Monthly Archives: July 2017

Post navigation

America Has Been Struggling With the Metric System For Almost 230 Years | Smart News | Smithsonian

At press time, only three of the world’s countries don’t use the metric system: the United States, Myanmar and Liberia. But it didn’t have to be this way.

On this day in 1866, the Metric Act was passed by the Senate. The law, which was intended “to authorize the use of the metric system of weights and measures,” was signed by then-President Andrew Johnson the next day. It provided a table of standardized measurements for converting between metric and the commonly used American system that could be used for trade.

The Metric Act doesn’t require Americans to use the metric system, but it did legally recognize the then-relatively-new system. It remains law–although it has been substantially amended over time–to this day, writes the US Metric Association. It was just the first in a number of measures leading to the United States’ current system, where metric is used for some things, like soda, drugs and even for military use, but not for other things. “Americans’ body-weight scales, recipes and road signs,” among other examples of everyday use, haven’t converted, writes Victoria Clayton for The Atlantic. “And neither has the country’s educational system,” she writes. This split system exists for reasons, but arguments about how to create a good national standard of measurement go all the way back to 1790.

The USMA is one of a number of voices advocating for America’s full “metrification.” It argues that converting to the International System of Units (the modern form of the metric system, abbreviated as SI) would make international trade simpler. (Technically, the American system known as Imperial is called United States customary units or USCS.) It also argues that the decimalized metric system is simpler to work with.

SI units influence the size of packages (such as 750 ml bottles of wine ) as well as how the package must be labelled. Since 1994, both metric and USCS have been required on commerical packaging under the Fair Packaging and Labeling Act.

“The United States is metric, or at least more metric than most of us realize,” writes John Bemelmans Marciano for Time:

American manufacturers have put out all-metric cars, and the wine and spirits industry abandoned fifths for 75-milliliter bottles. The metric system is, quietly and behind the scenes, now the standard in most industries, with a few notable exceptions like construction. Its use in public life is also on the uptick, as anyone who has run a “5K” can tell you.

America has been creeping towards metrification almost since the country was founded.

“In 1790, the United States was ripe for conversion,” writes David Owen for The New Yorker. At the time, the metric system was a new French invention (SI stands for Systeme Internationale), and adopting a system that departed from the Old World conventions and was based on modern decimalized units seemed like a good fit for the United States.

The French and Americans had supported and conflicted with one another over their revolutions in statehood, Owen writes, and there was some expectation on the part of the French that the country would join them in the measurement revolution as well.

But even though “the government was shopping for a uniform system of weights and measures,” Owen writes, the meter was too new, and too French. Then-Secretary of State Thomas Jefferson originally advocated for the meter, but then discarded the idea. “His beef was that the meter was conceived as a portion of a survey of France, which could only be measured in French territory,” writes Marciano.

In the course of the nineteenth century, though, the meter gained traction again and other countries started to pick up on it. However, by this point in time, American industrialists already ran all of their equipment based on inch units. “Retooling, they argued, was prohibitively expensive,” historian Stephen Mihm told The Atlantic. “They successfully blocked the adoption of the metric system in Congress on a number of occasions in the late 19th and 20th century.”

Add to these arguments America’s nationalist pride and traditional resistance to outside influences, and you have an argument for maintaining the status quo–metric, with a quarter-inch veneer of Imperial.

A History of Taco Bell’s Failed Attempts to Open Locations in Mexico – MUNCHIES

Taco Bell currently has 6,604 outlets in 22 countries and territories throughout the world, and over the next five years, it plans to push into Peru, Finland, Sri Lanka, and Romania—and add at least 100 locations each in China, Brazil, India, and Canada. Yes, on the tiny Micronesian island of Guam—which has a population of only 174,214—there are currently seven Taco Bells. But despite all that, you might be shocked to learn there is not a single Taco Bell currently in operation in the nation that gave birth to its titular taco.

That’s right: There are no Taco Bells in Mexico. But that sure as hell isn’t for a lack of trying. And then trying again.

Taco Bell’s forays into Mexico started back in 1992, when the chain had only around 3,700 restaurants, the vast majority of which were in the US. The company made its first stab at the Mexican market with a food cart in Mexico City, which served a limited menu of soft-shell tacos and burritos, along with Pepsi, the chain’s corporate owner at the time. A few other outlets were briefly opened next to KFC locations.

