The MysteryVibe is a snake-shaped vibrator that took the Internet by storm and is still going strong. This week I talked to the co-founder of the company, Stephanie Alys, about the future of pleasure and sextoys. It’s safe to say that this episode of Technotopia is a little NSFW.
The future, suggests Alys, will feature smart tools that will help with our sex lives and our relationships. The world is going to get a lot weirder, that’s for sure.
Ray Bradbury’s Fahrenheit 451 tells the story of a dystopian future where books have been outlawed and are destroyed by firemen who set them ablaze. But in an ironic twist, Super Terrain, a publisher in France, has created a new edition of Bradbury’s classic that actually requires extreme heat in order to be read.
Jo Frenken shared this video to Instagram showing a prototype copy of the book, which was developed by the Charles Nypels Lab at the Netherlands-based Jan van Eyck Academie—a research institute known for its experiments in materials and media. The pages of the book appear completely blacked-out—like a redacted CIA file—as you flip through them. But when heat is applied, using a flame from a lighter, in this case, the heat-activated ink disappears and the underlying text is revealed.
Super Terrain will apparently be making this unique version of Fahrenheit 451 available sometime in 2018, but we recommend maybe grabbing a hair dryer to read it. An actual open flame is probably a bit too risky.
Last night, Gordon Hayward’s season ended just six minutes after it started when he landed awkwardly after an alley-oop and suffered a serious leg injury in the process. There’s currently no timetable for his return, but based on how it looked there’s no doubt he has a long road of recovery ahead of him.
Plenty of NBA players offered their best wishes after witnessing the injury, and this morning Kobe Bryant threw up a post on Instagram offering some words of support to the injured Hayward:
This advice is coming from someone who knows what it’s like to overcome adversity— Kobe was certainly no stranger to injuries over the course of his playing years. He tore his Achilles in 2013 and broke his knee the following season before tearing his rotator cuff in 2015, a series of ailments that ultimately ended his career.
Remember AlphaGo, the first artificial intelligence to defeat a grandmaster at Go? Well, the program just got a major upgrade, and it can now teach itself how to dominate the game without any human intervention. But get this: In a tournament that pitted AI against AI, this juiced-up version, called AlphaGo Zero, defeated the regular AlphaGo by a whopping 100 games to 0, signifying a major advance in the field. Hear that? It’s the technological singularity inching ever closer.
A new paper published in Nature todaydescribeshow the artificially intelligent system that defeated Go grandmaster Lee Sedol in 2016 got its digital ass kicked by a new-and-improved version of itself. And it didn’t just lose by a little—it couldn’t even muster a single win after playing a hundred games. Incredibly, it took AlphaGo Zero (AGZ) just three days to train itself from scratch and acquire literally thousands of years of human Go knowledge simply by playing itself. The only input it had was what it does to the positions of the black and white pieces on the board. In addition to devising completely new strategies, the new system is also considerably leaner and meaner than the original AlphaGo.
Now, every once in a while the field of AI experiences a “holy shit” moment, and this would appear to be one of those moments. Looking back, other “holy shit” moments include Deep Blue defeating Garry Kasparov at chess in 1997, IBM’s Watson defeating two of the world’s best Jeopardy! champions in 2011, the aforementioned defeat of Lee Sedol in 2016, and most recently, the defeat of four professional no-limit Texas hold’em poker players at the hands of Libratus, an AI developed by computer scientists at Carnegie Mellon University.
This latest achievement qualifies as a “holy shit” moment for a number of reasons.
First of all, the original AlphaGo had the benefit of learning from literally thousands of previously played Go games, including those played by human amateurs and professionals. AGZ, on the other hand, received no help from its human handlers, and had access to absolutely nothing aside from the rules of the game. Using “reinforcement learning,” AGZ played itself over and over again, “starting from random play, and without any supervision or use of human data,” according to the Google-owned DeepMind researchers in their study. This allowed the system to improve and refine its digital brain, known as a neural network, as it continually learned from experience. This basically means that AlphaGo Zero was its own teacher.
“This technique is more powerful than previous versions of AlphaGo because it is no longer constrained by the limits of human knowledge,” notes the DeepMind team in a release. “Instead, it is able to learn tabula rasa [from a clean slate] from the strongest player in the world: AlphaGo itself.”
