowadays, user data—primarily our listening habits, interactions with Spotify, and the time of day—are compiled into tightly personalized mixtapes.

Proponents argue this offers an opportunity to democratize music promotion by accurately matching it with audiences. Yet, critics claim this hyper-subjective approach restricts music discovery to what listeners already know. Despite my attempts, my musical taste has become increasingly narrow. As an experiment, I paused my Spotify use for a month, rediscovering how to find music.

Initially, I consulted my father, someone who has never used streaming services, and who grew up in the vibrant punk and glam rock scene of 1970s London. Spending time at his local record shop, he would sample vinyl, selecting A-sides or B-sides to purchase. Some albums missed the mark, while others transported him to another dimension, akin to experiencing Pink Floyd’s “The Dark Side of the Moon.” He advised me to start with my favorite artist and listen to each album sequentially, as if I were reading a narrative.

Inspired, I purchased a $30 record player from a thrift shop and sought out vinyl. My visit to Record Renaissance yielded slim pickings—Australian pub classics, Christian country, and Christmas hits. However, when a friend pointed out that my new turntable lacked a needle, it unfortunately became a dusty but eye-catching décor piece in my living room.

My 20-year-old neighbor provided another idea: an iPod adorned with rhinestones, found on Facebook Marketplace for $200. Plugging it in with wired ear buds and hitting shuffle was a nostalgic throwback. Sadly, this romance was short-lived since the iPod struggled to sync with my Bluetooth speaker and required hours of tedious uploads.

The biggest hurdle arose during drives in my old silver Subaru, where I was limited to just one CD, a flimsy auxiliary chord, and my thoughts. Stuck in silence, I chanced upon my local community radio station, Vox FM 106.9. More than five million Australians tune in to community radio weekly for an average of 17 hours—and I understand why. The station prides itself on “real music” with the slogan, “I don’t know what I like until you try it.” It was just what I needed! I rediscovered the thrill of rolling down the window and blasting tracks by the Sugababes.

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I reached out to Justin Moon, who manages a popular underground radio station and record shop in Newcastle. He sources music from Record Fairs, friends, and Bandcamp, distributing interesting sounds like a modern-day Hermes, guiding listeners like me towards new auditory experiences. Moon notes that his audience seeks a more “active” listening journey. “It’s not the kind of background noise you forget about ten seconds into boiling two minutes of noodles,” he remarks.

Like movies, TV, and food, music is now more accessible than ever. However, this accessibility has resulted in a phenomenon where music is often drowned out. Instead of relying solely on algorithms, I spent a month finding new music independently, fostering a deeper connection with my parents, friends, radio presenters, and even strangers. Their recommendations embodied parts of themselves, their memories, or mutual interests, regardless of my past preferences.

After my month-long Spotify hiatus, my algorithm hadn’t completely reset. While composing this piece, my daylist evolved into “Indietronican Swimming Pool in France on a Tuesday Afternoon,” featuring two Khruangbin songs. It’s safe to say it’s time to roll the dice on the radio.

Source: www.theguardian.com

UK Uber Drivers Face Reduced Earnings Due to Secret Algorithm Changes

A significant number of Uber drivers have reported earning “considerably less” per hour since the introduction of the “dynamic pricing” algorithm by the ride-hailing app in 2023.

This conclusion emerged from a study released on Thursday by researchers at Oxford University, who examined data from 258 Uber drivers across the UK, accounting for 1.5 million trips.

Following a 20% reduction in fixed fare cuts in the UK, Uber launched dynamic pricing in 2023. This algorithm varies passenger ride prices and fare payments in numerous ways, evolving from Uber’s previous “surge pricing” model that raised prices during peak demand.

Researchers discovered that Uber currently claims a fare reduction of 29% or “acquisition rate,” which in some cases has exceeded 50%.

The union criticized this initiative, stating in 2023 that it lacked transparency and could degrade working conditions by profiling drivers based on their acceptance of lower fares.

According to the Oxford survey, “With the introduction of dynamic pricing, Uber riders now face higher fares, yet drivers do not benefit.”

The research was conducted in partnership with the non-profit gig worker organization, Worker Information Exchange (WIE). “Our results indicate that many aspects of Uber driver employment have worsened following the dynamic pricing rollout.”

The median take rate per driver has risen from 25% to 29%, with some trips exceeding 50%. Additionally, these higher take rates are predominantly observed among higher-income brackets. On average, many drivers are making significantly less per hour from their labor.

These findings come amidst various controversies involving tech companies, including a pivotal 2021 UK Supreme Court ruling affirming that Uber drivers are entitled to minimum wage and paid leave.

