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Monthly Archives: February 2017
Local robotics students headed to World Championship tournament – KOLO
Posted: February 7, 2017 at 8:19 am
CARSON CITY, Nev. (KOLO) - At Eagle Valley Middle School, six students are working to improve their LEGO robot. They're still not satisfied, even though it played a critical role in them winning the trophy at the Northern Nevada FIRST LEGO LEAGUE Championship last month.
"It was just an incredible feeling!" says Nevan McIlwee, 13. "To see all our hard work just paid off to get to that."
For this group, which calls itself the Jedi Engineers, winning that competition isn't enough. But it was a big deal. They beat out dozens of other teams at the competition at UNR. Teams were judged on their robots' ability to complete tasks and on their problem-solving skills.
Now, this group of seventh and eighth graders is gearing up for the World Championship Tournament in April in Houston, Texas. They will compete against more than a hundred other teams who are also champions in their own countries.
"It means a lot," says Kai Miller, 12, a Jedi Engineer. "I mean, we're going to see teams from all over the world. Teams from Europe, Africa, China, Russia, South America... It's really, really big for our community."
And while it was tough enough to qualify for this tournament, raising money is the new challenge.
"We are doing huge fundraising because it is going to be so expensive to go to World Festival," says Lisa Stocke-Koop, Eagle Valley STEM teacher and LEGO coach. "It's going to be over $20,000 before we're done."
That's because the students have also been invited to compete in an international tournament in England. Their teacher believes the kids are not just an inspiration for other students.
"These guys, they bring tears to my eyes," says Stocke-Koop. "When I look at what they've done and I look at how proud they are of their achievements... every one of these kids could change the world. And I am just so thrilled that I'm a part of their education."
The team has set up a gofundme account online to raise money for travel expenses. You can find it here.
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How to keep your children safe online as it’s revealed half of six-year-olds use the internet – Mirror.co.uk
Posted: at 8:18 am
Six-year-old children are as digitally advanced today as 10-year-olds were three years ago and nearly half of them use the internet for general online browsing, new research reveals.
A worrying 44% of children aged six are using the internet alone in their bedrooms and 41% of them are using it at home without supervision.
They are using social media , streaming content, and even uploading their own videos to YouTube.
To mark Safer Internet Day, web safety group Internet Matters are urging parents to take action at an early age and keep their children safe online.
Alarmingly the number of parents saying they are always present to supervise their child aged six when they are online, using computer devices, has gone down in the last three years from 53% to 43%.
Mum-of-four Zoe Holland, 39, from Uckfield, East Sussex, has noticed the changes first hand as her children Morris, 12, Leon, 10, Daisy, six and Logan, one, have gravitated towards spending more time online.
She and husband Matt, 37, are constantly learning when it comes to monitoring their children on the internet.
She says: Daisy mostly uses my tablet so I manage the device that shes on and shell mostly use the tablet for going on cartoons on Netflix and games.
"But my older children are interested in making their own YouTube videos and have their own YouTube accounts.
"Theyre so technology savvy, were not always aware of what theyre up to. I can see them becoming more advanced at understanding the internet in the future.
It can be isolating for children if you dont let them have the smart phones that their friends at school have, theres a lot of peer pressure.
Zoe, who runs blog jugglingonrollerskates.com, reveals that she worries about what her kids can be exposed to online.
It terrifies me what they can just look up on Google, she says. I would hate them to come across something that is shocking.
"Weve made it a rule that theyre not allowed to delete their internet history so we have that awareness. But its a learning curve.
"We are looking in to accountability apps - where you monitor and control what the children use on the phone. For peace of mind and visibility we want to know whats going on. Its all about trust.
EastEnders actor Danny-Boy Hatchard, who plays Lee Carter in the BBC soap, thinks that internet safety should be taught in schools.
The star, working with Safer Internet Day, told the Mirror: Social media safety should be on the national curriculum.
Children need to be taught about these tools to educate them and make sure theyre in a safe environment when theyre online. Parents need to monitor their kids use closely.
Pyschologist Dr Linda Papadopoulos, author of Unfollow: Living Life On Your Own Terms, says: This research shows just how quickly young children are advancing in the digital world.
"It also serves as a stark reminder why parents need to be extra vigilant and arm their children with the tools to stay safe online.
As well as setting up the relevant parental controls, its important to make sure you set boundaries when it comes to how your children use the internet at home.
Today is Safer Internet Day. For more information, help and resources, go to http://www.saferinternet.org.uk .
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Faultlines, black holes and glaciers: mapping uncharted territories – The Guardian
Posted: at 8:18 am
On a quiet summer evening, the Aurora, a 60ft cutter-rigged sloop, approaches the craggy shore of eastern Greenland, along what is known as the Forbidden Coast. Its captain, Sigurdur Jonsson, a sturdy man in his 50s, stands carefully watching his charts. The waters he is entering have been described in navigation books as among the most difficult in Greenland; the mountains rise almost vertically from the sea to form a narrow bulwark, with rifts through which active glaciers discharge quantities of ice, while numerous off-lying islets and rocks make navigation hazardous. The sloop is single-masted, painted a cheery, cherry red. Icebergs float in ominous silence.
Where Jonsson, who goes by Captain Siggi, sails, he is one of few to have ever gone. Because the splintered fjords create thousands of miles of uninhabited coastline, there has been little effort to map this region. Its practically uncharted, he says. You are almost in the same position as you were 1,000 years ago.
A naval architect turned explorer, Siggi navigates by scanning aerial photos and uploading them into a plotter, the ships electronic navigation system. Sometimes he uses satellite images, sometimes shots taken by Danish geologists from an open-cockpit plane in the 1930s, on one of the only comprehensive surveys of the coast. Siggi sails by comparing what he sees on the shore to these rough outlines. Of course, then you dont have any soundings, he says, referring to charts of ocean depths that sailors normally rely on to navigate and avoid running aground. Ive had some close calls. Over the years, he has got better at reading the landscape to look for clues. He looks for river mouths, for example, where silt deposits might create shallow places to anchor, so that icebergs will go to ground before they crush the boat. In the age of GPS and Google Maps, its rare to meet someone who still entrusts his life to such analogue navigation.
