A new report out of the University of Cambridge studied the experiences of a total of 2,700 primary and secondary students in the UK and Italy and found that primary and secondary school girls had higher levels of both math anxiety and general anxiety than boys. "The study also focuses on how parents and teachers shape math performance and attitudes, perhaps without even realizing it," adds Motherboard. "In the same way that anxious parents can shape their children's anxiety, math-anxious mentors can shape how kids view their own math anxiety." From the report: The new study builds on previous research by highlighting the importance of teachers and parents' own math anxieties impacting students. Most students that the researchers talked to said that their anxiousness started when the math topics became more challenging, and they felt like they couldn't do them. Another reason the students' said they were struggling was because multiple teachers were teaching them math, and it became confusing across teaching styles. "Importantly -- and surprisingly -- this new research suggests that the majority of students experiencing maths anxiety have normal to high maths ability," Josh Hillman, Director of Education at the Nuffield Foundation, said in a press release.

Several of the excerpts of the interviews conducted by researchers with math-anxious kids are heartbreaking: Many described feelings that they knew the answers but panicked, or tried to battle through initial confusion. One child, around 9 or 10 years old, said: "Once, I think it was the first day and he picked on me, and I just kind of burst into tears because everybody was staring at me and I didn't know the answer. Well I probably knew it but I hadn't thought it through." Another described doing a fractions test: "It means like enormously [nervous], and enormously means like massively... I felt very unwell and I was really scared and because my table's in the corner, I kind of just like tried to not be in the lesson."

An anonymous reader quotes a report from Motherboard: Now, for Pi Day (March 14), music software programmer Canton Becker has crafted a million-hour song based on Pi that unfolds generatively on a virtual tape deck. Titled "Shepard's Pi," the song combines two of Becker's favorite infinities: Pi, and an auditory illusion called a Shepard tone, which he describes as an "unsettling sonic illusion of a pitch that climbs or descends forever, never reaching a top or a bottom." Found at PiSongs.com, users can tune into "Shepard's Pi" in real time with a custom virtual tape deck. The track itself evolves moment to moment, but the synthesized and sampled tones will be familiar to anyone who has ever listened to the electronic music of Kraftwerk, Tangerine Dream, Aphex Twin, and Global Communication. Far from being a mere gimmick, it is a highly evocative and transporting piece of electronic music, alternately ambient, glitchy, and interestingly rhythmic. The 58,999 GB MP3 file needed to be distributed via a webpage or app, so Becker "started hacking away at the basic algorithm in the programming languages PHP and Javascript," reports Motherboard. "In between coding marathons, Becker composed and recorded the loops and samples that would form the basis of the song. He experimented with sounds that would work well together regardless of being stacked one upon the other."

"When users hit 'play' on the virtual tape deck, the algorithm actually 'performs' the piece," the report says. "This way, the 114-year song can fit in just one gigabyte of space, which is mostly comprised of the digits of Pi. The virtual tape deck was also a solution to a built-in quirk of browsers such as Chrome, Safari, and Firefox -- users must click on a webpage to trigger a sound." From start to finish, the song lasts 999,999 hours, "a limitation imposed by only considering the first one billion digits of Pi."

Pi just got bigger. Google's Compute Engine has calculated the most digits of pi ever, setting a new world record. From a report: Emma Haruka Iwao, who works in high performance computing and programming language communities at Google, used infrastructure powered by Google Cloud to calculate 31.4 trillion digits of pi. The previous world record was set by Peter Trueb in 2016, who calculated the digits of pi to 22.4 trillion digits. This is the first time that a publicly available cloud software has been used for a pi calculation of this magnitude.

Iwao became fascinated by pi when she learned about it in math class at school. At university, one of her professors, Daisuke Takahashi, was the record holder for the most-calculated digits of pi using a supercomputer. Now, y-cruncher is the software of choice for pi enthusiasts. Created in 2009, y-cruncher is designed to compute mathematical constants like pi to trillions of digits. "You need a pretty big computer to break the world record," says Iwao. "But you can't just do this with a computer from a hardware store, so people have previously built custom machines." In September of 2018, Iwao started to consider how the process of calculating even more digits of pi would work technically. Something which came up quickly was the amount of data that would be necessary to carry out the calculations, and store them -- 170 terabytes of data, which wouldn't be easily hosted by a piece of hardware. Rather than building a whole new machine Iwao used Google Cloud.

