Pirated video streams of televised National Football League games are widespread on Facebook and on Google's YouTube service, CNBC has found. From a report: Using technology from these internet giants, thousands of football fans were able to watch long segments of many contests free of charge during the league's Week 13 schedule of games last Thursday and Sunday. Dozens of these video streams, pirated from CBS and NBC broadcasts, featured ads from well-known national brands interspersed with game action. This online activity comes as the league struggles with declining ratings that have been blamed variously on player protests during the national anthem and revelations about former players suffering from a brain disease caused by concussions. Yet this illegal distribution of NFL content may also be crimping the league's viewer numbers.

An anonymous reader shares a BBC report: Some people claim they can hear a thudding sound when the pylon hits the ground and the picture vibrates. Last weekend, Dr Lisa DeBruine from the Institute of Neuroscience & Psychology at the University of Glasgow posted it on Twitter, asking her followers to describe whether they experienced any auditory sensations while watching it. One person who suffers from ringing ears replied: "I hear a vibrating thudding sound, and it also cuts out my tinnitus during the camera shake." Others offered explanations as to why. While another suggested it may have something to do with correlated neuronal activity: "The brain is 'expecting/predicting' what is coming visually and then fires a version of what it expects across the relevant senses. Also explains why some might 'feel' a physical shake."

An anonymous reader shares a report from the BBC, written by Amanda Ruggeri: As we fill our days with more and more "doing," many of us are finding that non-stop activity isn't the apotheosis of productivity. It is its adversary. Researchers are learning that it doesn't just mean that the work we produce at the end of a 14-hour day is of worse quality than when we're fresh. This pattern of working also undermines our creativity and our cognition. Over time, it can make us feel physically sick -- and even, ironically, as if we have no purpose. Think of mental work as doing push-ups, says Josh Davis, author of Two Awesome Hours. Say you want to do 10,000. The most 'efficient' way would be to do them all at once without a break. We know instinctively, though, that that is impossible. Instead, if we did just a few at a time, between other activities and stretched out over weeks, hitting 10,000 would become far more feasible. "The brain is very much like a muscle in this respect," Davis writes. "Set up the wrong conditions through constant work and we can accomplish little. Set up the right conditions and there is probably little we can't do." Many of us, though, tend to think of our brains not as muscles, but as a computer: a machine capable of constant work. Not only is that untrue, but pushing ourselves to work for hours without a break can be harmful, some experts say. Ruggeri goes on to highlight the negative health effects associated with working long hours. "One meta-analysis found that long working hours increased the risk of coronary heart disease by 40% -- almost as much as smoking (50%)," she writes. "Another found that people who worked long hours had a significantly higher risk of stroke, while people who worked more than 11 hours a day were almost 2.5 times more likely to have a major depressive episode than those who worked seven to eight."

schwit1 quotes ScienceAlert: In May 2017, researchers at Google Brain announced the creation of AutoML, an artificial intelligence (AI) that's capable of generating its own AIs. More recently, they decided to present AutoML with its biggest challenge to date, and the AI that can build AI created a 'child' that outperformed all of its human-made counterparts... For this particular child AI, which the researchers called NASNet, the task was recognising objects -- people, cars, traffic lights, handbags, backpacks, etc. -- in a video in real-time. AutoML would evaluate NASNet's performance and use that information to improve its child AI, repeating the process thousands of times.

When tested on the ImageNet image classification and COCO object detection data sets NASNet was 82.7 percent accurate at predicting images on ImageNet's validation set. This is 1.2 percent better than any previously published results, and the system is also 4 percent more efficient, with a 43.1 percent mean Average Precision (mAP).

Science_afficionado quotes Vanderbilt University's Research News: When your attention shifts from one place to another, your brain blinks. The blinks are momentary unconscious gaps in visual perception and came as a surprise to the team of Vanderbilt psychologists who discovered the phenomenon while studying the benefits of attention... The research was conducted with macaque monkeys that were trained to shift their attention among different objects on a display screen while the researchers monitored the pattern of neuron activity taking place in their brains... By combining advanced recording techniques that simultaneously track large numbers of neurons with sophisticated computational analyses, the researchers discovered that the activity of the neurons in the visual cortex were momentarily disrupted when the game required the animals to shift their attention. They also traced the source of the disruptions to parts of the brain involved in guiding attention, not back to the eyes.