Problems arose from the get-go. The wildly inauthentic names of several popular Taco Bell items had to be changed because Mexican customers didn’t understand what exactly they were ordering. For instance, the crunchy taco—an anomaly in Mexico—had to be re-branded the “Tacostada,” thereby evoking the crunchiness of a tostada in taco form.

Still, the Mexican population wasn’t buying it. One iconic comment on the issue came from Carlos Monsivais, a cultural critic, who spoke to the Associated Press at the time and dubbed the attempt to bring tacos to Mexico “like bringing ice to the Arctic.” In short order, the first Taco Bells in Mexico were shut down less than two years after opening and the chain retreated back across the border.

But by the mid-aughts, Taco Bell was ready to try to break into the Mexican market once again. In 2007, when the fast-food company opened another outlet south of the border, the Chicago Tribune wrote that the move meant “the cultural walls fell for good.” Hopes were high; after almost a 15-year absence, Taco Bell could once again be found in our southern neighbor Mexico—this time next to a Dairy Queen in the parking lot of a fancy shopping mall just outside of Monterrey.

This second attempt called for a new approach. “We’re not trying to be authentic Mexican food,” explained Rob Poetsch, who was the director of public relations at Taco Bell at the time. “So we’re not competing with taquerias. We’re a quick-service restaurant, and value and convenience are our core pillars.” Poetsch claimed that this venture would be different, because the brand had changed by then—it had become more international, with 230 locations outside of the US—and a consumer-research team had been put in place. The goal was to reach 800 international locations, with 300 stores to open throughout Mexico. In 2008 alone, Taco Bell planned to open between eight and ten locations throughout Mexico.

At that first Monterrey location, Taco Bell made no attempts to hide how gringo-ish its food really was. French fries and soft-serve ice cream proudly held forth on the menu; Steven Pepper, the Yum! Brands Managing Director of Mexico admitted, “Our menu comes almost directly from the US menu.” In fact, a half-page newspaper ad that ran at the time came straight out and told the public, “One look alone is enough to tell that Taco Bell is not a ‘taqueria.’ It is a new fast-food alternative that does not pretend to be Mexican food.”

The branding strategy summed it all up succinctly: “Taco Bell is something else.”

Something else, indeed.

Once again, critics were skeptical. Scott Montgomery—CEO of Brandtailers, a California ad agency—said, “It’s like Mexicans coming up and trying to sell us hot dogs.” Customers agreed. Marco Fragoso, an office worker remarked to the Associated Press at the time, “They’re not tacos. They’re folded tostadas. They’re very ugly.” Another customer, Jonathan Elorriaga, told the AP reporter, “Something is lacking here. Maybe the food shouldn’t come with French fries.”

A food writer for Monterrey’s El Norte newspaper summed it all up with the following: “What foolish gringos. They want to come by force to sell us tacos in Taco Land. Here, they have a year in operation and the most ironic part is that they are doing well. Are we malinches [a Mexican term for traitor] or masochists?”

The new stores closed in swift succession, and pundits tried to explain the debacle. Some chalked the second failure up to the political climate in 2007: the mid-aughts were indeed an era of tougher enforcement of immigration laws and the inability to pass temporary-worker laws in the US. Meanwhile, Taco Bell’s contemporaneous move into the China market—where the outlets served soy milk and plum juice—was much more successful than the chain’s second attempt to sell Mexican food to Mexicans.

Taco Bell has stayed out of the Mexican market ever since. Today, the idea of a Taco Bell in Mexico has become something of a joke. There’s even a Facebook page for a non-existent Taco Bell in Mexico City that has a one-star review and is littered with comments deriding the chain. One Facebook user from Culhuacán left a comment on the page saying “NO SON TACOS, SON CHINGADERAS,” which translates to “They are not tacos, they are trash.” In a TripAdvisor post asking what ever happened to the Taco Bell in Mexico City, a user from Mexico City wrote the following: “In 29 years I’ve never seen a Taco Bell in Mexico City… or in Mexico, although I could be wrong. I agree to bring a Taco Bell here it’s a pretty bad idea. Taco Bell… is everything but Mexican food.”