When playing Go, the system considers the most probable next moves (a “policy network”), and then estimates the probability of winning based on those moves (its “value network”). AGZ requires about 0.4 seconds to make these two assessments. The original AlphaGo was equipped with a pair of neural networks to make similar evaluations, but for AGZ, the Deepmind developers merged the policy and value networks into one, allowing the system to learn more efficiently. What’s more, the new system is powered by four tensor processing units (TPUS)—specialized chips for neural network training. Old AlphaGo needed 48 TPUs.
After just three days of self-play training and a total of 4.9 million games played against itself, AGZ acquired the expertise needed to trounce AlphaGo (by comparison, the original AlphaGo had 30 million games for inspiration). After 40 days of self-training, AGZ defeated another, more sophisticated version of AlphaGo called AlphaGo “Master” that defeated the world’s best Go players and the world’s top ranked Go player, Ke Jie. Earlier this year, both the original AlphaGo and AlphaGo Master won a combined 60 games against top professionals. The rise of AGZ, it would now appear, has made these previous versions obsolete.
This is a major achievement for AI, and the subfield of reinforcement learning in particular. By teaching itself, the system matched and exceeded human knowledge by an order of magnitude in just a few days, while also developing unconventional strategies and creative new moves. For Go players, the breakthrough is as sobering as it is exciting; they’re learning things from AI that they could have never learned on their own, or would have needed an inordinate amount of time to figure out.
“[AlphaGo Zero’s] games against AlphaGo Master will surely contain gems, especially because its victories seem effortless,” wrote Andy Okun and Andrew Jackson, members of the American Go Association, in a Nature News and Views article. “At each stage of the game, it seems to gain a bit here and lose a bit there, but somehow it ends up slightly ahead, as if by magic… The time when humans can have a meaningful conversation with an AI has always seemed far off and the stuff of science fiction. But for Go players, that day is here.”
No doubt, AGZ represents a disruptive advance in the world of Go, but what about its potential impact on the rest of the world? According to Nick Hynes, a grad student at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), it’ll be a while before a specialized tool like this will have an impact on our daily lives.
“So far, the algorithm described only works for problems where there are a countable number of actions you can take, so it would need modification before it could be used for continuous control problems like locomotion [for instance],” Hynes told Gizmodo. “Also, it requires that you have a really good model of the environment. In this case, it literally knows all of the rules. That would be as if you had a robot for which you could exactly predict the outcomes of actions—which is impossible for real, imperfect physical systems.”
The nice part, he says, is that there are several other lines of AI research that address both of these issues (e.g. machine learning, evolutionary algorithms, etc.), so it’s really just a matter of integration. “The real key here is the technique,” says Hynes.
“As expected—and desired—we’re moving farther away from the classic pattern of getting a bunch of human-labeled data and training a model to imitate it,” he said. “What we’re seeing here is a model free from human bias and presuppositions: It can learn whatever it determines is optimal, which may indeed be more nuanced that our own conceptions of the same. It’s like an alien civilization inventing its own mathematics which allows it to do things like time travel,” to which he added: “Although we’re still far from ‘The Singularity,’ we’re definitely heading in that direction.”
Noam Brown, a Carnegie Mellon University computer scientist who helped to develop the first AI to defeat top humans in no-limit poker, says the DeepMind researchers have achieved an impressive result, and that it could lead to bigger, better things in AI.
“While the original AlphaGo managed to defeat top humans, it did so partly by relying on expert human knowledge of the game and human training data,” Brown told Gizmodo. “That led to questions of whether the techniques could extend beyond Go. AlphaGo Zero achieves even better performance without using any expert human knowledge. It seems likely that the same approach could extend to all perfect-information games [such as chess and checkers]. This is a major step toward developing general-purpose AIs.”
As both Hynes and Brown admit, this latest breakthrough doesn’t mean the technological singularity—that hypothesized time in the future when greater-than-human machine intelligence achieves explosive growth—is imminent. But it should cause pause for thought. Once we teach a system the rules of a game or the constraints of a real-world problem, the power of reinforcement learning makes it possible to simply press the start button and let the system do the rest. It will then figure out the best ways to succeed at the task, devising solutions and strategies that are beyond human capacities, and possibly even human comprehension.
As noted, AGZ and the game of Go represent an oversimplified, constrained, and highly predictable picture of the world, but in the future, AI will be tasked with more complex challenges. Eventually, self-teaching systems will be used to solve more pressing problems, such as protein folding to conjure up new medicines and biotechnologies, figuring out ways to reduce energy consumption, or when we need to design new materials. A highly generalized self-learning system could also be tasked with improving itself, leading to artificial general intelligence (i.e. a very human-like intelligence) and even artificial superintelligence.