An anonymous reader quotes a report from Inverse: In the new paper, presented Thursday at the annual meeting of the Radiological Society of North America, a team of radiologists at Korea University report that smartphone addiction changes teenagers' brains. Using brain imaging, they argue that smartphone- and internet-addicted teenagers have imbalanced brain chemistry when compared to their peers who aren't addicted to smartphones or the internet. But scientists not involved with the study have some serious issues with their research. Perhaps the most important of these issues is the fact that "smartphone addiction" is not a scientifically established thing -- at least not yet.

In the study, the team led by Dr. Hyung Suk Seo used "standardized internet and smartphone addiction tests to measure the severity of internet addiction" in nine boys and 10 girls, according to a statement. Then, they used MRS, a brain imaging technique that can identify particular brain chemicals, to examine the participants' brains before and after taking nine weeks of cognitive behavioral therapy to help their "addiction." Compared to a control group, the "smartphone addicts" had skewed levels of neurotransmitters in their brains. In particular, they had a higher ratio of GABA to Glx (glutamateglutamine), which are respectively responsible for slowing down brain signals and exciting neurons. An elevated ratio of GABA to Glx, the researchers concluded, can be associated with the self-reported symptoms of the "smartphone addict" teens, including depression, anxiety, insomnia severity and impulsivity. After 12 of the teens participated in cognitive behavior therapy, the scientists report, their chemical imbalances appeared to even out to look more like the control group's.

An anonymous reader quotes a report from The Outline: Coditany of Timeness" is a convincing lo-fi black metal album, complete with atmospheric interludes, tremolo guitar, frantic blast beats and screeching vocals. But the record, which you can listen to on Bandcamp, wasn't created by musicians. Instead, it was generated by two musical technologists using a deep learning software that ingests a musical album, processes it, and spits out an imitation of its style. To create Coditany, the software broke "Diotima," a 2011 album by a New York black metal band called Krallice, into small segments of audio. Then they fed each segment through a neural network -- a type of artificial intelligence modeled loosely on a biological brain -- and asked it to guess what the waveform of the next individual sample of audio would be. If the guess was right, the network would strengthen the paths of the neural network that led to the correct answer, similar to the way electrical connections between neurons in our brain strengthen as we learn new skills.

Science_afficionado writes: Are you a cat lover? A dog lover? If so, you may be interested in the first scientific study to actually count the number of cortical neurons in the brains of a number of carnivores, including cats and dogs. Bottom line: Dogs have about twice as many of these "little grey cells" as cats. These "little gray cells" are associated with thinking, planning and complex behavior. The study found that dogs have about 530 million cortical neurons while cats have about 250 million. (For comparison, the human brain has 16 billion.) Another interesting discovery was that carnivores have about the same ratio of neurons to brain size as that of herbivores, "suggesting that there is just as much evolutionary pressure on the herbivores to develop the brain power to escape from predators as there is on carnivores to catch them," reports Vanderbilt University. "The study's findings also challenge the prevailing view that domesticated animals have smaller brains than their wild cousins. The ratios of brain size to body weight of the domestic species they analyzed -- ferret, cat and dog -- did not scale in a significantly different manner from those of their wild relatives -- mongoose, raccoon, hyena, lion and brown bear."

The results of the study are described in a paper titled "Dogs have the most neurons, though not the largest brain: Trade-off between body mass and number of neurons in the cerebral cortex of large carnivoran species" accepted for publication in the open access journal Frontiers in Neuroanatomy.

sciencehabit shares a report from Science Magazine: Automatic language translation has come a long way, thanks to neural networks -- computer algorithms that take inspiration from the human brain. But training such networks requires an enormous amount of data: millions of sentence-by-sentence translations to demonstrate how a human would do it. Now, two new papers show that neural networks can learn to translate with no parallel texts -- a surprising advance that could make documents in many languages more accessible.