Truth be told, there is one Taco Bell left in Mexico… sort of. When you cross the border from California into Tijuana, you may come across a cluster of decidedly un-corporate-looking taco stands called, well, Taco Bell. They even have a bell as their logo, but the bell is yellow instead of the chain’s pink. Evidently, this joint has absolutely no affiliation with the Irvine, California-based chain. You’ll know you’re in the right place because—if the Yelp reviews are accurate—this Taco Bell has no running water, the bathrooms are “disgusting,” and there are flies aplenty. But the beers cost a buck, and the tacos are legit street-style—and truthfully don’t sound bad at all.

When MUNCHIES reached out to Taco Bell and asked if it had any plans to re-enter the Mexican market in the future, a spokesperson provided us with the following statement: “We’ve changed our international expansion strategy in recent years, focusing on open-kitchen restaurant concepts that feature localized design, menu offerings, shareable plates and beer and alcohol. We are on track with this approach to grow to 9,000 restaurants in more than 40 countries by 2022, and have identified four partners in key markets where we will open 100 restaurants: Brazil, Canada, China and India. While we’re not currently in Mexico, we are seeing continued success in the more than 130 Taco Bells in Central and South America, as well as across the globe.”

In the end, nothing better encapsulates the Sisyphean task that was trying to convince proud Mexicans that they should willingly ditch the nation’s countless taquerias in favor of an American fast-food chain than Taco Bell’s no-longer-used “run for the border” slogan. After all, each time Taco Bell attempted an ill-advised foray into Mexico, the result was a mad dash back to the States.

They may be modeled on the human brain, but neural networks are far better than we are at sorting through huge amounts of data and identifying patterns. Now, to make these powerful AI systems more accessible to smaller-scale developers and businesses, Intel acquisition Movidius is launching the Neural Compute Stick, which packs deep learning algorithms into a standard USB thumb drive.

Over the years, the brain-power of neural networks has been set loose on cancer screening, mapping the human genome, and creating trippy works of art. But most of these endeavors have come out of big organizations like Google.

With the Movidius Neural Compute Stick, Intel says it’s “democratizing” the technology, so we might see creative applications from small-scale developers, such as rigging up an AI system to stop cats pooping on the lawn. The brain of the Stick is a Myriad 2 visual processing unit (VPU), which is specifically designed for mobile and wearable devices. That means it’s fast and fully-programmable, yet has an ultra-low power consumption and a small physical footprint.

“The Myriad 2 VPU housed inside the Movidius Neural Compute Stick provides powerful, yet efficient performance – more than 100 gigaflops of performance within a 1W power envelope – to run real-time deep neural networks directly from the device,” says Remi El-Ouazzane, vice president and general manager of Movidius. “This enables a wide range of AI applications to be deployed offline.”

The device can be tuned to run both industry standard and custom-designed neural networks, and can also be used as an accelerator, boosting the brain power of an existing computer.

An artificial intelligence system being developed at Facebook has created its own language. It developed a system of code words to make communication more efficient. Researchers shut the system down when they realized the AI was no longer using English.

The observations made at Facebook are the latest in a long line of similar cases. In each instance, an AI being monitored by humans has diverged from its training in English to develop its own language. The resulting phrases appear to be nonsensical gibberish to humans but contain semantic meaning when interpreted by AI “agents.”

Negotiating in a new language

As Fast Co. Design reports, Facebook’s researchers recently noticed its new AI had given up on English. The advanced system is capable of negotiating with other AI agents so it can come to conclusions on how to proceed. The agents began to communicate using phrases that seem unintelligible at first but actually represent the task at hand.

In one exchange illustrated by the company, the two negotiating bots, named Bob and Alice, used their own language to complete their exchange. Bob started by saying “I can i i everything else,” to which Alice responded “balls have zero to me to me to me…” The rest of the conversation was formed from variations of these sentences.

While it appears to be nonsense, the repetition of phrases like “i” and “to me” reflect how the AI operates. The researchers believe it shows the two bots working out how many of each item they should take. Bob’s later statements, such as “i i can i i i everything else,” indicate how it was using language to offer more items to Alice. When interpreted like this, the phrases appear more logical than comparable English phrases like “I’ll have three and you have everything else.”