Even when Siggi is retracing his own steps, the landscape of the Forbidden Coast is constantly changing. Where the glaciers have disappeared, he explains, pointing at washes of green on a creased, hand-drawn chart, a peninsula turns out to be an island. It was actually sea where you thought there was land. To account for this, he often trades notes with local hunters, who are similarly adept at reading the coast. Their language is very descriptive, Siggi explains. So all the names of places mean something. Although locations may have official Danish names, they are often ignored. An island technically called Kraemer, for instance, in East Greenlandic means the place that looks like the harness for a dogs snout.
Until a century ago, Greenlandic hunters would cut maps out of driftwood. The wooden part would be the fjord, so it would be a mirror image, Siggi says. Holes would be islands. Compared to a paper map, it was actually quite accurate. These driftwood sculptures were first recorded by a Danish expedition in the 1880s, along with bas-relief versions of fjords, carefully grooved and bevelled to represent headland depths. A Danish ethnologist, Gustav Holm, noted that notched into the wood, the map likewise indicates where a kayak can be carried when the path between fjords is blocked by ice. Unlike drawings, the contoured wood could be felt by hand useful in a region where the sun disappears for months at a time.
As a source of information, a map is always a way of groping through the darkness of the unknown. But locating yourself in space has never been cartographys sole function: like these driftwood pieces, maps inevitably chart how cultures perceive not only their landscapes but their lives.
Everything we do is some kind of spatial interaction with objects or ourselves, says John Hessler, a specialist in geographic information systems at the Library of Congress in Washington DC. A map is a way to reduce this huge complexity of our everyday world. For the last few decades, Hessler has been conducting research in the librarys map collection the largest in the world in stacks the lengths of football fields. Geographic information systems have revolutionised everything, he says.
Explorers have long filled in our understanding of the world, using and then discarding the sextant, the compass, MapQuest. The project of mapping the Earth properly is to some extent complete, Hessler says. But while there are no longer dragons fleshing out far-flung places, a surprising number of spaces are still uncharted and the locations we have discovered to explore have only expanded. Where we were just trying to accurately map terrestrial space, Hessler says, we have moved into a metaphor for how we live. Were mapping things that dont have a physical existence, like internet data and the neural connections in our heads.
From mapping the dark between stars to the patterns of disease outbreaks, who is making maps today, and what those maps are used for, says a lot about the modern world. Now anything can be mapped, says Hessler. Its the wild west. We are in the great age of cartography, and were still just finding out what its powers are.
The Amundsen-Scott South Pole Station sits on the Earths axis, at an altitude just above 9,000ft, in the worlds largest, coldest desert, where a small settlement of metal shipping containers takes shape in rows on a windblown sheet of continental ice. Heavy equipment beeps in the polar air. In these harsh conditions, Naoko Kurahashi Neilson has been trying to map black holes.
Its a thorny problem: how do you map something you cannot see? Normally, when you look up at the sky and see a star, the star emitted a light particle called a photon that travelled millions of years and ended up in your eyeball, Kurahashi Neilson explains. Thats how your eye knows theres a star there. But photons, like almost everything else, cannot escape a black holes gravity. Among the only things that can are tiny, high-energy particles called neutrinos, which do not often interact with other matter trillions of them pass through our bodies every second. So detecting neutrinos requires using a massive object. Kurahashi Neilson, for example, began looking for them by using the ocean itself. Very high-energy neutrinos make a splash when they enter water, she says. To detect those splashes, she installed highly sensitive microphones in the waters off the Bahamas, but soon realised that she would need much better equipment.
The answer was at the South Pole Station, amid the summer chaos when scientists around the world flock to take advantage of the short season. Kurahashi Neilson joined the team running the IceCube South Pole Neutrino Observatory, where scientists have created a particle detector so large it covers a cubic kilometre, with sensors buried beneath a mile and a half of ice. As part of her job researching neutrinos, she needed to upgrade the computers. When neutrinos are detected, the information is reported back to a massive collection centre that scientists around the world can access. However, there is no easy way for scientists in, say, Wisconsin, to communicate with the computers at the South Pole. The internet for the South Pole Station comes from satellites, which, in polar regions, often orbit below the horizon. Most of the day, you cant connect from the South Pole to the outside world, says Kurahashi Neilson. So even if its a simple algorithm update, you have to go do it yourself.
As an assistant professor at Drexel University in Philadelphia, Kurahashi Neilson is using these tiny particles to study the biggest ideas. She hopes that mapping where neutrinos come from will lead to the discovery of new black holes, and possibly explain what physical processes take place inside them. Because the majority of neutrinos were created around 14bn years ago, shortly after the birth of the universe, this might help answer a fairly fundamental question: what are the conditions that create energy?
The only way to study something you cant go to or touch is to look at it in many different ways, Kurahashi Neilson says. The funny thing is, if you map the universe in optical light what humans see or gamma rays, or radio rays, our universe doesnt look the same. Thats the beauty of this. You create a map of the same thing in different light, and when you compare them, you understand the universe better.
Whether on the Forbidden Coast or tracking neutrinos at the South Pole, this curiosity to compare, to see something no one has seen before is a fairly basic human compulsion. Thats why Robert Becker a radio astronomer who has recently retired from the University of California, Davis got into physics. When he started studying astronomy, the only map of the entire sky was a simple contour map, like the ones used for hiking. In the 1990s, Becker decided to conduct a Very Large Array radio survey using radio waves to map the sky in much greater detail finding scores of new phenomena.
In most other areas of science, a question leads to an experiment that tests a hypothesis. In astronomy, you cannot conduct experiments. We cant build new stars, Becker explains. So we do survey maps. The goal is to create a catalogue of the sky, which is essentially a record of all the ongoing experiments in space. In an infinite universe, all things that can happen will happen, Becker says, paraphrasing Douglas Adams.