As the DeepMind researchers conclude in their study, “Our results comprehensively demonstrate that a pure reinforcement learning approach is fully feasible, even in the most challenging of domains: it is possible to train to superhuman level, without human examples or guidance, given no knowledge of the domain beyond basic rules.”
And indeed, now that human players are no longer dominant in games like chess and Go, it can be said that we’ve already entered into the era of superintelligence. This latest breakthrough is the tiniest hint of what’s still to come.
The Natural History Museum of London has announced the winners of the 2017 Wildlife Photographer of the Year Competition. Highlights of this year include bioluminescent termite mounds, hoards of giant spider crabs, a juvenile gorilla lounging on the forest floor—and an absolutely heartbreaking image of a poached black rhino.
This year’s competition received over 50,000 entries from 92 countries. The winning images were chosen by a panel of judges and evaluated according to their creativity, originality, and technical excellence. As part of the annual competition, 100 photographs will be put on display at the 53rd Wildlife Photographer of the Year Exhibition in South Kensington, UK, which opens on Friday. Here are some of our favorite winning images.
Winner, Wildlife Photographer of the Year 2017: “Memorial to a Species” by Brent Stirton, South Africa
At one point, black rhinos were the most numerous of the world’s rhino species, but they’re now endangered on account of poaching and the illegal international trade of rhino horn. This award-winning shot of a dead, dehorned black rhino captures the brutality and senselessness of poaching.
“To make such a tragic scene almost majestic in its sculptural power deserves the highest award. There is rawness, but there is also great poignancy and therefore dignity in the fallen giant,” noted competition judge Rox Kidman Cox in a statement. “It’s also symbolic of one of the most wasteful, cruel and unnecessary environmental crimes, one that needs to provoke the greatest public outcry.”
Winner, Young Wildlife Photographer of the Year 2017: “The Good Life” by Daniël Nelson, Netherlands
Winner of the “Animals in Their Environment” Category: “The Night Raider” by Marcio Cabral, Brazil
There’s a lot going on in this photo taken by Marcio Cabral in Brazil’s Cerrado region. Click beetle larvae embedded on the outer layers of the termite mounds are glowing in a bioluminiscent green, which they do to lure in their prey—flying termites. Meanwhile, a giant anteater is also going for the termites, sticking its snout and nose into the mound to reach the termites inside.
Winner of the “11-14 Years Old” Category: “Stuck In” by Ashleigh Scully, USA
Tween Ashleigh Scully took this photo of an American red fox in Yellowstone National Park, which in her own words, “illustrates the harsh reality of winter life in Yellowstone.”
Winner of the “Behavior: Invertebrates” Category: “Crab Surprise” by Justin Gilligan, Australia
If you look carefully, you can see a Maori octopus intermingled within this large aggregation of giant spider crabs. Photographer Justin Gilligan captured this photo while documenting a kelp transplant experiment for the University of Tasmania.
Winner of the “Earth’s Environment” Category: “The Ice Monster” by Laurent Ballesta, France
This otherworldly photo shows the submersed portion of a small iceberg floating near the Dumont d’Urville science base in east Antarctica. It took photographer Laurent Ballesta three days to capture the scene.
Winner of the “Wildlife Photojournalist: Single Image” Category: “Palm-Oil Survivors” by Aaron “Bertie” Gekoski, UK/USA
In this image taken by Aaron “Bertie” Gekoski, three generations of elephants are seen crossing the terraces of an oil palm plantation in Borneo that’s being prepped for re-plantation.
Winner of the “Black and White” Category: “Polar Pas de Deux” by Elio Elvinger, Luxembourg
When a mother polar bear and her two-year-old cub approached her ship, Elio Elvinger couldn’t pass up the opportunity to take a photo. The animals were attracted to leakage from the ship’s kitchen as it was anchored off Svalbard in Arctic Norway. “I was ashamed of our contribution to the immaculate landscape,” she said, “and of how this influenced the bears’ behaviour.”
Winner of the “Behavior: Amphibians and Reptiles” Category: “The Ancient Ritual” by Brian Skerry, USA
A female leatherback turtle slinks towards the ocean after laying her eggs, in an ethereal photo captured by Brian Skerry while in the US Virgin Islands.
Eventually he pinpointed the source. "It was the carbs," he said.