Iwao used 25 virtual machines to carry out those calculations. "But instead of clicking that virtual machine button 25 times, I automated it," she explains. "You can do it in a couple of minutes, but if you needed that many computers, it could take days just to get the next ones set up." Iwao ran y-cruncher on those 25 virtual machines, continuously, for 121 days.

CSS, or the language that styles and arranges how page elements appear on a website, will soon get support for trigonometry functions such as sine, cosine, tangent, and others, ZDNet is reporting. From the report: The new trigonometry functions were approved at the end of February in a meeting of the World Wide Web Consortium (W3C) CSS Working Group. The new functions approved and set to join the CSS standard are: Sine - sin(), cosine - cos(), tangent - tan(), arccosine - acos(), arcsine - asin(), arctangent - atan(), arctangent (of two numbers x and y) - atan2(), square root - sqrt(), square root of the sum of squares of its arguments - hypot(), and power of - pow().

An anonymous reader quotes a report from Ars Technica: Pai's claim was questionable from the beginning, as we detailed last month. The Federal Communications Commission data cited by Chairman Pai merely showed that deployment continued at about the same rate seen during the Obama administration. Despite that, Pai claimed that new broadband deployed in 2017 was made possible by the FCC "removing barriers to infrastructure investment." But even the modest gains cited by Pai rely partly on the implausible claims of one ISP that apparently submitted false broadband coverage data to the FCC, advocacy group Free Press told the FCC in a filing this week.

The FCC data is based on Form 477 filings made by ISPs from around the country. A new Form 477 filer called Barrier Communications Corporation, doing business as BarrierFree, suddenly "claimed deployment of fiber-to-the-home and fixed wireless services (each at downstream/upstream speeds of 940mbps/880mbps) to census blocks containing nearly 62 million persons," Free Press Research Director Derek Turner wrote. "This claimed level of deployment stood out to us for numerous reasons, including the impossibility of a new entrant going from serving zero census blocks as of June 30, 2017, to serving nearly 1.5 million blocks containing nearly 20 percent of the U.S. population in just six months time," Turner wrote. "We further examined the underlying Form 477 data and discovered that BarrierFree appears to have simply submitted as its coverage area a list of every single census block in each of eight states in which it claimed service: CT, DC, MD, NJ, NY, PA, RI, and VA." In reality, BarrierFree's website doesn't market any fiber-to-the-home service, and it advertises wireless home Internet speeds of up to just 25mbps, Free Press noted. BarrierFree appears to have ignored the FCC's instructions to report service only in census blocks in which an ISP currently offers service and instead simply "listed every single census block located in eight of the states in which it's registered as a CLEC [competitive local exchange carrier]."

As a result of BarrierFree's claimed level of deployment, it skewed the FCC's overall data significantly. "Pai claimed that the number of Americans lacking access to fixed broadband with speeds of at least 25Mbps down and 3Mbps up 'has dropped by over 25 percent, from 26.1 million Americans at the end of 2016 to 19.4 million at the end of 2017,'" reports Ars. "With BarrierFree's erroneous filing removed, 'the number of Americans lacking access to a fixed broadband connection at the 25Mbps/3Mbps threshold declined to 21.3 million, not 19.4 million,' Free Press wrote."

An anonymous reader quotes a report from Motherboard: Last week, Motherboard published an investigation which revealed that law enforcement agencies around the country are using PredPol -- a predictive policing software that once cited the controversial, unproven "broken windows" policing theory as a part of its best practices. Our report showed that local police in Kansas, Washington, South Carolina, California, Georgia, Utah, and Michigan are using or have used the software. In a 2014 presentation to police departments obtained by Motherboard, the company says that the software is "based on nearly seven years of detailed academic research into the causes of crime pattern formation the mathematics looks complicated -- and it is complicated for normal mortal humans -- but the behaviors upon which the math is based are very understandable."