The two new papers, both of which have been submitted to next year's International Conference on Learning Representations but have not been peer reviewed, focus on another method: unsupervised machine learning. To start, each constructs bilingual dictionaries without the aid of a human teacher telling them when their guesses are right. That's possible because languages have strong similarities in the ways words cluster around one another. The words for table and chair, for example, are frequently used together in all languages. So if a computer maps out these co-occurrences like a giant road atlas with words for cities, the maps for different languages will resemble each other, just with different names. A computer can then figure out the best way to overlay one atlas on another. Voila! You have a bilingual dictionary. The studies -- "Unsupervised Machine Translation Using Monolingual Corpora Only" and "Unsupervised Neural Machine Translation" -- were both submitted to the e-print archive arXiv.org.

A new paper from Stanford University reveals how artificial intelligence algorithms can be quickly trained to diagnose pneumonia better than a radiologist. "Using 100,000 x-ray images released by the National Institutes of Health on Sept. 27, the research published Nov. 14 (without peer review) on the website ArXiv claims its AI can detect pneumonia from x-rays with similar accuracy to four trained radiologists," reports Quartz. From the report: That's not all -- the AI was trained to analyze x-rays for 14 diseases NIH included in the dataset, including fibrosis, hernias, and cell masses. The AI's results for each of the 14 diseases had fewer false positives and false negatives than the benchmark research from the NIH team that was released with the data. The paper includes Google Brain founder Andrew Ng as a co-author, who also served as chief scientist at Baidu and recently founded Deeplearning.ai. He's often been publicly bullish on AI's use in healthcare. These algorithms will undoubtedly get better -- accuracy on the ImageNet challenge rose from 75% to 95% in just five years -- but this research shows the speed at which these systems are built is increasing as well.

At present, there is no treatment to stop the Alzheimer's. Bill Gates wants to make a sizeable attempt to change that. From a report:He is to invest $50 million in the Dementia Discovery Fund, a venture capital fund that brings together industry and government to seek treatments for the brain-wasting disease. The investment -- a personal one and not part of Gates' philanthropic Bill & Melinda Gates Foundation -- will be followed by another $50 million in start-up ventures working in Alzheimer's research, Gates said. "It's a huge problem, a growing problem, and the scale of the tragedy -- even for the people who stay alive -- is very high," he said. Despite decades of scientific research, there is no treatment that can slow the progression of Alzheimer's. Current drugs can do no more than ease some of the symptoms.

At the annual meeting of the Society for Neuroscience starting November 11 in Washington D.C., two teams of scientists plan to present previously unpublished research on the unexpected interaction between human mini-brains and their rat and mouse hosts. "In the new papers, according to STAT, scientists will report that the organoids survived for extended periods of time -- two months in one case -- and even connected to lab animals' circulatory and nervous systems, transferring blood and nerve signals between the host animal and the implanted human cells," reports Inverse. "This is an unprecedented advancement for mini-brain research." From the report: That mini-brains can even be grown in the lab is a huge advancement in the first place, as they have many of the same characteristics as living human brains that are in the early stages of development. Though they're not "alive" in the same sense that you and I are, they grow and are organized into different layers like our brains are. They even react in similar ways to stimuli like psychedelic drugs. Organoids are poised to revolutionize research on the human brain since scientists can perform tests on them that would be unethical to attempt on living humans. STAT also reports that a third lab, in addition to the two presenting at the Society for Neuroscience meeting, has successfully connected human brain organoids to blood vessels. This attempt veered into such challenging ethical territory, though, that the lab reportedly paused its efforts.