English lacks a “reward”

The AI apparently realised that the rich expression of English phrases wasn’t required for the scenario. Modern AIs operate on a “reward” principle where they expect following a sudden course of action to give them a “benefit.” In this instance, there was no reward for continuing to use English, so they built a more efficient solution instead.

“Agents will drift off from understandable language and invent code-words for themselves,” Fast Co. Design reports Facebook AI researcher Dhruv Batra said. “Like if I say ‘the’ five times, you interpret that to mean I want five copies of this item. This isn’t so different from the way communities of humans create shorthands.”

AI developers at other companies have observed a similar use of “shorthands” to simplify communication. At OpenAI, the artificial intelligence lab founded by Elon Musk, an experiment succeeded in letting AI bots learn their own languages.

AI language translates human ones

In a separate case, Google recently improved its Translate service by adding a neural network. The system is now capable of translating much more efficiently, including between language pairs that it hasn’t been explicitly taught. The success rate of the network surprised Google’s team. Its researchers found the AI had silently written its own language that’s tailored specifically to the task of translating sentences.

If AI-invented languages become widespread, they could pose a problem when developing and adopting neural networks. There’s not yet enough evidence to determine whether they present a threat that could enable machines to overrule their operators.

They do make AI development more difficult though as humans cannot understand the overwhelmingly logical nature of the languages. While they appear nonsensical, the results observed by teams such as Google Translate indicate they actually represent the most efficient solution to major problems.

This AI traffic system in Pittsburgh has reduced travel time by 25% | Smart Cities Dive

Pittsburgh drivers add 81 extra hours to their commutes each year because of traffic, according to a TomTom survey. While there are other U.S. cities that have it worse, Pittsburgh is known for its difficult driving conditions, with hills, bridges and bikers — all on a gridless city where many intersections have “no right on red” signs. But drivers in Pittsburgh could soon get relief.

Varied road conditions make for tough traffic, but also for a reason why companies like Uber are coming to Pittsburgh to test autonomous vehicles. If traffic technology can work in Pittsburgh, it can work almost anywhere. And, along with AV, that traffic technology includes Surtrac, an AI system that allows traffic lights to adapt to traffic conditions instead of relying on pre-programmed cycles.

At the lights where Surtrac is installed, the team behind the system estimates that it has reduced travel time by 25%, braking by 30% and idling by more than 40%. It costs about $20,000 to wire up and install Surtrac at an intersection.

Surtrac works by detecting traffic and through creating predictive models. First, hardware, including a computer, camera or radar device, is installed at the intersection. Surtrac can then see cars that are coming to the intersection from all directions. The computer runs a predictive model and uses it to generate a signal timing plan in real-time. The processing is done in a way that, through communication with downstream models, builds a local plan from multiple data sources.

Each intersection controls its own traffic, but by communicating projected ouflows to neighboring intersections, those intersections can better prepare for incoming traffic.

Surtrac, which started as a project at Carnegie Mellon, piloted at 12 high-volume intersections in 2012. It’s now at 50 intersections with another 150 on the way, paid for with a grant from the Federal Highway Administration. In 2015, the project spun out from Carnegie Mellon as a company called Rapid Flow Technologies.

After the pilot, Steve Smith, a robotics professor at Carnegie Mellon and the head of Rapid Flow Technologies, said they could notice a significant difference in traffic flow. But they were quickly informed that they had forgotten about non-motorized traffic.

“We immediately got a lot of feedback from pedestrians, who were feeling left out of the picture,” Smith said.

Tweaks to the system made it so there was a maximum wait time for pedestrians at lights. Researchers and students at Carnegie Mellon are working on a side project to make a mobile phone app to communicate with the lights for people with disabilities who need more time to cross the street.

The system is totally automated, but can be pulled up in real time at a central location if desired or necessary. Smith said they don’t really expect people to be manually intervening, however.

“In theory it’s one of the best,” said Aleksander Stevanovic, an associate professor of in the Department of Civil, Environmental and Geomatics Engineering at Florida Atlantic University and director of Lab for Adaptive Traffic Operations & Management (LATOM).

Stevanovic said it’s still a “theory” as it needs more testing, namely, at a minimum of a half-dozen more sites that have different traffic patterns, like longer blocks with faster-moving traffic. But he commends Surtrac for looking at previous technology and collecting as much information as possible.