The fall of 2017 marks the one-year anniversary since Libin, who now runs an artificial intelligence startup studio called All Turtles, started fasting on a regular basis. The tech executive foregoes food for between two to eight days in a row every week, drinking only water, coffee, and tea.
Libin has lost 85 pounds, reversed a prediabetes diagnosis, and feels "25 years younger," he told Business Insider in a recent interview at the All Turtles office in San Francisco.
The fad has picked up fans in Silicon Valley, including author and podcaster Tim Ferriss, Y Combinator partner Daniel Gross, internet entrepreneur Kevin Rose (who created an app that lets fasters track their progress), and nearly the entire team at "smart drug" startup HVMN.
In November 2016, Libin found himself in a rut. He was working as a venture capitalist at General Catalyst while trying to come up with his next idea for a game-changing startup. He moved from New York to San Francisco while dealing with divorce after 19 years of marriage.
Loïc Le Meur, a friend and fellow entrepreneur, told him about a new diet that made him feel great. He hadn’t eaten in three days. Libin thought it sounded "really stupid."
"I went home [after meeting with Le Meur] to Google it, with the intention of just like, proving to him that he was being an idiot and needs to eat", Libin said. "I was really surprised after reading about it for a few hours that it all felt really plausible."
With the countdown to his 45th birthday ticking, Libin decided to try a three-day fast. On the first day, he was hungry. The second day proved harder. On the third day, he felt amazing.
"It was a little difficult in the beginning — but difficult compared to what? Even the first day was easier than spending an hour at the gym," Libin said. "I woke up on the third day and I felt better than I had in years. I was hooked on it right away."
Libin now fasts for two to eight days straight, depending on his work schedule and personal life. A business trip to Japan, where Libin can’t say no to ramen, or New York, where the pizza is divine, warrants an "eating day." So does a meal with an old friend in town.
On days he fasts, Libin drinks copious amounts of water, coffee, and tea. He rarely cheats on the diet, because he knows he won’t be able to stop eating once he’s started.
Other days, he indulges, but not overly so. Libin typically skips breakfast because he "prefers sleeping." He enjoys his favorite meals at some of the top restaurants in San Francisco, including the farm-to-table fare at Cockscomb and yakitori (a Japanese-style skewered chicken) at Rintaro. There is no calorie-counting or strict dieting on these days.
Libin returned to his doctor for testing and blood work earlier this year and found that he had reversed his likelihood of developing type 2 diabetes. He’s maintained his goal weight for at least three months.
At work, he describes feeling happier and more focused. He’s rarely hungry. There are no midday sugar crashes, because there are no snack binges. His meals, which are nearly always shared with business colleagues or friends and family, are documented on his calendar.
"Eating nothing is [working out] really great for me. You don’t have to think about it. I get back all this time, and I just don’t eat anything," Libin said.
Libin plans to continue eating — and not eating — this way for the rest of his life.
"This is easily in the top three most important things in my life that I’ve ever done. It’s absolutely transformative," Libin said. "And, look, check back in a year. I feel like I’m going to stick with it, because I really like it. I’ve dieted before, but I always thought the diet that I was doing wasn’t fun. I didn’t enjoy it. It got harder and harder.
"I’m not fasting to lose weight anymore. I’m fasting because I really like it," he added.
Japan’s work culture is so intense, people in the 1970s invented a word that translates to "death by overwork."
Karoshi, as it’s known, involves employees committing suicide or suffering from heart failure and stroke due to long hours.
The Japanese federal government has taken steps to reduce karoshi cases, but experts fear the measures don’t go far enough.
Ever since the late 1970s, Japan has had a word to refer to people dying from spending too much time in the office: karoshi. The literal translation is "death by overwork."
The latest employee death determined to be karoshi was 31-year-old journalist Miwa Sado. She reportedly logged 159 hours of overtime in one month at the news network NHK, before dying of heart failure in July 2013.
Her death was just recently announced as karoshi in early October 2017.
Before that, 24-year-old Matsuri Takahashi worked 105 hours of overtime in a month at the Japanese ad agency Dentsu. Takahashi leapt from her employer’s roof on Christmas Day 2015. Tadashi Ishii, Dentsu’s president and CEO, resigned a month later.
Working yourself to death
Japan’s karoshi concept can be traced back to the aftermath of World War II.
During the early 1950s, Prime Minister Shigeru Yoshida made rebuilding Japan’s economy his top priority. He enlisted major corporations to offer their employees lifelong job security, asking only that workers repay them with loyalty. The pact worked. Japan’s economy is now the third largest in the world, and it’s largely because of Yoshida’s efforts 65 years ago.