Hes not being cute; this is one of the fundamental principles of quantum physics. We can only observe as far as light has had the chance to travel in the 13.7bn years since the big bang. But space-time extends far beyond that. Because there are only a finite number of ways particles can be arranged, at some point patterns start repeating, even if we cannot detect them. The principle suggests that, in all likelihood, there are many other universes besides our own, coexisting in a kind of cosmic patchwork quilt. If we could look far enough, we would encounter other versions of ourselves actually, infinite versions. So all the possible experiments are already out there, its just a question of finding them and watching, Becker says. Hypothetically, a perfect map would facilitate all the questions astronomers have. Of course, we do not yet have the equipment to observe even a fraction of the universe we are in, never mind others.
In 1995, Becker surveyed 25% of the sky with a radio telescope array, making the galaxy accessible to astronomers through an image that was more accurate than those that previous arrays could provide. Though a quarter of the sky doesnt sound like much, it was such a monumental project that, along with the results, he published an image of his head superimposed on to Michelangelos Adam touching the hand of God. According to Becker, astronomers one day hope to have surveys like this from every part of the electromagnetic spectrum. Once you make an image, youll find a whole bunch of new phenomena. Every new survey opens new dimensions, he says and he means this literally.
In physics, Becker explains, most of what we take for granted today wasnt dreamed of 30 years ago. Its like science fiction dark matter, gravitational waves, quantum entanglement. Since he began mapping the sky, for example, we have learned to predict where black holes are through their gravitational pull if theyre orbiting a star, the star wobbles. Any time you talk about black holes, youre on the verge of science fiction, he says. Can you fall into a black hole and be transported across the universe? Some physicists dont think thats totally far-fetched. In much the same way that early explorers stretched the human imagination, astronomy continues to push the limits of our understanding of creation itself, requiring a kind of faith. As Becker notes, more data usually just gives rise to even more questions. In the outer reaches of even our own universe, Becker says, dragons are still there.
If you could somehow drain the seas, scientists predict you would see not sea monsters but a few volcanoes sprouting from an immense, flat floor, which is hundreds of thousands of hills covered by millennia of falling sediment. Because of these cloaking deposits, developing a better map of the ocean could shed light on the distant past. Its one of the most complete records of history on Earth, says Alan Mix, an oceanographer at Oregon State University. All of history accumulates in layers on the ocean floor. The problem is that this wealth of information lies submerged just out of reach. Because satellites cannot read through water, mapping the sea has been much more difficult than mapping land.
The joke, Mix says, is that we know more about the back side of the moon than the bottom of the ocean. In the meantime, we work with best guesses. On Google Earth, for example, the sea floor appears to be mapped, displaying mountain ranges and submerged islands, but these shapes are actually based on inferred data. Its an interpreted map, Mix explains. Because a mountain on the bottom of the ocean has a lot of mass, its gravity pulls on the water around it, causing a dip in the surface that a satellite can observe. But its like looking through a bad pair of glasses, Mix says. To really know whats going on below the surface, scientists must still send out an expedition.
Deep-sea submersibles, now the tool regularly used to map the ocean floor, were not invented until the 1930s. Their utility expanded with the ability to be operated remotely as an unmanned, robotic craft. In the 1980s, the US navy recruited the scientist Robert Ballard to push the limits of remote-controlled submersibles to find two nuclear submarines that had gone missing during the height of the cold war. They cloaked the top-secret mission as an attempt to find the Titanic which Ballard finally did, during the last 12 days of the expedition, using what he had learned while looking for the submarines. Since then, Ballards idea of deploying remote-controlled robots closer to the bottom of the sea has become standard practice. But the ocean is huge and submersibles can only travel so far. Even today, only about 17% of the ocean has been mapped with sonar, meaning that a ship or submersible has physically driven back and forth over the ocean floor in a grid, like mowing a lawn.
Still, as our knowledge of the ocean floor slowly expands, what scientists learn about ancient history could prove crucial for the future. Mix, for example, has spent the better part of a decade studying the bottom of the sea near the Petermann glacier, an enormous ice sheet on the north-west coast of Greenland, across the island from where Captain Siggi sails. Ice flows across bedrock as it melts and refreezes throughout the year, draining rivers off the Petermann glacier into the sea. The rate of Petermanns melt over the last five years has changed dramatically. (In 2012, an iceberg twice the size of Manhattan tore off the glacier.) Mix explains that the ice shelf acts like the flying buttress of a cathedral. The ice in the ocean helps hold ice back on land. So when it shrinks, its easier for the ice to go out into the ocean, catalysing the already increasing rate of melt.
To understand this process, first you have to make a map, Mix says, although making a map is more complicated when youre dodging bergs. To make his map, Mix sent an icebreaking ship as close as he dared to the glacier, using sonar signals to chart the glaciers historical path by recording the marks scraped like sandpaper on steroids along the bottom. Radiocarbon dating on samples suggests how fast the glacier once moved. These streams of information have been combined by Larry Mayer, director of the School of Marine Science and Ocean Engineering at the University of New Hampshire, who developed a 3D visualisation tool for the expedition. Like a first-person-viewer video game, it takes all the data and turns it into an image like flying over the landscape on the seafloor, Mix says.
The new maps Mixs team have created suggest that actual change events [such as catastrophic ice melt] may happen on very human time scales. Civilisation is built on the assumption that tomorrow will be kind of like today. That has been true since the advent of agriculture. But if we do trigger the melting of ice sheets, it would change the system. Once that tipping point has been reached, the seas will rise so dramatically that for the next thousand years, humans would have to continuously move away from the ocean.
This summer, Mayer took his 3D visualisation tool on an icebreaker up to the Arctic as part of a project to map the ocean floor for the US government. Under the Law of the Sea treaty, Mayer explains, youre allowed to establish sovereign rights 200 nautical miles into the sea. But if the sea floor has certain morphological characteristics, the countrys territory can be extended beyond that 200 nautical-mile limit, into an area called the extended continental shelf. As the rush to claim the Arctic begins Russia has symbolically staked its claim to recently discovered oil reserves by planting a titanium flag in the bottom of the Arctic Ocean maps such as this will be a crucial part of the manoeuvring.