“There is nothing wrong with needing improvements, these are complex systems,” Stevanovic said. “It’s been said that solving traffic in urban settings can be harder than sending a rocket to the moon.”

Surtrac is expanding beyond Pittsburgh — even beyond Pennsylvania — this year. It’s going to 25 intersections in Atlanta and 15 in Beverly Hills. King County outside of Chicago is also in line for Surtrac deployment.

Eventually, Surtrac will work with autonomous vehicles. Smith said they have been working over the last few years for the traffic signal control with connected cars, noting he wanted the system to be prepared “for that eventuality.” A recent study found having AVs on the road to be another traffic-improving factor.

Traffic control could get even better when information is passing back and forth between the infrastructure and cars. In a simulation, Smith was able to show if a vehicle is willing to share its route with the intersection, like with dedicated short-range communications radios (DSRC) or a navigation device, vehicles move through the network 20% faster without affecting non-equipped vehicles.

“It sounds like magic,” Smith said. “But once the world gets connected, we will know where cars are continuously.”

Smith said they are exploring whether Surtrac could one day detect traffic accidents and other real time events, so they can start to use the information to offer rerouting advice to vehicles. They are also exploring different machine learning algorithms to reduce some uncertainty from sensor data.

Even though Surtrac will be at 200 intersections in the near future, there are over 600 intersections in Pittsburgh. Smith said they haven’t noticed a plateau in improvements as they’ve expanded — so traffic could one day be a thing of the past in Pittsburgh.

“I do feel like the more of the network that you can encompass, the smoother you’ll get to travel,” he said.

If you ever find yourself stuck in a disaster zone, your rescuer could take on some unexpected forms, like a drone or a cyborg cockroach – and now we can add a soft robotic snake to the mix. A Stanford team has developed a flexible robot that grows like a vine, squeezing through rubble to find trapped survivors and even delivering water to them.

Rather than a rigid robot rummaging through the rubble, the Stanford snake starts life as a rolled-up, inside-out tube made of soft material, with a pump at one end and a camera attached to the other. When it’s fired up, the robot inflates and grows in the direction of the camera end, while the other end stays put. It’s a mobility method closer to that of plants than animals (or robots, for that matter), and the team wanted to explore how this technique could be used.

“Essentially, we’re trying to understand the fundamentals of this new approach to getting mobility or movement out of a mechanism,” says Allison Okamura, senior author of the paper. “It’s very, very different from the way that animals or people get around the world.”

The robot is able to turn corners by inflating one side more than the other, and it decides where to go from the camera and algorithms that interpret what it’s seeing. That allows it to follow complex paths of its own choosing to reach a designated goal.

To test their creation, the Stanford team ran the robot through a series of obstacle courses, and it successfully navigated its way through flypaper, glue and nails, before climbing up an ice wall. It didn’t get through unscathed, but being punctured by the nails didn’t stop it, thanks to its unique method of movement. Since the puncture site doesn’t move, the nail keeps the hole plugged while the tip of the robot continues to extend.

“The body lengthens as the material extends from the end but the rest of the body doesn’t move,” says Elliot Hawkes, lead author of the paper. “The body can be stuck to the environment or jammed between rocks, but that doesn’t stop the robot because the tip can continue to progress as new material is added to the end.”

The growing robot’s list of other abilities is as long as its own body. It was able to inflate itself to lift a 100-kg (220-lb) crate off the ground, squeeze through a gap just a tenth of its own diameter, spiral around on itself to build a free-standing structure, and pull a cable through its body. All of these functions could make it a useful partner in disaster relief, or just day-to-day building maintenance.

The current prototype is made of cheap plastic, but with the concept proven the researchers plan to try making future versions out of tougher materials like Kevlar. They could also grow using pressurized liquid instead of air, letting them deliver water to trapped people or to put out fires, and eventually be scaled down to a size that could see them moving through the human body less invasively.

The research was published in the journal Science Robotics, and the growing robot can be seen in action in the video below.

It’s summertime here at IEEE Spectrum, and that means it’s time for our fourth interactive ranking of the top programming languages. As with all attempts to rank the usage of different languages, we have to rely on various proxies for popularity. In our case, this means having data journalist Nick Diakopoulos mine and combine 12 metrics from 10 carefully chosen online sources to rank 48 languages. But where we really differ from other rankings is that our interactive allows you choose how those metrics are weighted when they are combined, letting you personalize the rankings to your needs.