But within a decade of Yoshida’s initial call, Japanese workers began committing suicide and suffering strokes or heart failure from the enormous burdens of stress and sleep deprivation.
Initially, the ailment was known as "occupational sudden death," as the fatalities were primarily job-related, according to researchers studying the history of karoshi. In their quest to make good impressions on their bosses, workers began putting their undying loyalty to the ultimate test.
Fast-forward to today and the picture of work-life balance in Japan is hardly any better.
A 2016 report examining karoshi cases and their cause of death found that more than 20% of people in a survey of 10,000 Japanese workers said they worked at least 80 hours of overtime a month.
In the US, 16.4% of people work an average of 49 hours or longer each week. In Japan, more than 20% do, according to the report. Half of all respondents said they don’t take paid vacations.
Instead of karoshi cases affecting a majority-male workforce, as they used to, now women like Takahashi and Sado also suffer the consequences of staying committed to a job. "It’s 4 a.m. My body’s trembling," Takahashi reportedly said in one Twitter post. "I’m going to die. I’m so tired."
It’s not uncommon for young employees in Japan to work long hours. Bosses expect young employees still working their way up the corporate ladder to arrive early and leave late, often well into the night. Takehiro Onuki, a 31-year-old salesman, often arrives at 8 a.m. and leaves at midnight. He sees his wife only on the weekends.
So it goes for countless other Japanese employees, many of whom work in white-collar jobs that come with rigid hierarchies. Advancement is earned through back-breaking effort. And people seldom leave their jobs because finding a new one means starting from scratch, not at the level they just left.
The result is an entire generation of workers desperate to seem devoted to their work.
How to end karoshi for good
Japan is trying to curb cases of karoshi through policies that give people more time off at work. Soon after Takahashi’s suicide in December 2016, the federal government announced its Premium Friday plan. Effective immediately, workers would get the chance to leave at 3 p.m. on the last Friday of each month.
Now eight months into the program, the government hasn’t seen much success. Many Japanese companies are organizing their monthly finances and looking to hit sales targets at the end of the month; a shorter day has only made people busier.
"We will listen to various views both from the viewpoint of boosting consumer spending and achieving work-style reform, and review the campaign if necessary," Hiroshige Seko, a Japanese politician leading the program, recently told Japan Times.
Other companies have tried to minimize karoshi cases by offering breakfast to those arriving early, dissuading them from staying too late. Others have let workers take more time off as needed.
Experts on Japanese culture are skeptical these measures will make a long-term impact, however. They believe Japan’s true problem lies in its view of gender roles.
Frances Rosenbluth, a political scientist at Yale University, has said the best strategy for cutting working hours is to give firms tax breaks if they hire more women, thereby increasing the labor pool. But she acknowledged it won’t be easy.
"What do you do about the fact that firms’ incentives don’t align with the social desirability of changing this problem?" Rosenbluth told Business Insider. "That’s a hard one."
Amazon is helping parents stay on top of the gifts their kids will be begging for with its predictions for this year’s 100 most popular holiday toys.
If Amazon’s predictions are correct, kids will be looking for products from traditional favorites like Lego and Play-Doh, as well as gifts inspired by newer properties like "Moana" and Hatchimals, one of last year‘s hottest toys.
These are the toys Amazon thinks will be the biggest sellers this holiday season.
So you’re skydiving and it has come time to open your parachute. You rip the cord and nothing happens. What next? Well, firstly you try and stay as come as possible because crapping your parachute pants at 12,500 feet isn’t going to ameliorate the situation at all. In fact, if you crap your pants while flying through the sky the situation becomes a lot worse in an instant.
This video is half comedy and half practical knowledge. It’s from Austin McConnell‘s YouTube channel. He gives some advice on what to do in the event that your parachute doesn’t open while skydiving.
First things first, you try and make yourself as big as possible. You want to take up as much space as your body will allow to try and create some drag to slow yourself down and give yourself more time to handle the situation. Once you ditch your primary chute you go for the reserve chute. If that doesn’t deploy then…well, your chances aren’t good but you still have some options. Your best chance of survival is to land in swamp, snow, or trees. If you see any of these three things you start to head for them. If you’re going to land without a chute you need the softest ground possible. Now, I don’t want to spoil this entire video, so I’ll stop recapping it now and let you watch the clip above.