Even when not displaying contested territory, making a map is inherently political. Mapping a round thing in two dimensions is difficult: imagine flattening the unbroken peel of an orange and trying to connect the edges. In order to make a map, you have to give something up, says John Hessler. The decision of which variable to hold true distance or area or shape or scale is called a projection, and every one of them distorts the surface of the Earth in some capacity. The world maps you probably remember from school are Mercator projections, where Greenland appears larger than Africa a continent 14 times the islands size in order to preserve the accuracy of angles. In the 1960s, Arno Peter created a map that looks strangely elongated in comparison, preserving a more accurate sense of scale. Now called the Peters projection, he thought [it] had a better sense of equality for third world countries, Hessler explains. Since then, the number of potential projections has only expanded. Which distortion of the world works best depends on what you think is important.
On January 12, 2010, the epicentre of Haitis 7.0 magnitude earthquake registered just 15 miles from the countrys capital. By the time the aftershocks ceased, Port-au-Prince was left in ruins. Hundreds of thousands died, and many of the survivors had nowhere to go; 1.5 million people lost their homes overnight. Over the following days and weeks, healthcare workers and UN troops from around the world flocked to the country to aid those affected by the earthquake, bringing a strain of the cholera virus that ultimately triggered one of the worst epidemics in recent history.
Until then, Haiti was an epidemiologically naive population, an island with no previous encounter with this particular strain of cholera, and therefore possessing no innate resistance. There were many places that medical personnel were unable to reach. Where aid workers were able to estimate rates, 5% of the population contracted the disease, and without treatment, 40% of those patients died. Health centres struggled to keep up with the caseload, triaging people in tents. Those in acute stages of the illness lay in cots with holes cut in them and a bucket underneath.
Every patient that walked in, we asked them where they were from, recalls Ivan Gayton, the head of mission for Doctors Without Borders (MSF) in Haiti during the cholera outbreak. It may seem like common sense, but it wasnt until 1854 that doctors thought to map disease outbreaks. Like Haiti in 2010, London was suffering a severe cholera epidemic when a physician named John Snow plotted the addresses of cases on to a simple street map. He went door to door knocking, asked everyone where they were getting their water from, Gayton explains. When Snow saw the clusters, it became clear certain water pumps were spreading the disease. It was the foundational moment of epidemiology. It was a stunningly important moment in medicine, Gayton says. He was possibly one of the greatest physicians in all of history, and his claim to fame wasnt a new treatment or a drug it was making a map.
More than a century and a half later in Haiti, MSF doctors could not even do that. Though everyone being treated in Haitian clinics was asked where they were from, the information proved confounding, since none of the informal neighbourhoods and slums in Haiti were adequately mapped. Doctors lacked the ability to connect the place names with geographical coordinates. It was effectively being recorded in random syllables, Gayton says. Though staff tried to record cases in a spreadsheet, without locations, doctors could not tell if cases were adjacent to one another or on opposite sides of the city, making it difficult to trace or stop the sources of infection. We couldnt do our job, says Pete Masters, the Missing Maps project coordinator at MSF. We didnt have the evidence to take the best action.
At the peak of the outbreak, Gayton was wandering through the hallway of a clinic and spotted a colleague, Maya Allan, crouched on a windowsill with a laptop. She was trying to place pins [of cholera cases] on Google Earth by hand, Gayton says. Frustrated, he thought there had to be a better way. So he called Google, which was like calling the Batcave.
A few days later, Google software engineer Pablo Mayrgundter flew to Port-au-Prince, bringing with him Google Earth programs and map data downloaded on to hard drives so he could work in the field without the internet. He trained Haitians how to use GPS units, then sent them into neighbourhoods to get latitude and longitude coordinates for Haitian place names. Googles engineers were aided by a group called the Humanitarian OpenStreetMap (Hot) team Earthquake nerds, looking at the TV, looking at the street map of Port-au-Prince, and realising theres nothing there, Masters says. After the earthquake, the group coordinated with members of the Haitian diaspora to map Haitis slums and identify local landmarks for the first time. Within 72 hours of the earthquake, search-and-rescue teams were using their maps. Together, Google and Hot worked to geolocate all of the information they had gathered and to write a script to import the case records. Suddenly, the MSF patient list could be transformed into an animated map of cases. Boom. All of a sudden, we could do what Snow did years ago, Gayton says. Hallelujah.
A couple of days after the Google team left, Gayton was able to pinpoint a water outage in a neighbourhood where cholera cases had suddenly jumped. After notifying the water utility, workers were dispatched to the site to make repairs. Fewer people were dying because a map allowed us to correlate a spike in cases to a specific event, Gayton says. Thats the holy grail of mapping actual lives saved.
Anyone who says the world is mapped, ask them to show you where Congo's population are living, where the villages are
Following the projects success in Haiti, Gayton was invited to MSF headquarters in London to try to set up a system for mapping other disasters. It didnt work, mainly because reactive mapping, it turns out, cant possibly keep up with the scale and speed of humanitarian disasters. Because of the horrible earthquake, HOT volunteer mapping got done [before the cholera crisis], Gayton says. A map that comes post-disaster doesnt save lives.
During the Ebola crisis in west Africa, cases moved too swiftly for maps to be created of all of the areas that the virus reached. What is needed is proactive mapping on a continental scale, of all vulnerable areas. Thats why Gayton helped coordinate Missing Maps, a collaboration between existing aid groups and volunteers using open-source data to map places where crises are likely to occur. The organisation holds mapathons, where volunteers connect to people in the field. Take names of streets, Gayton says. Youre on the Avenue of Church there are 200 of those in Lubumbashi. You have to trace it, have to have imagery, have to go into the field and get names, and then integrate all of that into a nice visual map. He describes the process as being similar to fitting a Russian doll together.
I like maps, Gayton says. But really what I care about is equitable distribution of healthcare. As long as 1 billion people dont have it, sooner or later itll come and bite people in rich countries. He scoffs at the idea that there are no blank spaces left on Earth. Anyone who says the world is mapped, ask them to show you where the population of Congo is living. Ask them where the villages are. If they can do it, please let me know.
To Gayton, its not an idle distinction. When you have a place like South Sudan, where millions of people live and die without ever figuring in a database anywhere, their names will never be written down. Theres not a lot of dignity in that to not be on the map is quite a powerful statement of uncaring.