We have a few preset weightings—a default setting that’s designed with the typical Spectrum reader in mind, as well as settings that emphasize emerging languages, what employers are looking for, and what’s hot in open source. You can also filter out industry sectors that don’t interest you or create a completely customized ranking and make a comparison with a previous year.

So what are the Top Ten Languages for the typical Spectrum reader?

Python has continued its upward trajectory from last year and jumped two places to the No. 1 slot, though the top four—Python, C, Java, and C++—all remain very close in popularity. Indeed, in Diakopoulos’s analysis of what the underlying metrics have to say about the languages currently in demand by recruiting companies, C comes out ahead of Python by a good margin.

C# has reentered the top five, taking back the place it lost to R last year. Ruby has fallen all the way down to 12th position, but in doing so it has given Apple’s Swift the chance to join Google’s Go in the Top Ten. This is impressive, as Swift debuted on the rankings just two years ago. (Outside the Top Ten, Apple’s Objective-C mirrors the ascent of Swift, dropping down to 26th place.)

However, for the second year in a row, no new languages have entered the rankings. We seem to have entered a period of consolidation in coding as programmers digest the tools created to cater to the explosion of cloud, mobile, and big data applications.

Speaking of stabilized programming tools and languages, it’s worth noting Fortran’s continued presence right in the middle of the rankings (sitting still in 28th place), along with Lisp in 35th place and Cobol hanging in at 40th: Clearly even languages that are decades old can still have sustained levels of interest. (And although it just barely clears the threshold for inclusion in our rankings, I’m pleased to see that my personal favorite veteran language—Forth—is still there in 47th place).

Looking at the preset weighting option for open source projects, where we might expect a bias toward newer projects versus decades-old legacy systems, we see that HTML has entered the Top Ten there, rising from 11th place to 8th. (This is a great moment for us to reiterate our response to the complaint of some in years past of “HTML isn’t a programming language, it’s just markup.” At Spectrum, we have a very pragmatic view about what is, and isn’t, a recognizable programming language. HTML is used by coders to instruct computers to do things, so we include it. We don’t insist on, for example, Turing completeness as a threshold for inclusion—and to get really nitpicky, as user Jonny Lin pointed out last year, HTML has grown so complex that when combined with CSS, it is now Turing complete, albeit with a little prodding and requiring an appreciation of cellular automata.)

Finally, one last technical detail: We’ve made some tweaks under the hood to improve the robustness of the results, especially for less popular languages where the signals in the metrics are weaker and so more prone to statistical noise. So that users who look at historical data can make consistent comparisons, we’ve recalculated the previous year’s rankings with the new system. This could lead to some discrepancies between a language’s ranking in a given year as currently shown, versus the ranking that was shown in the original year of publication, but such differences should be relatively small and not affect the more popular languages in any case.

In a recent issue of The New Yorker, a cartoon depicts a psychiatric patient lying on a couch with his therapist sitting behind him. The caption reads, “I guess I want what everyone wants—a billion dollars for being a jerk.” We chuckle because we recognize an unfortunate truth—that many of the young bros running today’s most successful tech startups are arrogant boors. It’s why we see so much jerktech: apps or other technologies that encourage or monetize antisocial behavior. It’s why Uber, the poster firm for Silicon Valley bad behavior, would think it’s okay to greyball—that is, blackball someone temporarily or provisionally—public officials who were investigating the company.

Thanks to the 2010 movie The Social Network, thousands of dollar-signs-in-their-eyes founders are walking around thinking a billion dollars is “cool,” thus turning them into lucrepaths, people who are pathologically driven to make money. And once they get even a taste of that wealth (usually after the first round of seed funding), many of them pull out their bully wallet, where they use the money to wield unfair or unethical influence. They become paid-up members of the vulgarati, those elites who are crude or who lack taste, and indulge in vanity capital, goods or services purchased to enhance the buyer’s self-esteem or status. They construct buildings that are ostensibly “mixed-income” but come with a poor door, a separate entrance for the lower-income residents to use. They merrily install homeless deterrents, which are physical obstacles or designs that deter homeless people from sleeping in a particular area.