The company says those behaviors are "repeat victimization" of an address, "near-repeat victimization" (the proximity of other addresses to previously reported crimes), and "local search" (criminals are likely to commit crimes near their homes or near other crimes they've committed, PredPol says.) But academics Motherboard spoke to say that the mathematical theory that is used to power PredPol is flawed, and that its algorithm -- at least as pitched to police -- is far too simplistic to actually predict crime. Kristian Lum, who co-wrote a 2016 paper that tested the algorithmic mechanisms of PredPol with real crime data, told Motherboard in a phone call that although PredPol is powered by complicated-looking mathematical formulas, its actual function can be summarized as a moving average -- or an average of subsets within a data set. "The academic foundation for PredPol's software takes a statistical modeling method used to predict earthquakes and apply it to crime," reports Motherboard. "Much like how earthquakes are likely to appear in similar places, the papers argue, crimes are also likely to occur in similar places. Suresh Venkatasubramanian, a professor of computing at the University of Utah and a member of the board of directors for ACLU Utah, told Motherboard that earthquake data and crime data are, naturally, collected in different ways."

"I would say in our mind, the key difference is that in earthquake models, you have seismographs everywhere -- wherever an earthquake happens, you'll find it," Venkatasubramanian said. "The crux of the issue really is that to what extent are you able to get data about what you're observing that is not also totally on the model itself." "If you build predictive policing, you are essentially sending police to certain neighborhoods based on what what they told you -- but that also means you're not sending police to other neighborhoods because the system didn't tell you to go there," Venkatasubramanian said. "If you assume that the data collection for your system is generated by police whom you sent to certain neighborhoods, then essentially your model is controlling the next round of data you get."

Zorro shares a report from The Register: Older satnavs and such devices won't be able to use America's Global Positioning System properly after April 6 unless they've been suitably updated or designed to handle a looming epoch rollover. GPS signals from satellites include a timestamp, needed in part to calculate one's location, that stores the week number using ten binary bits. That means the week number can have 210 or 1,024 integer values, counting from zero to 1,023 in this case. Every 1,024 weeks, or roughly every 20 years, the counter rolls over from 1,023 to zero. The first Saturday in April will mark the end of the 1,024th week, after which the counter will spill over from 1,023 to zero. The last time the week number overflowed like this was in 1999, nearly two decades on from the first epoch in January 1980. You can see where this is going. If devices in use today are not designed or patched to handle this latest rollover, they will revert to an earlier year after that 1,024th week in April, causing attempts to calculate position to potentially fail. System and navigation data could even be corrupted, we're warned. U.S. Homeland Security explained the issue in a write-up this week. GPS.gov also notes that the new CNAV and MNAV message formats will use a 13-bit week number, so this issue shouldn't happen again anytime soon. The site recommend users consult the manufacturer of their equipment to make sure they have the proper updates in place.

A Beijing-based online education start-up has developed an artificial intelligence-powered maths app that can check children's arithmetic problems through the simple snap of a photo. Based on the image and its internal database, the app automatically checks whether the answers are right or wrong. From a report: Known as Xiaoyuan Kousuan, the free app launched by the Tencent Holdings-backed online education firm Yuanfudao, has gained increasing popularity in China since its launch a year ago and claims to have checked an average of 70 million arithmetic problems per day, saving users around 40,000 hours of time in total. Yuanfudao is also trying to build the country's biggest education-related database generated from the everyday experiences of real students. Using this, the six-year-old company -- which has a long line of big-name investors including Warburg Pincus, IDG Capital and Matrix Partners China -- aims to reinvent how children are taught in China. "By checking nearly 100 million problems every day, we have developed a deep understanding of the kind of mistakes students make when facing certain problems," said Li Xin, co-founder of Yuanfudao -- which means "ape tutor" in Chinese -- in a recent interview. "The data gathered through the app can serve as a pillar for us to provide better online education courses."

According to a new study published in the journal Science Advances, researchers from Australia and France have shown that bees can perform simple arithmetic, adding and subtracting small numbers by studying color-coded shapes. CNET reports: To test the buzzers' ability to perform arithmetic, the team used a three-chambered maze shaped like a Y, training bees to enter through a hole into a small chamber where they would see their first stimulus: blue or yellow shapes on a plain, grey background. The number of shapes varied between 1 and 5 and the color of the shapes told the bee whether it needed to add one (blue) or subtract one (yellow) from the initial number. The bee then flew into a subsequent chamber which presented both a correct option and an incorrect option. To train the bees, the correct option rewarded the critters with a drop of tasty sugar solution -- a delightful dessert for the bee. On the other hand, selecting the incorrect solution resulted in a nasty drop of quinine -- like a slab of Brussels sprouts slathered in chocolate.