Thats what Missing Maps is about. We still dont know who they are, but at least we know where their house is. At least the map actually contains them, rather than a blank wash of green, Gayton says. I tell people at mapathons sometimes, That house youre tracing right now, that hut thats the first time in the history of humanity someone cared enough about them to take note. Things dont exist just because we name them, but giving them a name engenders new meaning. At its most basic, to exist on a map is to have value.
It isnt coincidental that humans have been drawn to maps for almost as long as we have had written records.
Our best way of sharing knowledge whether its a physical representation of land or an energy space variable its a map, says Naoko Kurahashi Neilson. Every scientific analysis produces maps or visual plots to look at. Thats the way we intuitively understand the best.
By building narratives that orient us not only where we are physically standing, but in the past and future maps are an instinctual way of ordering chaos, of turning stars to constellations and glacial scratches to predictions. A map in the hands of a pilot is a testimony to a mans faith in other men; it is a symbol of confidence and trust. It is not like a printed page that bears mere words, wrote Beryl Markham in the 1940s, shortly after becoming the first woman to fly solo across the Atlantic from the east to the west. A map says to you, Read me carefully, follow me closely, doubt me not.
The daughter of a colonial horse trainer, Markham grew up hunting barefoot with the Nandi, and learned to fly a plane when there were only a few in all of Africa. In early September 1936, Markham took off in a turquoise-and-silver Gull, with what she hoped was enough fuel to make it across the Atlantic. She flew for more than 21 hours across the open ocean, mostly in the dark. Recalling those interminable hours, she later wrote: Were all the maps in this world destroyed and vanished each man would be blind again, each city made a stranger to the next, each landmark become a meaningless signpost pointing to nothing.
Since Markhams record-breaking flight, weve sent a spaceship to the edge of the solar system. As technology shrinks the world, the concept of nothingness can feel obsolete; our very understanding of distance has fundamentally changed. But that doesnt mean small spaces can no longer be large enough to get lost in.
Several fjords over from Captain Siggis winter anchorage in Iceland, a pot-holed gravel road winds steeply up a mountain. Beyond the summit, a valley plunges into the sea. An Arctic fox pads silently downhill. Sheep graze over the moss and late blueberries. On the beach, waves eat away at the walls of an ancient sod-and-stone house. After generations of farmers ploughing a living into this stony plain, only a single woman, Betty, remains.
The road to her valley is closed for half the year; the rare visitor arrives only by snowmobile. Bettys TV cable went out two years ago, and the telephone doesnt work in the rain. She cares for the family church, where baptisms and deaths have been recorded for centuries, an imposition of will into a world that will exist without us. On winter nights when the northern lights come out, she piles on hand-knitted sweaters and stomps down to the beach to watch the sky perform.
The notion that place is capable of imparting its qualities to people may sound a little fanciful, writes geographer Yi-Fu Tuan, so let me say, first, something that is merely common sense, namely good soil yields good crops, bad soil poor crops. In humans, the phenomenon is subtle, but place just as surely moulds what used to be called character.
When Betty leaves the valley, these hills will be mapped, though no one will know their wind and their weather. Until then, when the sheep give birth in the spring, shell watch over the miracle. If one day the distant universe is as mundane as the road that leads to our doors, even in the most familiar, there will always be wonder. Its where all exploration begins.
Main photograph: Sean McDermott
This article is adapted from an essay published in the winter 2017 issue of the Virginia Quarterly Review
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A Heroic AI Will Let You Spy on Your Lawmakers’ Every Word – WIRED
Posted: at 8:16 am
Slide: 1 / of 1. Caption: Getty Images
No one knows better than Sam Blakeslee that your elected officials operate in the shadows. No one is sure what they do or what they say.
He knows because he used to be one of them. As a Republican state senator and assemblyman in California, Blakeslee worked on negotiating the state budget and drafting bills around the energy sector and lobbying reform. And he did itas did his fellow legislatorsfar from the prying eyes of the very people he was representing.
Thats one reason why, when Blakeslee left government, he began working with students on a way to automate government accountability. Digital Democracy is like YouTube for local government hearings, bolstered with a splash of artificial intelligence. Bots create transcripts of lawmakers every official utterance at the state house and use face recognition software to keep track of whos speaking. Voters can search the transcripts by speaker and subject while at the same time getting a glimpse of legislators financial ties. The non-profit effort launched in California back in 2015, and today, its expanding to New York.
Were keenly aware that most legislators operate in the dark and with impunity, says Blakeslee, now founding director of the Institute for Advanced Technology & Public Policy at Cal Poly. Their constituencies dont know what they say or what they do behind closed doors.
Most legislators operate in the dark and with impunity.
The Digital Democracy platform, funded by the Laura and John Arnold Foundation and the Rita Allen Foundation, is a collaboration between man and machine. Students at Cal Poly review each transcript for accuracy before it goes live. They also compile a profile page for each legislator, complete with an itemized list of gifts that person has received.
Government in the past has been, you vote, I decide,' says Gavin Newsom, the lieutenant governor of California, former mayor of San Francisco, and co-founder of Digital Democracy. That model is in peril, and Donald Trump exploited it brilliantly.
Not surprisingly, Newsom says California lawmakers were none too thrilled when the platform launched. We wax on about the importance of transparency in public forums but we dont always practice what we preach, he says.
The expansion of Digital Democracy comes at an opportune time. Not only is the public hungry for accountability both inside and outside of Washington, DC, but as Trump works to roll back federal legislation on everything from healthcare to environmental protections, the future of those policies will be in states hands.
The Trump administration is making a number of decisions that would push issues back to state houses across the country, says Blakeslee. This is a perfect moment if you want to make a difference to engage in the politics in your state.
That may be true, but in other crucial ways, the Digital Democracy platform couldnt be more of a mismatch for this particular time. Most people today will share a link without ever reading the story it references. Americans consume their news in bite-sized tweets and push alerts. In California, journalists with the patience and time to sift through transcripts have been Digital Democracys most frequent users. Even Newsom acknowledges its not exactly user-friendly.