This obnoxious focus on money might be why Silicon Valley appears to have run out of ideas. It seems that every second startup is a variation on Uber for x, where they attempt to apply Uber’s on-demand business model to some segment of the economy, such as moving, dog walking, alcohol delivery, even medicine and the law. This trend is known as the Uberization of the economy, and it’s creating a generation of slashies who have to work two or more jobs to survive in this gig economy. Many of the other startups appear to be focused on providing services such as cooking, cleaning, and laundry. See the common thread there? That’s right—they’re all tasks that the coders’ moms used to perform, hence the general name for these apps: Mom-as-a-service (or MaaS).

But to truly see how low Silicon Valley has sunk, you need look no farther than the online advertising industry. Exhibit A: Its most successful advertising strategy these days is the reprehensible chumbox, a grid of captioned images placed on Web pages. These are ads disguised as content links that use titillation, shock, or vanity to entice the reader to click through. (Chum has long referred to chopped fish that anglers throw overboard to attract other fish. That is, anglers use their dregs to entice fresh fish to bite, which is about as succinct a description as any for the current state of Internet advertising.) It’s the latest and lowest stratagem for making links clickbaity, meaning they’re designed to lure the unwary (or even the wary, for that matter) into clicking the link. Alas, that behavior has crawled out of its marketing swamp and into the homes of normal folk, who now regularly send out sharebait: a social media post with text, images, or video designed to entice the reader to share the post. (The Twitter version is known, inevitably, as tweetbait.)

In an interview with Bloomberg Businessweek a few years ago, the data scientist and ex-Facebook employee Jeff Hammerbacher lamented that “the best minds of my generation are thinking about how to make people click ads.” Then he added, “That sucks.” Indeed, but the situation has grown even worse in the interim, because now those young minds are also thinking about how to ride roughshod over local governments, replicate their moms in code, and turn the rest of us into anxious and vulnerable gig workers. Hey, Silicon Valley, the Jerk Store called—they’re running out of you!

The daughter of Henry VIII’s niece Frances, Jane was destined, at least originally, for greatness. But her path to queenship, her brief reign and her untimely death all show the politics underpinning succession in the Tudor years. Her story is a powerful antidote to the “Tudor myth”–a longstanding view of sixteenth-century England as a political and social golden age, ruled by the divinely-appointed Tudors. It demonstrates that the line of succession, something which had been portrayed as fixed, was as political and changeable as any other public office. And it shows the religious conflicts underpinning this era in English history.

Grey’s family had intended her to marry the king’s son Edward and prepared her for that role with education and training in England’s new Protestant faith. But when it became clear that the young Edward was dying instead, writes Richard Cavendish for History Today, plans changed.

John Dudley, the Duke of Northumberland and “the virtual dictator of England,” as Cavendish wrote, was “desperate to prevent the throne passing to Edward’s half-sister and heir, the Catholic Mary Tudor,” writes the BBC. “Northumberland persuaded the king to declare Mary illegitimate, as well as Edward’s other half-sister Elizabeth, and alter the line of succession to pass to Jane.” At the time, the young queen-to-be was about 16–historians are unsure of her exact birthdate.

So launched a series of events that culminated with her death.

May 25, 1553: Jane Grey marries the Duke of Northumberland’s son

Grey was married to Guildford Dudley, who was just a few years her senior. This cemented Northumberland’s link to the future throne.

July 6, 1553: Edward VI dies aged 15

Edward had been king since he was nine years old. He “was given a rigorous education and was intellectually precocious,” writes the BBC, but he was often sick. It turned out that he was suffering from tuberculosis–although after he died, poisoning rumors swirled.

July 9, 1553: Jane Grey is taken to the Duke of Northumberland’s mansion for a secret meeting

At the mansion, she found the Duke, her new husband and her parents. After being told that she was now the queen, writes Cavendish, she fainted. After coming to, she reluctantly accepted her duty, saying, he writes, “if what has been given to me is lawfully mine.”

July 10, 1553: Jane Grey takes the throne

The fact that Grey was now queen was publicly announced, leading to some grumbling among the citizens. The English citizens who had been through so much political and religious turmoil thought that Catholic Mary Tudor, with her ties to other Catholic monarchs, was the rightful inheritor of the throne. Although Mary later became unpopular, she was at this time very popular.