Andrew Ng, formerly the head of AI for Chinese search giant Baidu and, before that, creator of Google's deep-learning Brain project, knows as well as anyone that artificial intelligence is coming for plenty of jobs. Speaking at a conference on Tuesday, Ng said he would like to see a "new New Deal" that pays people displaced by technology to study, offering an incentive to learn new skills and reenter the workforce. From a report: Speaking at MIT Technology Review's annual EmTech MIT conference in Cambridge, MA, on Tuesday, Ng said he's visited call centers and spoken to workers, knowing that his teams of software engineers will then write software that will automate aspects of their work. "There are many professions in the crosshairs of AI teams across the world," he said. Ng, who's currently working on a startup called Deeplearning.ai that helps train people on deep-learning technology, has some ideas for helping those in jobs he thinks will be automated, from call-center workers to radiologists, truck drivers, and the like. His suggestion is for an updated version of the New Deal -- the Depression-era economic programs that invested in, among other things, getting unemployed Americans back to work -- that pays displaced workers to learn new job skills.

A new study published in the journal Nature Medicine found that sleep deprivation causes the bursts of electrical activity that brain cells use to communicate to become slower and weaker. "The finding could help explain why a lack of sleep impairs a range of mental functions, says Dr. Itzhak Fried, an author of the study and a professor of neurosurgery at the University of California, Los Angeles," reports NPR. From the report: The finding comes from an unusual study of patients being evaluated for surgery to correct severe epilepsy. As part of the evaluation, doctors place wires in the brain to find out where a patient's seizures are starting. That allows Fried and a team of scientists to monitor hundreds of individual brain cells, often for days. And because patients with epilepsy are frequently kept awake in order to provoke a seizure, the scientists had an ideal way to study the effects of sleep deprivation. In the study, all the patients agreed to categorize images of faces, places and animals. Each image caused cells in areas of the brain involved in perception to produce distinctive patterns of electrical activity. Then, four of the patients stayed up all night before looking at more images. And in these patients, "the neurons are responding slower," Fried says. "The responses are diminished, and they are smeared over longer periods of time." These changes impair the cells' ability to communicate, Fried says. And that leads to mental lapses that can affect not only perception but memory.

A reader shares commentary on the newly launched Xbox One X gaming console: Fundamentally, Xbox One X is the same machine that Microsoft released in 2013. It plays the same games, runs the same apps, depends on the same operating system. You can still plug your cable box into it and watch OneGuide magically sync with your local TV listings. Most of the things you can do look a little better and run a little faster/more efficiently, sure. The actual casing is smaller than the previous iterations, too. It's a gorgeous $500 machine. That's why I keep eyeballing it. My brain screams, "Why do you exist?" The Xbox One X does not answer. This is a familiar problem in 2017. Look around at all the tech in your life and do a quick, informal poll: How many of those items become outdated every year or every few years when a newer, shinier version of the same thing comes along? I'm talking about your iPhone and iPad. Your Amazon Echo and Kindle. Your Pixel and Daydream VR headset. Your Apple Watch. Your Roku, your Apple TV, your Chromecast. Incremental upgrades that push features like 4K! HDR! Wireless charging! Slimmer design! No headphone jack! (Wait, no, that last one is awful.) Breathless bullet point after breathless bullet point. Some of these additions have genuine utility and add value to the product. Many don't, or depend on you also possessing some other piece of incrementally upgraded tech (like the kinds of fancy-shmancy TVs that play the nicest with Xbox One X).

The Guardian shares the story of a PhD student at Imperial College London who abruptly stopped coming to the facility, even as he had one-year of studies left. From the story: Eventually, the professor called him. He had left for a six-figure salary at Apple. "He was offered such a huge amount of money that he simply stopped everything and left," said Maja Pantic, professor of affective and behavioural computing at Imperial. "It's five times the salary I can offer. It's unbelievable. We cannot compete." It is not an isolated case, the report says. Adding: Across the country, talented computer scientists are being lured from academia by private sector offers that are hard to turn down. According to a Guardian survey of Britain's top ranking research universities, tech firms are hiring AI experts at a prodigious rate, fuelling a brain drain that has already hit research and teaching. One university executive warned of a "missing generation" of academics who would normally teach students and be the creative force behind research projects. The impact of the brain drain may reach far beyond academia. Pantic said the majority of top AI researchers moved to a handful of companies, meaning their skills and experience were not shared through society. "That's a problem because only a diffusion of innovation, rather than its concentration into just a few companies, can mitigate the dramatic disruptions and negative effects that AI may bring about."