The testing procedure itself focused on 14 bees undergoing four tests of 10 choices. The tests themselves were "non-reinforced," so they didn't receive reward or punishment when selecting their "answers" during testing. Because the bees were subjected to two answers each time, the expectation is that -- purely by chance -- they would select the correct answer 50 percent of the time. But the bees performed significantly better than chance would predict, selecting the correct answer around 65 percent of the time.

Tesla CEO Elon Musk announced today that the company would cut 7% of its workforce in order to cut costs as the company prepares to ramp up production and boost margins as they get closer to releasing the long-awaited $35,000 version of the Model 3. CNBC reports: Musk says Tesla faces "an extremely difficult challenge" in making their products a competitive alternative to traditional vehicles, adding that he expects Q4 profit to come in significantly lower than Q3. Five experts weigh in on whether it's a challenge Musk and Tesla can overcome:

- Oppenheimer managing director Colin Rusch agrees with Jed Dorsheimer on Tesla's job cuts, but isn't bullish on what they'll accomplish.
- Canaccord Genuity's Jed Dorsheimer thinks the workforce cut is just fine, calling it "clean-up" after the company's latest push to ramp up Model 3 production came with a wealth of new hires.
- "They're certainly in a better position than they were eight or nine months ago," says ROTH Capital's Craig Irwin. "Where we're going to see pressure on the stock today is the 'copy-paste' expectations of Q3 going through 2019 need to be reset."
- Needham's Raji Gil thinks that Tesla may have overestimated how many people can actually afford a high-end electric vehicle. "Clearly, in my mind, they have an issue with demand," says Rusch, " If you do the math, you have to conclude that 90 percent of the reservations that have been built up over the past couple of years are folks that wanted the standard battery version of the vehicle, which is $35,000."
- Westly Group founder Steve Westly loves where Elon Musk's company is right now, calling Tesla "the iPhone of electric vehicles," and saying they're well ahead of the game when it comes to a quickly-changing auto market.

Joshua S. Goldstein, a professor emeritus of international relations at American University, and Staffan A. Qvist, an energy engineer and consultant, writing for The Wall Street Journal: Climate scientists tell us that the world must drastically cut its fossil fuel use in the next 30 years to stave off a potentially catastrophic tipping point for the planet. Confronting this challenge is a moral issue, but it's also a math problem -- and a big part of the solution has to be nuclear power. Today, more than 80% of the world's energy comes from fossil fuels, which are used to generate electricity, to heat buildings and to power car and airplane engines. Worse for the planet, the consumption of fossil fuels is growing quickly as poorer countries climb out of poverty and increase their energy use. Improving energy efficiency can reduce some of the burden, but it's not nearly enough to offset growing demand.

Any serious effort to decarbonize the world economy will require, then, a great deal more clean energy, on the order of 100 trillion kilowatt-hours per year, by our calculations -- roughly equivalent to today's entire annual fossil-fuel usage. A key variable is speed. To reach the target within three decades, the world would have to add about 3.3 trillion more kilowatt-hours of clean energy every year. Solar and wind power alone can't scale up fast enough to generate the vast amounts of electricity that will be needed by midcentury, especially as we convert car engines and the like from fossil fuels to carbon-free energy sources. Even Germany's concerted recent effort to add renewables -- the most ambitious national effort so far -- was nowhere near fast enough. A global increase in renewables at a rate matching Germany's peak success would add about 0.7 trillion kilowatt-hours of clean electricity every year. That's just over a fifth of the necessary 3.3 trillion annual target.

"One of the world's foremost mathematicians, Prof Sir Michael Atiyah, has died at the age of 89," reports the BBC.

"He has been described to me by more than one professor of mathematics as the best mathematician in this country since Sir Isaac Newton," his brother tells the BBC. Slashdot reader OneHundredAndTen shared their report: Sir Michael was best known for his co-development of a branch of mathematics called topological K-theory and the Atiyah-Singer index theorem. His research also involved deep insights relating to mathematical concepts known as "vector bundles". His work in these areas has helped theoretical physicists to advance their understanding of quantum field theory and general relativity.
In September, Atiyah also claimed to have proved the 160-year-old Riemann hypothesis.