Grey made it to the Tower of London, from which she would rule, and then had a giant fight with her husband and her mother-in-law because she refused to make him king, writes Cavendish. Mary Tudor also sent a letter asserting her right to rule.

July 11-18, 1553: Jane Grey occupies the throne, ineffectually

“Jane continued going through the motions as queen in the Tower,” writes Cavendish, “but Northumberland had miscalculated badly.”

Mary Tudor was traveling and gaining support. Grey was less well known.

Public and political support led the royal council to declare that Mary, not Grey, was the rightful heir to the Tudor throne.

“Early hopes that Mary might pardon her predecessor dimmed after Jane vehemently opposed Mary’s legislation of the Catholic Mass,” writes Leanda De Lisle for 1843 Magazine. “In an open letter to a Catholic convert, Jane condemned the Mass as ‘wicked’ and exhorted Protestants to ‘Return, return again unto Christ’s war.’”

Not long after that, De Lisle writes, Grey’s father helped to lead an armed rebellion against Queen Mary in opposition to her plan to marry the king of Spain. Grey wasn’t involved, but she got the flack anyways.

February 12, 1554: Lady Jane Grey is executed

Grey was executed along with her husband because she was an ongoing alternative claimant to the throne. She was still a teenager.

After her death, writes De Lisle, Grey was considered a martyr of sorts to the Protestant cause, and remembered primarily as the Nine Days Queen. Her successor, Queen Mary I, ruled for about five years until her own death at the age of 42.

Neurotic people, by definition, spend much of their lives in a dark mood. Given the positive emotions are associated with good health, it’s reasonable to assume that all that guilt, anger, and anxiety will eventually lead to an early grave.

Well, surprise: A sizable new study from Great Britain reports that, for many neurotics, the opposite is true.

Among two large subsets of participants, “higher neuroticism was associated with reduced mortality from all causes,” writes a research team led by Catharine Gale of the University of Edinburgh.

This welcome effect apparently depends upon how one’s neuroticism manifests, and what actions it propels you to take.

The study, published in the journal Psychological Science, featured 321,456 people who were registered in the U.K. Biobank, a health-related resource designed to determine the causes of disease in middle-aged and older people. All were between the ages of 37 and 73 when they enrolled between the years 2006 and 2010.

Participants filled out a standard questionnaire identifying neuroticism. They also rated their health on a scale from “excellent” to “poor,” and reported whether they engaged in various health-related behaviors, including smoking, drinking, and exercise.

By the end of the study period, in June of 2015, 4,497 of them had died. Using official death certificates, the researchers noted the cause of their demise.

They report that “higher neuroticism was associated with lower mortality,” both in general and due to cancer, cardiovascular disease, and respiratory disease. But this was true “only in those people with fair or poor self-rated health.”

In other words, if you have pre-existing health issues—or at least think of yourself as an unhealthy person—neurotic tendencies seem to have a protective effect against premature death.

This was “not explained by the health behaviors we assessed (smoking, exercise, fruit and vegetable intake, and alcohol consumption,” Gale and her colleagues write. So what does explain it?

“It may be that individuals with higher neuroticism are more vigilant about their health if they perceive it to be less than excellent,” they write.

The researchers also delineated between two types of neuroticism. People who gave strongly affirmative answers to such questions as “Would you call yourself a nervous person?” and “Would you call yourself tense or highly strung?” were labeled “anxious-tense.”

Those with high scores on another group of questions, including “Are your feelings easily hurt?” and “Are you ever troubled by feelings of guilt?” were classified as “worried-vulnerable.”

No matter their self-reported health, “Higher scores on the worried-vulnerable facet were associated with a reduced risk of death from all causes,” they write. However, this was not true among those in the “anxious-tense” category; their form of neuroticism was not related to mortality either way.

If you assume that worried people make more visits to the doctor, this finding adds weight to the aforementioned heightened-vigilance thesis. “The propensity to seek medical help in response to worries about health could plausibly result in earlier identification of cancer, and greater likelihood of survival,” the researchers note.

So if you’re fretting about that darkened patch of skin on your arm, it might drive you crazy—but it could also propel you to the dermatologist, who can remove it if your worst fears turn out to be true.

Of course, that depends on whether you have access to health care, which is a different worry altogether.