Summary of “How Our Beliefs Can Shape Our Waistlines”

A recent epidemiological study suggests that our beliefs about how much we exercise may substantially influence our health and longevity, even if those beliefs are objectively inaccurate – which hints that upending our thinking about exercise might help us whittle away pounds, whether we work out more or not.
Crum and her co-author studied 84 female hotel-room attendants, who told the researchers that they felt they completed little or no daily exercise, although their work consisted mostly of physical labor.
Crum and her colleague explained to half of them that they were meeting or exceeding national recommendations for 30 minutes of daily exercise; a month later, when the researchers checked back, the women said they believed they were getting more exercise than before.
For the new study, Crum and a different co-author, Octavia Zahrt, turned to two federal databases, the National Health Interview Survey and the National Health and Nutrition Examination Survey, which contain health data about representative samples of Americans.
The scientists homed in on information from 61,141 participants who answered questions about whether they felt they were getting more, less or about the same amount of exercise as most people their age.
Risk of early death was up to 71 percent higher than for the group that, correctly or not, felt confident that they exercised more than their peers.
This type of study cannot prove that exercise beliefs directly cause life spans to shorten or grow; it can show only that the two issues are related.
Self-comparisons might also dampen exercise motivation, leading to declining health.

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Summary of “The GANfather: The man who’s given machines the gift of imagination”

The goal of GANs is to give machines something akin to an imagination.
When future historians of technology look back, they’re likely to see GANs as a big step toward creating machines with a human-like consciousness.
Yann LeCun, Facebook’s chief AI scientist, has called GANs “The coolest idea in deep learning in the last 20 years.” Another AI luminary, Andrew Ng, the former chief scientist of China’s Baidu, says GANs represent “a significant and fundamental advance” that’s inspired a growing global community of researchers.
In one widely publicized example last year, researchers at Nvidia, a chip company heavily invested in AI, trained a GAN to generate pictures of imaginary celebrities by studying real ones.
Once it’s been trained on a lot of dog photos, a GAN can generate a convincing fake image of a dog that has, say, a different pattern of spots; but it can’t conceive of an entirely new animal.
Researchers at Yale University and Lawrence Berkeley National Laboratory have developed a GAN that, after training on existing simulation data, learns to generate pretty accurate predictions of how a particular particle will behave, and does it much faster.
Hany Farid, who studies digital forensics at Dartmouth College, is working on better ways to spot fake videos, such as detecting slight changes in the color of faces caused by inhaling and exhaling that GANs find hard to mimic precisely.
Researchers are already highlighting the risk of “Black box” attacks, in which GANs are used to figure out the machine-learning models with which plenty of security programs spot malware.

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Summary of “Why Self-Taught Artificial Intelligence Has Trouble With the Real World”

In 2016, Google DeepMind’s AlphaGo thrashed champion Lee Sedol at the ancient board game Go after poring over millions of positions from tens of thousands of human games.
The past year also saw otherworldly self-taught bots emerge in settings as diverse as no-limit poker and Dota 2, a hugely popular multiplayer online video game in which fantasy-themed heroes battle for control of an alien world.
One characteristic shared by many games, chess and Go included, is that players can see all the pieces on both sides at all times.
An even more daunting game involving imperfect information is StarCraft II, another multiplayer online video game with a vast following.
Before the release of AlphaGo and its progeny, the DeepMind team achieved its first big, headline-grabbing result in 2013, when they used reinforcement learning to make a bot that learned to play seven Atari 2600 games, three of them at an expert level.
Within the larger category of reinforcement learning, board games and multiplayer games allow for an even more specific approach.
In game after game, an algorithm in a self-play system faces an equally matched foe.
Since 2008, hundreds of thousands of human players have attempted Foldit, an online game where users are scored on the stability and feasibility of the protein structures they fold.