"If the hypothesis is proven to be correct," New Scientist reported, "mathematicians would be armed with a map to the location of all such prime numbers, a breakthrough with far-reaching repercussions in the field."

A federal district court has ruled that the state of Oregon illegally infringed on a man's First Amendment rights for fining him $500 because he wrote "I am an engineer" in a 2014 email to the state's Engineering Board. The court ruled that the provision in the law he broke is unconstitutional, which opens the door for people in the state to legally call themselves "engineers." Motherboard reports: This dystopian saga dates back to 2013, when Mats Jarlstrom's wife, while driving, was caught by a red light camera near their home in Beaverton, Oregon. Rather than pay the red light camera fine, Jarlstrom, an electrical engineer, spent months researching the specifics of yellow light timing and red light cameras, and learned that his wife had likely been ticketed for running a yellow light. Jarlstrom began sharing his findings on his personal website, at conferences, and even got featured on 60 Minutes. He also wrote several emails to the Oregon Board of Engineers explaining what he had found. In the email, he noted that he was an "engineer."

Rather than looking into whether traffic light timing should be changed, however, the board sent Jarlstrom a warning -- and then a $500 fine for the crime of "practicing engineering without being registered." Jarlstrom had violated one of Oregon's "Title Laws," which states that "no persons may ... hold themselves out as an 'engineer'" unless they are an "individual who is registered in this state and holds a valid certificate to practice engineering in this state." Jarlstrom has a bachelor's degree in electrical engineering and spent his career working in electronics, but wasn't board certified. He sued the state's engineering board and, last week, a U.S. District Court judge for the District of Oregon ruled that the state's law is unconstitutional. The judge wrote: "The statutes prohibit truthfully describing oneself as an 'engineer,' in any context. This restriction clearly controls and suppresses protected speech, and enforcement of the statute against protected speech is not a hypothetical threat. The term 'engineer,' standing alone, is neither actually nor inherently misleading. Courts have long recognized that the term 'engineer' has a generic meaning separate from 'professional engineer' and that the term has enjoyed 'widespread usage in job titles in our society to describe positions which require no professional training.'"

"The judge ordered that the word 'engineer' be struck from Oregon's law, which is 'substantially overbroad in violation of the First Amendment' and specifically noted that Jarlstrom may describe himself publicly and privately using the word 'engineer' and that he may continue to talk about traffic light timing publicly," reports Motherboard.

chalsall (Slashdot reader #185), writes: The Great Internet Mersenne Prime Search (GIMPS) has discovered the largest known prime number, 2^82,589,933-1, having 24,862,048 digits. A computer volunteered by Patrick Laroche from Ocala, Florida made the find on December 7, 2018.

GIMPS has been on amazing lucky streak, finding triple the expected number of new Mersenne primes -- a dozen in the last fifteen years.
"This anomaly is not necessarily evidence that existing theories on the distribution of Mersenne primes is incorrect," notes GIMPS. "However, if the trend continues it may be worth further investigation. " They also report that the newly-discovered prime number "is more than one and a half million digits larger than the previous record prime number" -- and it's one of just 51 known Mersenne prime numbers ever discovered. "GIMPS, founded in 1996, has discovered the last 17..."

Patrick Laroche is one of thousands of volunteers using GIMPS' free software to hunt for prime numbers -- and is now eligible for a $3,000 "research discovery award," the group writes at mersenne.org. "GIMPS' next major goal is to win the $150,000 award administered by the Electronic Frontier Foundation offered for finding a 100 million digit prime number" -- of which $50,000 will be awarded to the discoverer, with another $50,000 going to a 501(c)(3) mathematics-related charity selected by GIMPS, and $50,000 retained by GIMPS to cover expenses and fund other awards.

dmoberhaus shares a report from Motherboard: A team of Japanese researchers from Keio University in Tokyo have demonstrated that an amoeba is capable of generating approximate solutions to a remarkably difficult math problem known as the "traveling salesman problem." The traveling salesman problem goes like this: Given an arbitrary number of cities and the distances between them, what is the shortest route a salesman can take that visits each city and returns to the salesman's city of origin. As these Japanese researchers demonstrated, a certain type of amoeba can be used to calculate nearly optimal solutions to the traveling salesman problem for up to eight cities. Even more remarkably, the amount of time it takes the amoeba to reach these nearly optimal solutions grows linearly, even though the number of possible solutions increases exponentially. The reason this amoeba is considered especially useful in biological computing is because it can extend various regions of its body to find the most efficient way to a food source and hates light.