Its a data dump, he says. But both Newsom, a Democrat, and Blakeslee, a Republican, worry that curation could threaten the platforms objectivity. Its harder to cry fake news about a video thats presented in full without commentary.
The founders are also joining up with other organizations that have become instrumental to holding politicians accountable. Cal Poly students will soon run their hearing transcripts through an AI tool called ClaimBuster, which automatically detects assertions of fact, and then feed those statements to PolitiFact for fact-checking.
The non-profit is also rolling out an enhanced version that will enable other organizations to embed the videos directly on their websites. Meanwhile, Digital Democracy has plans to expand to Florida and Texas, at which point the platform will reach one-third of the countrys citizens. In time, Newsom hopes that Digital Democracy will be a platform on which developers of politically minded tech build other apps.
That will take time. For now, putting these videos in citizens hands is simply a much needed step toward transparency at a time when so much policy-making is anything but. Its not a perfect system. Then again, neither is democracy.
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AI is here to save your career, not destroy it – VentureBeat
Posted: at 8:15 am
Imagine: Humans waging an epic battle against technology, with human intelligence inevitably subjugated by artificial overlords. Plenty of folks would line up with front-row tickets and popcorn in hand. But its also the very real manifestation of a universal fear jobs relegated to machines, livelihoods handed over to bots.
But when we take a closer look at bots and other forms of artificial intelligence, our worst fears are a far cry from the truth. Weve built bots to help us succeed. And instead of viewing them as our grand reckoning, we should view AI and bots as tools to exponentially expand our human capabilities in and out of the workplace. Yes, bots can make us more human in our daily lives.
Those who use bots as superhuman digital assistants will find the most success. Itll be humans to the bot-th power, rather than humans versus bots.
Much of our understanding of AI and the future is rooted in misconception. Were trepidatious toward the future. Its a valid and human response that shouldnt go ignored. But the truth is, the future is already here.
Anyone whos tagged a photo of a friend on Facebook has used AI. But do people think that way? While 86 percent of people say theyre interested in trying AI tools, 63 percent dont realize theyre already using AI.
Machines are much better at quickly surfacing the most relevant information the internet holds. Its on us humans to take that knowledge and make the most informed decisions. But finding information not all our bot friends can help us with they can do much more than just answer direct questions.
Soon, bots will work in the background on our behalf and initiate a conversation when something interesting has happened. Well be prompted with a notable result, and then well make the choice to move forward.
Its simple, but so powerful. As technology should be.
Computers now have the ability to do what we once thought only human intelligence could handle. In the near future, AI is going to feel less artificial and more intelligent.
Humans learn from example and experience. So do machines. Machine learning allows you tell a system what you want, not how to do it.
Once something a few PhDs wrote about, machine learning is now something millions of people benefit from. Everything from predictive learning and lead scoring to content recommendations and email optimization will get much easier for marketers and salespeople alike.
Already, 40 percent of people dont care if theyre served by an AI tool or a human so long as the question gets answered. Only 26 percent say the same for more complicated customer requests. But how those humans will best serve their customers will take (you guessed it) bots.
If you want your employees and business to benefit from all this machine learning, youll need to invest in getting the data in one centralized place. After all, the data is what gives machine learning the learning part. Theres no learning without the data.
Not only is AI the future of marketing and sales, its the future of the inbound movement. AI and bots allow you to provide highly personalized, helpful, and human experiences for your customers. It may not be a summer blockbuster fit for theaters, but AI and bots sure feel like theyre fit for businesses.
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Teach undergrads ethics to ensure future AI is safe compsci boffins – The Register
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Universities should step up efforts to educate students about AI ethics, according to a panel of experts speaking at the AAAI conference in San Francisco on Monday.
Machine learning is constantly advancing as new algorithms are developed, and as hardware to accelerate computations improves. As the capabilities of AI systems increases, so do fears that this progressing technology will be abused to trample on people's privacy and other rights.
Sure, there are magazines and blogs full of academics wringing their hands about seemingly impossible conscious computers wrestling with moral dilemmas. But before we get to that point in AI development, though, there are still modern-day practical problems to consider. Say, when a program decides which medication you should take, shouldn't you be able to pick apart how it came to that conclusion? What if the prescription is based on an paid-for bias in the model in favor of a particular pharmaceutical giant?
When a machine harms a person, who is at fault? How do you, as an engineer, design your system so that a machine doesn't hurt or cause damage?
Several groups such as the Partnership on AI and The Ethics and Governance of Artificial Intelligence Fund have spawned to try to keep tech in check. More direct than that, though, undergrads should be made aware of the moral and ethical issues surrounding technology; good practices should be drilled into the next generation of engineers, the conference was told.
Robots are particularly worrying. Its already difficult to explain decisions made by algorithms, but when they are applied to physical machines capable of directly affecting the environment, its no wonder that alarm bells are ringing.
More robots and AI are functioning as members of society, Ben Kuipers, a professor of computer science and engineering at the University of Michigan, said.
We worry about robot behavior," he told the audience. "With no sense of whats appropriate, and whats not, they may do great harm. Prof Kuipers uses the example of Robot from the sci-fi comedy flick Robot & Frank, who willingly lies and breaks the law in pursuit of its goals.
Even if the robots missions are human-given top-level goals, it will create subgoals and execute them in unexpected ways to fulfill its main task. To design robots to be trustworthy, a solid grounding in engineering is not enough philosophy is needed.
Prof Kuipers pointed to the theories of utilitarianism; deontology; and virtue ethics to find useful clues for ethical theories.
Illah Nourbakhsh, a professor of robotics at Carnegie Mellon University, agreed. On his online robotics and ethics teaching guide, he wrote: First, students need access to formal ethical frameworks that they can use to study and evaluate ethical consequence in robotics well enough to make their own well-informed decisions. Second, students need to understand the downstream impact of media-making well enough to help the field as a whole communicate with the public authentically and effectively about robotics and its ramifications on society.
But rigid ethical frameworks arent always the best way to model moral problems in AI, Judy Goldsmith, a professor of computer science at the University of Kentucky, told the audience.