After the Uber Files were published, Jill Hazelbaker, Uber’s Vice President of Public Relations, stated:

The Oxford research also noted that the average hourly wage for a driver stands at £29.46. However, this drops to £15.98 when factoring in wait times, as defined by Uber, or the moments drivers are available for passenger pickups. Neither of these averages accounts for vehicle upkeep, insurance, fuel, or other expenses.

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Uber responded, stating it “does not recognize the figures in this report,” emphasizing that “all drivers are assured a minimum national living wage.”

One participant in the survey remarked, “It feels like Uber is taking away our clients and opportunities.”

An Uber representative affirmed, “UBU drivers garnered more than £1 billion in earnings from January to March of this year, surpassing previous years. Drivers have the freedom to choose to drive with Uber.”

“Every driver receives a weekly earnings summary, detailing what Uber and the drivers have made from their rides. Many drivers take pride in their choice to drive for Uber, especially as passenger demand and travel continue to increase.”

Source: www.theguardian.com

Grayscale and Prune Algorithm: “Digital Nutritionist” Provides Tips for Reducing Screen Time

A professor, now regarded as a “digital nutritionist,” suggests that disabling the color on your phone and dedicating 30 minutes a week to pruning your online feeds can enhance consumers’ control over their digital media consumption.

These strategies, termed grayscale and algorithmic tolerance, are part of Dr. Kaitlyn Regehr’s many recommendations. She is an associate professor at the University of London and a prominent authority on digital literacy.

While much of the conversation centers on social media’s negative effects on children, Regehr’s focus is on combating digital illiteracy among parents, empowering them to better understand and use their children’s devices safely and effectively.

In her upcoming book, Smartphone Nation, Regehr advises taking an initial step by performing a digital “walkthrough” of your preferred app alongside friends and family.

“Switching your phone to GreyScale is one of the easiest and quickest methods to grasp how colors and images impact your user experience,” she notes. “This experience allows you to feel the addictive nature of these devices through their visual elements.”

Users can find instructions for this feature in Google Help for Android devices or Apple Support for iPhones.

On the flip side, algorithm resistance focuses on taking charge of the algorithm rather than allowing it to dictate your preferences. Thus, Regehr advocates for being deliberate about what you wish to see in your feed, and filtering out unwanted content for 30 minutes each week.

“When I had concerns about my family’s digital consumption… I struggled to find adequate guidance,” Regehr shares in her book. “I developed a framework to help myself and my family navigate the digital landscape. I came to see myself as a digital nutritionist.”

In a conversation with the Guardian, she expressed her support for school smartphone bans and initiatives promoting a smartphone-free childhood, but highlighted the necessity for more education to encourage families to think critically about their digital choices.

“Even if parents postpone giving their children smartphones until they are 15, they will still turn 16. It’s essential to equip them with the tools to navigate this environment effectively,” she emphasized. “Education on how these devices operate is crucial.”

Her forthcoming book, “Why Are We All Obsessed with the Screen and What You Can Do About It,” aims to bridge this knowledge gap, with new educational resources set to be introduced in schools later this month.

As per the UK’s first national survey, nearly all schools in the country have implemented a ban on mobile phone usage during school hours.

Driven by worries regarding children’s mental health, attention span, and online safety, a survey of over 15,000 schools revealed that 99.8% of primary schools and 90% of secondary schools enforce some form of ban.

“I advocate for my efforts towards a smartphone-free childhood,” stated Regehr, who directs the digital humanities program at UCL and previously explored the rapid amplification of extreme misogynistic content through social media algorithms. “My concern is that enforcing the ban can lead schools and lawmakers to feel complacent, believing they’ve fulfilled their responsibilities.”

Dedicated to two young girls, Regehr’s book aims to prompt a cultural shift. “I aspire to reflect on our generation as being less healthy and more skillfully ensnared, akin to looking back on previous norms like smoking in delivery rooms and not using seatbelts.”

“My aim is to foster cultural change to ensure their lives are better. This represents the largest threat to their health and well-being, and that is the challenge I wish to tackle. I believe change is possible; people simply need access to information.”

Smartphone Nation: Why We’re All Obsessed with Screens and What You Can Do by Dr. Kaitlyn Regehr is set to be published by Bluebird on May 15th.

Source: www.theguardian.com

Quantum-inspired algorithm improves weather forecasting.

It is essential for weather forecasts to accurately simulate the turbulent air flow.

EUMETSAT/ESA

The algorithm inspired by quantums allows you to simulate the turbulent liquid flow on a classic computer much faster than the existing tools, and calculate from a few days of a large supercomputer to a normal laptop. Can be reduced. Researchers say that the weather forecast can be improved and industrial processes can be improved.