To turn this natural feeding mechanism into a computer, the Japanese researcher placed the amoeba on a special plate that had 64 channels that it could extend its body into. This plate is then placed on top of a nutrient rich medium. The amoeba tries to extend its body to cover as much of the plate as possible and soak up the nutrients. Yet each channel in the plate can be illuminated, which causes the light-averse amoeba to retract from that channel. To model the traveling salesman problem, each of the 64 channels on the plate was assigned a city code between A and H, in addition to a number from 1 to 8 that indicates the order of the cities. To guide the amoeba toward a solution to the traveling salesman problem, the researchers used a neural network that would incorporate data about the amoeba's current position and distance between the cities to light up certain channels. The neural network was designed such that cities with greater distances between them are more likely to be illuminated than channels that are not. When the algorithm manipulates the chip that the amoeba is on it is basically coaxing it into taking forms that represent approximate solutions to the traveling salesman problem.

An anonymous reader shares a report: One day this fall, Ashutosh Garg, the chief executive of a recruiting service called Eightfold.ai, turned up a resume that piqued his interest. It belonged to a prospective data scientist, someone who unearths patterns in data to help businesses make decisions, like how to target ads. But curiously, the resume featured the term "data science" nowhere.

Instead, the resume belonged to an analyst at Barclays who had done graduate work in physics at the University of California, Los Angeles. Though his profile on the social network LinkedIn indicated that he had never worked as a data scientist, Eightfold's software flagged him as a good fit. He was similar in certain key ways, like his math and computer chops, to four actual data scientists whom Mr. Garg had instructed the software to consider as a model.

The idea is not to focus on job titles, but "what skills they have," Mr. Garg said. "You're really looking for people who have not done it, but can do it." The power of such technology will be immediately apparent to any employer scrambling to fill jobs in a tight labor market -- not least positions for data scientists, whom companies like Google, Facebook and Amazon are competing to attract. Thanks to services like Eightfold, which rely on sophisticated algorithms to match workers and jobs, many employers may soon have access to a universe of prospective workers -- even for hard-to-fill roles -- whom they might not otherwise have come across.

Paradoxically, the abundance of tight interactions among living species usually leads to disasters in ecological models. New analyses hint at how nature seemingly defies the math. Veronique Greenwood, writing for Quantamagazine: Behind the beautiful facade of a rainforest, a savanna or a placid lake is a world teeming with contests and partnerships. Species are competing for space, consuming one another for resources, taking advantage of one another's talents, and brokering trades of nutrients. But there's something funny about this picture. When ecologists try to model ecosystems using math, they tend to find that the more interactions there are among species, the more unstable the system. For a simple ecosystem model to be stable, all the interactions among its species must be in perfect harmony. Maintaining that balancing act gets much harder, however, as the number of coupled species and the strengths of their interactions rise: Any disturbance or imbalance for one couple ripples outward and sows chaos throughout the network.

Bring in mutualisms, relationships in which species contribute directly to each other's survival, and things can really fly off the handle. Pairs of organisms that live off each other sometimes do so well in the mathematical simulations -- thriving exponentially in extreme cases, in what Robert May, the theoretical ecology pioneer, once called "an orgy of mutual benefaction" -- that everything else can go extinct. It seems unlikely that real ecosystems are quite this flimsy. In a new paper in Nature Communications, a pair of theoretical ecologists at the University of Illinois explored more precisely how the give-and-take in mutualism affects ecosystem stability and how, under the right conditions, it might contribute to it. Their result joins previous work in suggesting how real-world communities manage to be more resilient than the models imply.