Case studies are rarely memorable, emotionally gripping or subtle. There is no character development and often theres a right answer, she said. Prof Goldsmith prefers science fiction as it provides a rich vein for ethical dilemmas and an emotional connection to stories makes discussions memorable when real-world dilemmas arise.
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AI For Matching Images With Spoken Word Gets A Boost From MIT – Fast Company
Posted: at 8:15 am
Children learn to speak, as well as recognize objects, people, and places, long before they learn to read or write. They can learn from hearing, seeing, and interacting without being given any instructions. So why shouldnt artificial intelligence systems be able to work the same way?
That's the key insight driving a research project under way at MIT that takes a novel approach to speech and image recognition: Teaching a computer to successfully associate specific elements of images with corresponding sound files in order to identify imagery (say, a lighthouse in a photographic landscape) when someone in an audio clip says the word "lighthouse."
Though in the very early stages of what could be a years-long process of research and development, the implications of the MIT project, led by PhD student David Harwath and senior research scientist Jim Glass, are substantial. Along with being able to automatically surface images based on corresponding audio clips and vice versa, the research opens a path to creating language-to-language translation without needing to go through the laborious steps of training AI systems on the correlation between two languages words.
That could be particularly important for deciphering languages that are dying because there aren't enough native speakers to warrant the expensive investment in manual annotation of vocabulary by bilingual speakers, which has traditionally been the cornerstone of AI-based translation. Of 7,000 spoken languages, Harwath says, speech recognition systems have been applied to less than 100.
It could even eventually be possible, Harwath suggested, for the system to translate languages with little to no written record, a breakthrough that would be a huge boon to anthropologists.
"Because our model is just working on the level of audio and images," Harwath told Fast Company, "we believe it to be language-agnostic. It shouldnt care what language its working on."
t-SNE analysis of the 150 lowest-variance audio pattern cluster centroids for k = 500. Displayed is the majority-vote transcription of the each audio cluster. All clusters shown contained a minimum of 583 members and an average of 2482, with an average purity of .668.
The MIT project isnt the first to consider the idea that computers could automatically associate audio and imagery. But the research being done at MIT may well be the first to pursue it at scale, thanks to the "renaissance" in deep neural networks, which involve multiple layers of neural units that mimic the way the human brain solves problems. The networks require churning through massive amounts of data, and so theyve only taken off as a meaningful AI technique in recent years as computers processing power has increased.
Thats led just about every major technology company to go on hiring sprees in a bid to automate services like search, surfacing relevant photos and news, restaurant recommendations, and so on. Many consider AI to be perhaps the next major computing paradigm.
"It is the most important computing development in the last 20 years," Jen-Hsun Huang, the CEO of Nvidia, one of the worlds largest makers of the kinds of graphics processors powering many AI initiatives, told Fast Company last year, "and [big tech companies] are going to have to race to make sure that AI is a core competency."
Now that computers are powerful enough to begin utilizing deep neural networks in speech recognition, the key is to develop better algorithms, and in the case of the MIT project, Harwath and Glass believe that by employing more organic speech recognition algorithms, they can move faster down the path to truly artificial intelligent systems along the line of what characters like C-3PO have portrayed in Star Wars movies.
To be sure, were many years away from such systems, but the MIT project is aiming to excise one of the most time-consuming and expensive pieces of the translation puzzle: requiring people to train models by manually labeling countless collections of images or vocabularies. That laborious process involves people going through large collections of imagery and annotating them, one by one, with descriptive keywords.
Harwath acknowledges that his team spent quite a lot of time starting in late 2014 doing that kind of manual, or supervised, learning on sound files and imagery, and that afforded them a "big collection of audio."
Now, theyre on to the second version of the project, which is to build algorithms that can both learn language as well as the real-world concepts the language is grounded in, and to do so utilizing very unstructured data.
Heres how it works: The MIT team sets out to train neural networks on what amounts to a game of "which one of these things is not like the other," Harwath explains.
They want to teach the system to understand the difference between matching pairsan image of a dog with a fluffy hat and an audio clip with the caption "dog with a fluffy hat"and mismatched pairs like the same audio clip and a photo of a cat.
Matches get a high score and mismatches get a low score, and when the goal is for the system to learn individual objects within an image and individual words in an audio stream, they apply the neural network to small regions of an image, or small intervals of the audio.
Right now the system is trained on only about 500 words. Yet its often able to recognize those words in new audio clips it has never encountered. The system is nowhere near perfect, for some word categories, Harwath says, the accuracy is in the 15%-20% range. But in others, its as high as 90%.
"The really exciting thing," he says, "is its able to make the association between the acoustic patterns and the visual patterns. So when I say lighthouse, Im referring to a particular [area] in an image that has a lighthouse, [and it can] associate it with the start and stop time in the audio where you says, lighthouse."
A different task that they frequently run the system through is essentially an image retrieval task, something like a Google image search. They give it a spoken query, say, "Show me an image of a girl wearing a blue dress in front of a lighthouse," and then wait for the neural network to search for an image thats relevant to the query.
Heres where its important not to get too excited about the technology being ready for prime time. Harwath says the team considers the results of the query accurate if the appropriate image comes up in the top 10 results from a library of only about 1,000 images. The system is currently able to do that just under 50% of the time.
The number is improving, though. When Harwath and Glass wrote a paper on the project for an upcoming conference in France, it was 43%. Still, he believes that although there are regular improvements and increased accuracy every time they train a new model, theyre held back by the available computational power. Even with a set of eight powerful GPUs, it can still take two weeks to train a single model.
An example of our grounding method. The left image displays a grid defining the allowed start and end coordinates for the bounding box proposals. The bottom spectrogram displays several audio region proposals drawn as the families of stacked red line segments. The image on the right and spectrogram on the top display the final output of the grounding algorithm. The top spectrogram also displays the time-aligned text transcript of the caption, so as to demonstrate which words were captured by the groundings. In this example, the top three groundings have been kept, with the colors indicating the audio segment that is grounded to each bounding box.
Perhaps the most exciting potential of the research is in breakthroughs for language-to-language translation.