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Summary of “Better climate science has opened the door to lawsuits against Big Oil”

These lawsuits are also a sign that the science connecting climate change to damaging events has greatly improved.
Though scientists still warn that it’s inaccurate to speak of weather events being “Caused” by climate change – weather always has multiple causes – better climate models, more powerful computers, and refined methodologies now allow researchers to quantify how climate change has increased the likelihood or severity of heat waves, droughts, deluges, and other extreme events.
Combined with attribution science, the two fields form a sort of climate forensics, enabling communities to point to an ostensibly natural disaster, find the fingerprints of climate change, and trace them back to an Exxon or BP. If the current volley of lawsuits over adaptation costs are successful, they will likely be followed by others: Phoenix might sue over deadly heat, Boulder over its shrinking ski season, or Houston over torrential rain.
“Advances in the science of extreme weather event attribution have the potential to change the legal landscape in novel ways.” The better attribution science gets, the easier it will be to argue that governments should have foreseen climate risks and prepared for them – and to hold them liable if they fail to.
The new lawsuits from Santa Cruz, New York, and elsewhere may fare better, according to Michael Burger, the executive director of Columbia University’s Sabin Center for Climate Change Law.
If the new round of lawsuits go to trial, there will be a bitter fight over these two links in the causal chain: that these companies contributed to climate change, and that climate change is causing these particular harms.
In a petition filed last month in a Texas district court, the company accused the California communities of “Abusive law enforcement tactics” designed to stifle the company’s “First Amendment right to participate in the national dialogue about climate change and climate policy.” Seeking depositions and documents, Exxon also accused the communities of failing to tell bondholders about the climate risks cited in their lawsuits.
It’s standard practice for fossil fuel companies to push back fiercely against attempts to hold them accountable for climate change, but it’s easy to see why the current round of lawsuits would be worrisome.

The orginal article.

Summary of “Why A.I. Researchers at Google Got Desks Next to the Boss”

A growing number of tech companies are pushing research labs and other far-reaching engineering efforts closer to the boss.
A year ago, the Google Brain team of mathematicians, coders and hardware engineers sat in a small office building on the other side of the company’s campus.
“Any C.E.O. thinks a lot about where people are sitting – who they can walk around and have casual conversations with,” said Diane Greene, who oversees Google’s cloud computing team and sits on the board of Alphabet, Google’s parent company.
Google is placing big bets on the A.I. being explored by researchers like Mr. Goodfellow.
These big companies are trying to duplicate the vibe of a Silicon Valley start-up, where the boss is next to everyone.
Ms. Greene, who was the chief executive of the software company VMware, said she had always made a point of sitting beside the top engineers because they saw the company’s future.
After Facebook went public and started a big push for revenue, important members of the ad team moved next to the boss, said Antonio García Martínez, who wrote a book about his experiences inside Facebook.
The boss is also showing them how important they are to the company.

The orginal article.

Summary of “China’s great leap forward in science”

These days, Chinese scientists stand at least as good a chance of making a global impact on science from within China itself.
In January, the United States National Science Foundation reported that the number of scientific publications from China in 2016 outnumbered those from the US for the first time: 426,000 versus 409,000.
“The startup packages for researchers in good universities in China can be significantly higher than Hong Kong universities can offer,” says Che Ting Chan, a physicist at the Hong Kong University of Science & Technology in what was previously China’s affluent and westernised neighbour.
According to quantum physicist Jian-Wei Pan of the University of Science and Technology in Hefei, as a relative latecomer to the global scientific stage, China needs such incentives as a way of maintaining enthusiasm.
The pattern seems clear, and is worth heeding by other nations: despite China’s reputation for authoritarian and hierarchical rule, in science the approach seems to be to ensure that top researchers are well supported with funding and resources, and then to leave them to get on with it.
It’s with good reason Poo asserts that China has become a world leader in stem-cell science and regenerative medicine.
China is taking great strides in other areas of biological science too.
In 2016 China initiated an international project called Quantum Experiments at Space Scale and launched a satellite designed for quantum data handling, called Micius after the romanised name of the ancient Chinese philosopher Mozi.

The orginal article.

Summary of “Google is using 46 billion data points to predict a hospital patient’s future”

Some of Google’s top AI researchers are trying to predict your medical outcome as soon as you’re admitted to the hospital.
To conduct the study, Google obtained de-identified data of 216,221 adults, with more than 46 billion data points between them.
The data span 11 combined years at two hospitals, University of California San Francisco Medical Center and University of Chicago Medicine.
The biggest challenge for AI researchers looking to train their algorithms on electronic health records, the source of the data, is the vast, disparate, and poorly-labelled pieces of data contained in a patient’s file, the researchers write.
In addition to data points from tests, written notes have traditionally been difficult for automated systems to comprehend; each doctor and nurse writes differently and can take different styles of notes.
To compensate for this, the Google approach relies on three complex deep neural networks that learn from all the data and work out which bits are most impactful to final outcomes.
After analyzing thousands of patients, the system identified which words and events associated closest with outcomes, and learned to pay less attention to what it determined to be extraneous data.
Google heavy-hitters like Quoc Le, credited with creating recurrent neural networks used for predictions based on time, and Jeff Dean, a legend at the company for his work on Google’s server infrastructure, are both on the paper, as well as Greg Corrado, a director at the company involved in high-profile projects like translation and its Smart Reply feature.