Liquid or air turbulence has a lot of interactions and quickly becomes very complicated, so it is impossible for the most powerful computer to simulate accurately. The quantum counter part promises to improve the problem, but now the most advanced machine cannot do anything other than rudimentary demonstrations.

These turbulent simulations can be simplified by replacing accurate calculations with probability. However, even with this approximation, scientists will surely request scientists to solve them.

Nikita Guulianov Oxford University and his colleagues have now developed a new approach to the stream probability distribution using algorithms inspired by quantum computers called Tensol Network.

Tensol networks were derived from physics and were commonly used in the early 2000s. They now provide a promising path to show much more performance from existing classical computers before truly convenient quantum machines become available.

“Algorithms and ideas come from the world of quantum simulation. These algorithms are very close to the quantum computer,” says Gourianov. “Both the theory and the actual can see a very dramatic speed up.”

In just a few hours, the team was able to perform a simulation on a laptop that took several days on a supercomputer before. With the new algorithm, the demand for processors has decreased by 1000 times and memory demand has decreased by 1 million times. This simulation was just a test, but the same type of problem is behind the weather, aircraft analysis, and industrial chemistry analysis.

It is said that the turbulent problem with five dimensions data is very difficult without using the tensor. Gunner Meller At Kent University. “It's a nightmare in calculation,” he says. “If you have a super computer and are happy to run for 1-2 months, you can do it in a limited case.”

The tensor network actually works by reducing the amount of data required for simulation and greatly reducing the calculation capacity required to execute it. The amount and nature of the deleted data can be carefully controlled by dialing the upper and lower accuracy level.

These mathematics tools are already used in cats and mouse games between quantum computer developers and classic computer scientists. Google announced in 2019 that a quantum processor called Sycamore has achieved “quantum advantage.” This is a point where quantum computers can complete tasks that are impossible for regular computers for all intentions and purposes.

However, the Tensol network, which simulates the same problem with a large -scale cluster of a conventional graphic processing unit, later achieved the same thing over 14 seconds and lost its previous claim. Since then, Google has once again pulled a new WILLOW Quantum Machine.

When a large -scale and fault -resistant quantum computer is created, the tensor can be executed on a much larger scale than the classic computer, but Möller is excited about what may be achieved in the meantime. I say you are.

“If you use a laptop, the author of this paper may lose what you can do with a supercomputer. You can get a big profit right away and have a perfect quantum computer.

topic:

Source: www.newscientist.com

Artificial Intelligence (AI) Algorithm Successfully Deciphers Rogue Wave Pattern

Scientists used artificial intelligence to analyze more than 1 billion waves over 700 years and developed a breakthrough formula for predicting rogue waves. This groundbreaking research, which converts vast amounts of oceanographic data into equations for the probability of adverse waves, raises questions about previous theories and has significant implications for maritime safety. This research represents a major step forward in this field in terms of the accessibility of findings and the role of AI in enhancing human understanding.

Researchers from the University of Copenhagen and the University of Victoria used over 700 years of ocean wave data, including more than a billion wave observations, and advanced artificial intelligence techniques to predict the occurrence of these threatening sea giants. Previously thought to be a myth, these unusually large and rough waves can cause serious damage to ships and oil rigs. The research team leveraged AI to analyze the vast amounts of data and create a mathematical model that provides a way to predict the occurrence of rogue waves. This new knowledge contributes to making shipping safer, and has paradigm-shifting implications for the maritime industry.

Rogue waves, perceived as a part of sailor folklore for centuries, became scientifically documented when a 26-meter high wave hit the Norwegian oil platform His Draupner in 1995. Since then, research on these extreme waves has been ongoing, culminating in the breakthrough reached by the University of Copenhagen and the University of Victoria. The research team leveraged big data on ocean movements and AI techniques to map the causal variables that lead to rogue waves, ultimately developing a model which usess artificial intelligence to calculate the probability of rogue wave formation.

Incorporating data collection from buoys at 158 locations on U.S. coasts and overseas territories and over a billion waves across 700 years, the researchers were able to use AI to analyze the vast amount of data and predict the likelihood of being hit by a huge wave at sea. The AI techniques also helped the researchers discover the causes of rogue waves and translate them into an equation that describes the recipe for rogue waves. This study also challenged common perceptions about the causes of rogue waves, establishing the dominance of a phenomenon known as “linear superposition.” This new knowledge can help the shipping industry to plan routes in advance and mitigate the risk of encountering dangerous rogue waves.

Source: scitechdaily.com