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Testosterone Significantly Boosts Women's Athletic Performance, Study Shows
Posted on Thursday January 01, 1970

An anonymous reader quotes a report from The Guardian: Boosting testosterone levels significantly improves female athletic performance, according to one of the first randomized controlled trials. The findings come as the International Association of Athletics Federations (IAAF) announced on Monday it would impose an upper limit for testosterone levels on trans female athletes competing in middle-distance events. The latest research confirmed that testosterone significantly increases endurance and lean muscle mass among young women, even when given for a relatively short period. In the study, published in the British Journal of Sports Medicine, 48 healthy 18- to 35-year-old women were randomly assigned to 10 weeks of daily treatment with 10mg of testosterone cream or 10mg of a placebo. The scientists tested the hormone's impact on aerobic performance measured by how long the women could run on a treadmill before reaching the point of exhaustion, and leg power, muscle strength and lean muscle mass. Circulating levels of testosterone rose from 0.9 nmol/litre of blood to 4.3 nmol/L in the women given the hormone cream. This was below the recent 5 nmol/L IAAF limit and below the normal male range of 8-29 nmol/L. Running time to exhaustion increased significantly by 21.17 seconds (8.5%) in the testosterone group, compared with those given the inactive substance. The group given the hormone also had significant changes in lean muscle mass, gaining 923g vs 135g overall and 398g vs 91g in their legs. "The IAAF ruled this week that trans female athletes must keep their levels of natural testosterone below 5 nanomoles per liter of blood to compete in the female category," the report adds. "The new regulation follows a similar limit imposed on athletes with differences of sexual development (DSD), including the South African Olympic gold medallist, Caster Semenya."

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Dutch Family 'Waiting For End of Time' Discovered In Basement
Posted on Thursday January 01, 1970

A family who spent nine years in a basement "waiting for the end of time" have been discovered by police in the Netherlands after one of them turned up at a local pub, reports say. The BBC reports: A man of 58 and a family with young adults aged 18 to 25 were living at a farm in the province of Drenthe. They were found after the eldest of the children ordered beer at a bar in the nearby village of Ruinerwold. He then told staff he needed help, broadcaster RTV Drenthe reported. The older man, who has been arrested, was initially assumed to be the father, but local mayor Roger de Groot later told reporters that was not the case. Nor was the man the owner of the farmhouse, Mr de Groot said, adding: "I've never seen anything like it." The public broadcaster said that the family had been living in isolation waiting for the end of time. Unconfirmed reports said the children's father was among those found. Bar owner Chris Westerbeek described how a man had come in, ordered five beers and drunk them. "Then I had a chat with him and he revealed he had run away and needed help... then we called the police," he said. He added: "He had long hair, a dirty beard, wore old clothes and looked confused. He said he'd never been to school and hadn't been to the barber for nine years." "He said he had brothers and sisters who lived at the farm. He said he was the oldest and wanted to end the way they were living." Officers visited the remote farmhouse and carried out a search. They discovered a hidden staircase behind a cupboard in the living room that led down to a basement room where the family were housed.

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Robot War Breaks Out As Roomba Maker Sues Upstart SharkNinja
Posted on Thursday January 01, 1970

Roomba robotic vacuum maker IRobot Corp. is suing rival SharkNinja for copying a device of theirs and selling it at "half the price." "Shark is not even shy about being a copycat," iRobot said in a lawsuit filed Tuesday in federal court in Boston, "claiming that the Shark IQ Robot offers the same iRobot technology at 'half the price of iRobot i7+'."Bloomberg reports: The company that unveiled the Roomba robotic vacuum in the early 2000s launched a product last year that takes house cleaning to a new level: It maps your home, schedules sweeps through each room, empties the dust bin itself and even knows where to resume cleaning after has returned to its base for a recharge. After being recognized by Time magazine for one of 2018's inventions of the year, IRobot Corp. says it's no accident that rival SharkNinja Operating LLC came out with a similar device a year later. [...] SharkNinja, a unit of closely held EP Midco LLC, on Friday filed a pre-emptive lawsuit in federal court in Delaware, asking the court to declare that the Shark IQ doesn't infringe six patents cited in iRobot's complaint, nor five others. IRobot had previously demanded that the Shark IQ be pulled off store shelves.

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YouTube Gets Alleged Copyright Troll To Agree To Stop Trolling YouTubers
Posted on Thursday January 01, 1970

Alleged copyright troll Christopher Brady will no longer be able to issue false DMCA takedowns to other YouTubers, according to a lawsuit settlement filed today. The Verge reports: Under the new agreement, Brady is banned from "submitting any notices of alleged copyright infringement to YouTube that misrepresent that material hosted on the YouTube service is infringing copyrights held or claimed to be held by Brady or anyone Brady claims to represent." Brady agreed to pay $25,000 in damages as part of the settlement. He is also prohibited from "misrepresenting or masking their identities" when using Google products, including YouTube. "This settlement highlights the very real consequences for those that misuse our copyright system. We'll continue our work to prevent abuse of our systems," a YouTube spokesperson told The Verge. "I, Christopher L. Brady, admit that I sent dozens of notices to YouTube falsely claiming that material uploaded by YouTube users infringed my copyrights," he said in an apology, shared by YouTube with The Verge. "I apologize to the YouTube users that I directly impacted by my actions, to the YouTube community, and to YouTube itself." YouTube claimed the investigation caused the company to "expend substantial sums on its investigation in an effort to detect and halt that behavior, and to ensure that its users do not suffer adverse consequences from it." YouTube also said that the company may be "unable to detect and prevent similar misconduct in the future," as a result of the various methods Brady took to cover up his identity.

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OpenAI's AI-Powered Robot Learned How To Solve a Rubik's Cube One-Handed
Posted on Thursday January 01, 1970

Earlier today, San Francisco-based research institute OpenAI announced that it had taught a robotic hand to solve Rubik's cube one-handed. "Lost in the shuffle is just what is new here, if anything, and what of it may or may not be machine learning and artificial intelligence -- the science in other words," writes Tiernan Ray via ZDNet. An anonymous Slashdot reader shares an excerpt from his report: The real innovation in Tuesday's announcement, from a science standpoint, is the way many versions of possible worlds were created inside the computer simulation, in an automated fashion, using an algorithm called ADR. ADR, or "Automatic domain randomization," is a way to reset the neural network at various points based on different appearances of the Rubik's cube and different positions of the robotic hand, and all kinds of physical variables, such as friction and gravity. It's done by creating thousands of variations of the values of those variables inside the computer simulator while the neural network is being trained. ADR is an algorithm that changes the variables automatically and iteratively, as the policy network is trained to solve the Rubik's cube. The ADR, in other words, is a separate piece of code that is designed to increase random variation in training data to make things increasingly hard for the policy neural network. Using ADR, the real world Dexterous Hand can adapt to changes such as when it drops the cube on the floor and the cube is placed back in the hand at a slightly different angle. The performance of the Dexterous Hand after being trained with ADR is vastly better than without it, when only a handful (sorry again again for the pun) of random variants are thrown at it using the prior approach of manually-crafted randomness, the authors report. What's happening, they opine, is the emergence of a kind of "meta-learning." The neural network that has been trained is still, in a sense "learning" at the time it is tested on the real-world Rubik's cube. What that means is that the neural network is updating its model of what kinds of transitions can happen between states of affairs as events happen in the real world. The authors assert that they know this is happening "inside" the trained network because they see that after a perturbation -- say, the Dexterous Hand is hit with some object that interrupts its effort -- the robot's activity suddenly plunges, but then steadily improves, as if the whole policy network is adjusting to the changed state of affairs.

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