A new proof from the Australian science fiction writer Greg Egan and a 2011 proof anonymously posted online are now being hailed as significant advances on a puzzle mathematicians have been studying for at least 25 years. Erica Klarreich, writing for Quanta Magazine: On September 16, 2011, an anime fan posted a math question to the online bulletin board 4chan about the cult classic television series The Melancholy of Haruhi Suzumiya . Season one of the show, which involves time travel, had originally aired in nonchronological order, and a re-broadcast and a DVD version had each further rearranged the episodes. Fans were arguing online about the best order to watch the episodes, and the 4chan poster wondered: If viewers wanted to see the series in every possible order, what is the shortest list of episodes they'd have to watch? In less than an hour, an anonymous person offered an answer -- not a complete solution, but a lower bound on the number of episodes required. The argument, which covered series with any number of episodes, showed that for the 14-episode first season of Haruhi, viewers would have to watch at least 93,884,313,611 episodes to see all possible orderings. "Please look over [the proof] for any loopholes I might have missed," the anonymous poster wrote.

The proof slipped under the radar of the mathematics community for seven years -- apparently only one professional mathematician spotted it at the time, and he didn't check it carefully. But in a plot twist last month, the Australian science fiction novelist Greg Egan proved a new upper bound on the number of episodes required. Egan's discovery renewed interest in the problem and drew attention to the lower bound posted anonymously in 2011. Both proofs are now being hailed as significant advances on a puzzle mathematicians have been studying for at least 25 years. Mathematicians quickly verified Egan's upper bound, which, like the lower bound, applies to series of any length. Then Robin Houston, a mathematician at the data visualization firm Kiln, and Jay Pantone of Marquette University in Milwaukee independently verified the work of the anonymous 4chan poster. Now, Houston and Pantone, joined by Vince Vatter of the University of Florida in Gainesville, have written up the formal argument. In their paper, they list the first author as "Anonymous 4chan Poster."

An anonymous reader quotes a report from IEEE Spectrum: Deep learning has a DRAM problem. Systems designed to do difficult things in real time, such as telling a cat from a kid in a car's backup camera video stream, are continuously shuttling the data that makes up the neural network's guts from memory to the processor. The problem, according to startup Flex Logix, isn't a lack of storage for that data; it's a lack of bandwidth between the processor and memory. Some systems need four or even eight DRAM chips to sling the 100s of gigabits to the processor, which adds a lot of space and consumes considerable power. Flex Logix says that the interconnect technology and tile-based architecture it developed for reconfigurable chips will lead to AI systems that need the bandwidth of only a single DRAM chip and consume one-tenth the power.

Mountain View-based Flex Logix had started to commercialize a new architecture for embedded field programmable gate arrays (eFPGAs). But after some exploration, one of the founders, Cheng C. Wang, realized the technology could speed neural networks. A neural network is made up of connections and "weights" that denote how strong those connections are. A good AI chip needs two things, explains the other founder Geoff Tate. One is a lot of circuits that do the critical "inferencing" computation, called multiply and accumulate. "But what's even harder is that you have to be very good at bringing in all these weights, so that the multipliers always have the data they need in order to do the math that's required. [Wang] realized that the technology that we have in the interconnect of our FPGA, he could adapt to make an architecture that was extremely good at loading weights rapidly and efficiently, giving high performance and low power."

An anonymous reader shares a report: Factorising numbers into their constituent primes may sound esoteric, but the one-way nature of the problem -- and of some other, closely related mathematical tasks -- is the foundation on which much modern encryption rests. Such encryption has plenty of uses. It defends state secrets, and the corporate sort. It protects financial flows and medical records. And it makes the $2trn e-commerce industry possible. Nobody, however, is certain that the foundation of all this is sound. Though mathematicians have found no quick way to solve the prime-factors problem, neither have they proved that there isn't one. In theory, any of the world's millions of professional or amateur mathematicians could have a stroke of inspiration tomorrow and publish a formula that unravels internet cryptography -- and most internet commerce with it.

In fact, something like this has already happened. In 1994 Peter Shor, a mathematician then working at Bell Laboratories, in America, came up with a quick and efficient way to find a number's prime factors. The only catch was that for large numbers his method -- dubbed Shor's algorithm -- needs a quantum computer to work. Quantum computers rely on the famous weirdness of quantum mechanics to perform certain sorts of calculation far faster than any conceivable classical machine. Their fundamental unit is the "qubit", a quantum analogue of the ones and zeros that classical machines manipulate. By exploiting the quantum-mechanical phenomena of superposition and entanglement, quantum computers can perform some forms of mathematics -- though only some -- far faster than any conceivable classical machine, no matter how beefy.