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Summary of “10 Monkeys and a Beetle: Inside VW’s Campaign for ‘Clean Diesel'”

“All of the research work commissioned with the E.U.G.T. was accompanied and reviewed by a research advisory committee consisting of scientists from renowned universities and research institutes,” Daimler said in a statement.
Volkswagen said in a statement that the researchers had never managed to publish a complete study.
Documents produced in legal proceedings show that in August 2016 Michael Spallek, the director of the automakers’ research group, emailed the Lovelace Respiratory Research Institute, the Albuquerque organization that conducted the tests with monkeys.
David King, a former chief scientific adviser to the British government, recalled being taken to a lab in the early 2000s where 10 diesel vehicles were running on rollers.
The automakers’ research group was created in 2007, as Volkswagen was readying a major push to market diesel technology in the United States, which has stricter limits on nitrogen oxide emissions than Europe.
Elsewhere, a regional court in Austria cited the research in a 2014 ruling against residents of Graz who had sued to force officials to restrict diesel traffic.
The research group intended the Albuquerque experiment to be a rebuttal to a 2012 finding by a division of the World Health Organization that had classified diesel exhaust as a carcinogen.
The automakers’ research group set out to show that new diesel vehicles were better.

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Summary of “Why People Dislike Really Smart Leaders”

Although previous research has shown that groups with smarter leaders perform better by objective measures, some studies have hinted that followers might subjectively view leaders with stratospheric intellect as less effective.
Decades ago Dean Simonton, a psychologist the University of California, Davis, proposed that brilliant leaders’ words may simply go over people’s heads, their solutions could be more complicated to implement and followers might find it harder to relate to them.
The researchers looked at 379 male and female business leaders in 30 countries, across fields that included banking, retail and technology.
IQ positively correlated with ratings of leader effectiveness, strategy formation, vision and several other characteristics-up to a point.
The researchers suggest the “Ideal” IQ could be higher or lower in various fields, depending on whether technical versus social skills are more valued in a given work culture.
“To me, the right interpretation of the work would be that it highlights a need to understand what high-IQ leaders do that leads to lower perceptions by followers,” he says.
“The wrong interpretation would be, ‘Don’t hire high-IQ leaders.'”.
The study’s lead author, John Antonakis, a psychologist at the University of Lausanne in Switzerland, suggests leaders should use their intelligence to generate creative metaphors that will persuade and inspire others-the way former U.S. President Barack Obama did.

The orginal article.

Summary of “Does Your Gut Hold the Secret to Performance?”

Hyde manages the American Gut Project at the university’s Knight Lab, which is five years into a deeply ambitious effort to map the average American’s bacterial makeup-what scientists call the human microbiome.
How to Boost Your Microbiome Wondering how to ensure that your gut is healthy? We’re here to answer your most pressing questions.
“People call the microbiome the forgotten organ,” says Erica Sonnenburg, a micro­biologist at Stanford University who has made big strides connecting the microbiome and the immune system.
Thus far the American Gut Project has found our digestive tracts to be so diverse in microbial content, and so unique to us and our individual lifestyles, that researchers really can’t yet say what a “Normal” gut should look like-let alone an elite athlete’s gut.
Shanahan’s colleague Mick Molloy had been a team doctor for the national rugby team, and in 2011 Shanahan asked him, “What do you suppose the microbiome of a professional athlete looks like?” Molloy made some calls, and the team agreed to help the researchers find out.
“I can’t do that here,” said Gilbert, of the University of Chicago’s Microbiome Center, adding, “There’s a lot of snake oil out there.” Ixcela, like many of the new microbiome companies, has not yet published peer-reviewed papers ­attesting to its products’ efficacy, though it does plan to publish a study about Team USA’s results.
Hyde and her team at the American Gut Project will analyze your microbiome for about a hundred bucks, but she stresses that the test is not diagnostic.
In Australia, Nicholas West, a researcher at Queensland’s Griffith University, has been meticulously testing publicly available probiotics on national-team athletes, based on their personal microbiomes, to help ward off pre-competition illness.

The orginal article.