An anonymous reader quotes a report from WIRED: In a study published today in Nature Human Behavior, researchers at Carnegie Mellon and the University of Pittsburgh analyzed how suicidal individuals think and feel differently about life and death, by looking at patterns of how their brains light up in an fMRI machine. Then they trained a machine learning algorithm to isolate those signals -- a frontal lobe flare at the mention of the word "death," for example. The computational classifier was able to pick out the suicidal ideators with more than 90 percent accuracy (Warning: source may be paywalled; alternative source). Furthermore, it was able to distinguish people who had actually attempted self-harm from those who had only thought about it. In today's study, the researchers started with 17 young adults between the ages of 18 and 30 who had recently reported suicidal ideation to their therapists. Then they recruited 17 neurotypical control participants and put them each inside an fMRI scanner. While inside the tube, subjects saw a random series of 30 words. Ten were generally positive, 10 were generally negative, and 10 were specifically associated with death and suicide. Then researchers asked the subjects to think about each word for three seconds as it showed up on a screen in front of them. "What does 'trouble' mean for you?" "What about 'carefree,' what's the key concept there?" For each word, the researchers recorded the subjects' cerebral blood flow to find out which parts of their brains seemed to be at work.

mirandakatz writes: If you want to pick Evan Prodromou's brain -- as many people often do -- you'll have to pay him. And not just a consulting fee: You'll have to pay him in his own personal cryptocurrency, dubbed Evancoin. Currently, 20 days after his Initial Coin Offering, a single Evancoin is worth $45. As Prodromou tells Scott Rosenberg at Backchannel, "I'm not above a stunt! But in this case I'm really serious about exploring how cryptocurrency is changing what we can do with money and how we think about it. Money is this sort of consensual hallucination, and I wanted to experiment around that." The story goes on to explain what, exactly, goes into creating a personal cryptocurrency, and whether Evancoin could becoming a phenomenon that spreads.

An anonymous reader quotes a report from Quartz: The human brain has evolved and expanded over millennia to accommodate our ever-more-complex needs and those of our societies. This process is known as "encephalization" and has given us the big brain we need to communicate, cooperate, reach consensus, empathize, and socialize. The same is true for cetaceans, like whales and dolphins, it seems. These sea creatures also grew big brains in order to better live in societies, according to a study published on Oct. 16 in Nature Ecology & Evolution. According to Michael Muthukrishna, an economic psychologist at the London School of Economics and co-author of the study, the researchers used two related theories, the Social-Brain Hypothesis and the Cultural-Brain Hypothesis, to make predictions about various relationships between brain size, societal organization, and the breadth of behaviors the cetaceans would display. Then they tested these predictions by creating and evaluating a comprehensive database of cetacean brain size, social structures, and cultural behaviors across species using data from prior studies on 90 types of whales and dolphins.

The study found that cetaceans had complex alliances and communications, played and worked together for mutual benefit, and could even work with other species, like humans. Some also have individual signifiers, sounds that set them apart from others, and can mimic the sounds of others. In addition, it found that brain size predicted the breadth of social and cultural behaviors of these marine creatures (though ecological factors, like prey diversity and latitudinal range, also played a role). The researchers concluded there was a tie between cetacean encephalization, social structure, and group size.

jeffengel writes:Computer keyboards will be phased out over the next 20 years, and we should think carefully about what replaces them as the dominant mode of communicating with machines, argues Android co-founder Rich Miner. Virtual reality technology and brain-computer links -- whose advocates include Elon Musk -- could lead to a "dystopian" future where people live their lives inside of goggles, or they jack directly into computers and become completely "de-personalized," Miner worries.

He takes a more "humanistic" view of the future of human-machine interfaces, one that frees us to be more expressive and requires computers to communicate on our level, not the other way around. That means software that can understand our speech, facial expressions, gestures, and handwriting. These technologies already exist, but have a lot of room for improvement.
One example he gives is holding up your hand to pause a video.