Japan’s population is shrinking. Last year it fell by nearly 450,000 people. Not since records began in 1899 had so few babies been born (921,000). Before that, 2017 had also set a record. Meanwhile the number of people passing away last year set a post-war record. The figures are part of a larger pattern in which births have declined and deaths increased steadily for decades.
Less noticed is another alarming figure that’s been growing. According to the latest government statistics, the number of abandoned homes in Japan reached a record high of 8.5 million as of Oct. 1, 2018, up by 260,000 from five years earlier. As a proportion of total housing stock, abandoned homes reached 13.6%.
The U.S. has been an “island of stability” as economic woes grow all over the world. Other such islands exist, too.
Australia is high on the list. The last Down Under recession was 27—yes, 27—years ago in 1991. No other developed economy can say the same.
The long streak has a lot to do with being one of China’s top raw material suppliers during its historic boom. Australia has done other things right, too.
But all good things come to an end. While not officially in recession yet, Australia’s growth is slowing.
Will robots become self-aware? Will they have rights? Will they be in charge? Here are five scenarios from our future dominated by AI.
SMITHSONIAN MAGAZINE | April 2018
In June of 1956, A few dozen scientists and mathematicians from all around the country gathered for a meeting on the campus of Dartmouth College. Most of them settled into the red-bricked Hanover Inn, then strolled through the famously beautiful campus to the top floor of the math department, where groups of white-shirted men were already engaged in discussions of a “strange new discipline”—so new, in fact, that it didn’t even have a name. “People didn’t agree on what it was, how to do it or even what to call it,” Grace Solomonoff, the widow of one of the scientists, recalled later. The talks—on everything from cybernetics to logic theory—went on for weeks, in an atmosphere of growing excitement.
What the scientists were talking about in their sylvan hideaway was how to build a machine that could think.
The spectre of superintelligent machines doing us harm is not just science fiction, technologists say – so how can we ensure AI remains ‘friendly’ to its makers?
It began three and a half billion years ago in a pool of muck, when a molecule made a copy of itself and so became the ultimate ancestor of all earthly life. It began four million years ago, when brain volumes began climbing rapidly in the hominid line.
Fifty thousand years ago with the rise of Homo sapiens sapiens.
Ten thousand years ago with the invention of civilization.
Five hundred years ago with the invention of the printing press.
Fifty years ago with the invention of the computer.
Are you taking in too much information every day? If so, be on the lookout for this potentially dangerous new condition.
Obesity and dramatic overweight are a huge global problem, costing an estimated $450 billion per year in the U.S. alone, where more than two-thirds of people are overweight and an estimated 35.7% are considered obese. But that’s just physical obesity. The exact same processes that companies use to trick us into wanting to eat and eat are also being used to get us to spend more and more time online.
Imagine strolling through a cemetery at night, the wooded path softly illuminated by a canopy of glowing pods filled with human remains suspended overhead and transforming decomposition into electricity until the body is finally gone. The cycle of life complete, the light then dims to dark, the pod taken down and replaced by a bright new body shining down upon the path from its star-like grave.
While this may sound like the stuff of science fiction, in reality it’s a reimagined cemetery of the future called the Sylvan Constellation, a system where microbial fuel cells facilitate the body’s decomposition and transform it into light. More than a ghostly fantasy, this project from DeathLAB — a Columbia University–based interdisciplinary research and design initiative rethinking how we live with death in the metropolis — is a potential solution to one of the biggest problems cities are facing: We’re running out of space to store the dead, and the way we do it now is environmentally disastrous.
Switzerland Swiss army honor guard soldiers troops military
Switzerland hasn’t had a mass shooting since 2001, when a man stormed the local parliament in Zug, killing 14 people and then himself.
The country has about 2 million privately owned guns in a nation of 8.3 million people. In 2016, the country had 47 attempted homicides with firearms. The country’s overall murder rate is near zero.
The National Rifle Association often points to Switzerland to argue that more rules on gun ownership aren’t necessary. In 2016, the NRA said on its blog that the European country had one of the lowest murder rates in the world while still having millions of privately owned guns and a few hunting weapons that don’t even require a permit.
But the Swiss have some specific rules and regulations for gun use.
Business Insider took a look at the country’s past with guns to see why it has lower rates of gun violence than the US, where gun death rates are now at their highest in more than 20 years.
Nine more have ended veteran homelessness. It’s part of a national program called Built for Zero that uses a data-based approach to help officials figure out exactly who needs what services. Now it’s accelerating its work in 50 more cities.
In late February, the city of Abilene, Texas, made an announcement: It had ended local veteran homelessness. It was the first community in the state and the ninth in the country to reach that goal, as part of a national program called Built for Zero. Now, through the same program, Abilene is working to end chronic homelessness. While homelessness might often be seen as an intractable problem because of its complexity–or one that costs more to solve than communities can afford–the program is proving that is not the case.
“By ending homelessness, we mean getting to a place where it’s rare, brief, and it gets solved correctly and quickly when it does happen,” says Rosanne Haggerty, president of Community Solutions, the nonprofit that leads the Built for Zero program. “That’s a completely achievable end state, we now see.” The nonprofit, which calls this goal “functional zero,” announced today that it is accelerating its work in 50 communities.
A man wearing a mask rides a bicycle along the Han river in Seoul, South Korea, Wednesday, March 6, 2019. South Korean President Moon Jae-in has proposed a joint project with China to use artificial rain to clean the air in Seoul, where an acute increase in pollution has caused alarm.
Garbage in is garbage out. There’s no saying more true in computer science, and especially is the case with artificial intelligence. Machine learning algorithms are very dependent on accurate, clean, and well-labeled training data to learn from so that they can produce accurate results. If you train your machine learning models with garbage, it’s no surprise you’ll get garbage results. It’s for this reason that the vast majority of the time spent during AI projects are during the data collection, cleaning, preparation, and labeling phases.
According to a recent report from AI research and advisory firm Cognilytica, over 80% of the time spent in AI projects are spent dealing with and wrangling data. Even more importantly, and perhaps surprisingly, is how human-intensive much of this data preparation work is. In order for supervised forms of machine learning to work, especially the multi-layered deep learning neural network approaches, they must be fed large volumes of examples of correct data that is appropriately annotated, or “labeled”, with the desired output result. For example, if you’re trying to get your machine learning algorithm to correctly identify cats inside of images, you need to feed that algorithm thousands of images of cats, appropriately labeled as cats, with the images not having any extraneous or incorrect data that will throw the algorithm off as you build the model. (Disclosure: I’m a principal analyst with Cognilytica)
As older workers look to retire, companies reckon with how to replace departing skill sets
Baby boomers are entering their final years in the workforce, and their relationships with their employers are changing. Some companies are considering offering older workers partial-year employment and shorter hours.The youngest baby boomers are around 55 years old. The oldest are in their 70s. MostAmericans don’t remember a workforce without the largest generation.
And yet, as boomers enter their final years in the workforce, their retirements are taking companies by surprise.
In the next five years, almost three-quarters of the companies surveyed in 2018 by Willis Towers Watson, a risk-management and insurance brokerage company, expect to face significant or moderate challenges from late retirements. But because nothing is predictable, a significant share are also worried about early ones.