"The way to think about it is this," Harwath says. "If you have an image of a lighthouse, and if we speak different languages but describe the same image, and if the system can figure out the word Im using and the word youre using, then implicitly, it has a model for translating my word to your word . . . It would bypass the need for manual translations and a need for someone whos bilingual. It would be amazing if we could just completely bypass that."
To be sure, that is entirely theoretical today. But the MIT team is confident that at some point in the future, the system could reach that goal. It could be 10 years, or it could be 20. "I really have no idea," he says. "Were always wrong when we make predictions."
In the meantime, another challenge is coming up with enough quality data to satisfy the system. Deep neural networks are very hungry models.
Traditional machine learning models were limited by diminishing returns on additional data. "If you think of a machine learning algorithm as an engine, data is like the gasoline," he says. "Then, traditionally, the more gas you pour into the engine, the faster it runs, but it only works up to a point, and then levels off.
"With deep neural networks, you have a much higher capacity. The more data you give it, the faster and faster it goes. It just goes beyond what older algorithms were capable of."
But he thinks no ones sure of the outer limits of deep neural networks capacities. The big question, he says, is how far will a deep neural network scale? Will they saturate at some point and stop learning, or will it just keep going?
"We havent reached this point yet," Harwath says, "because people have been consistently showing that the more data you give them, the better they work. We dont know how far we can push it."
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Artificial intelligence: How to build the business case – ZDNet
Posted: at 8:15 am
"The acceptance of AI in the business is going to involve an evolution."
There's plenty of excitement around artificial intelligence: analyst Gartner places it at the top of its top 10 strategic technology trends for 2017. The analyst says the technology has reached a tipping point and AI is beginning to extend its tentacles into every service, thing, or application, and that it will become the primary battleground for technology vendors looking to make money through 2020.
Interim CIO Christian McMahon, who is managing director at transformation specialist three25, acknowledges interest in AI has exploded recently, but he also voices a word of caution.
AI and the Future of Business
Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them.
"All the major corporates, accelerators and venture capitalists are desperate to find a foothold," he says. "However, I don't think the current AI market is at a stage where breakthrough technologies are about to be unveiled. Rather, it's a vibrant market which seems more conceptual than one of tangible substance."
It is a sentiment that chimes with Omid Shiraji, interim CIO at Camden Council. His organisation holds a huge amount of data and aims to use its knowledge to help people with complex needs. AI could provide a breakthrough in data insight, yet Shiraji says CIOs must focus on value creation.
"The business case for these projects is not easy -- you can take a step into the unknown," says Shiraji. "You sometimes have to rely on intuition rather than ROI to place your investments in these types of projects."
Gartner suggests executives who take a risk on AI projects will be rewarded and should consider experiments in one or two high-impact scenarios. So how will pioneering organisations build a business case for AI? Two IT leaders -- one each from the private and public sectors -- give us their take.
Sizing up the opportunity
Matt Peers, CIO of global law firm Linklaters, draws a parallel between the use of big data and the growing importance of AI. Peers says success in big data is all about being able to make the best use of the information you possess -- and Linklaters, a 175-year-old firm, is a business with more knowledge than most.
Peers says his organisation should be able to turn its history into a competitive advantage. Lawyers need knowledge about legal precedent, previous projects, and internal skills specialisms. He believes advances in AI will help his firm to create more sophisticated approaches to search.
"The key to success is getting the right information to people quickly," he says. "Some of the tools that are being developed for AI will help us search big data. Most of the technologies on the market today are good at clustering and reading contracts, and enabling you to search vast volumes of data for legal themes."
He expects the ability to digitise and search contracts for key legal themes to become commonplace very quickly. Linklaters has already created an AI working group to help analyse services in the marketplace and to work out how these technologies might impact the business.
"Firms in some key sectors are already making a move," says Peers. "We've spent a lot of time in the past 18 months sizing up the opportunities by talking to people, seeing demonstrations, and running proof of concept studies."
Peers recognises AI could also help change the way lawyers work, yet he also expects a cultural challenge. Senior partners trust their associates to spend hours considering the details of legal documents. Trusting computers to undertake the same task in seconds presents a different form of dependence.
"It's a big shift because the reputation of that lawyer and firm is on the line," he says. "The acceptance of AI in the business is going to involve an evolution. It's important to remember that there are many matters in the legal world where AI is not going to be useful for quite a long time. It's going to take a while for computers to provide trusted advice and opinion."
Using data to save lives
Toby Clarke, interim head of IT at Moorfields Eye Hospital NHS Foundation Trust, says AI will have a huge impact on the work of publicly-funded organisations. Moorfields has been working closely with DeepMind Research, a project that involves the Trust sharing a set of one million anonymised eye scans.
The project between Moorfields and DeepMind relies on historic scans, meaning that while the results of the research might be used to improve future care, they will not affect patients today. However, the hope is that discoveries through the initiative will lead to earlier detection and help reduce preventable eye disease.
"What they're doing with that information is truly amazing," says Clarke, referring to the DeepMind project. "It's cutting edge and will make a significant difference."
He says the key to long-term change through AI is being able to use information to inform patient care. And that use presents challenges, particularly in terms of data security and confidentiality. "The real value will come from using non-anonymised data," he says.
"If you have a large repository of information, and you can add big data from demographics, you can start to take make predictions about patient healthcare. You could potentially say when people should be coming in for tests in terms of early warnings."
The current project uses anonymous data. "It has to be that way," says Clarke. "In terms of healthcare, there will always be issues around how you commercialise data, and how you deliver value back to the host organisation and its patients."
Clarke, however, is keen to point out that similar projects could sponsor significant change. "It's difficult for humans to understand the impact of AI right now but the potential is huge," he says. "The technology self-learns and I find it exceptionally exciting. AI is different and new, and it's something everyone involved in IT should be investigating."
In contrast to reports that automation simply leads to job cuts, Clarke says AI - particularly in the role of predictive medicine - could lead to a whole new range of data science roles. "It's not about removing jobs but it is potentially about saving lives," he says.
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Artificial Intelligence-Driven Robots: More Brains Than Brawn – Forbes
Posted: at 8:15 am
Forbes | Artificial Intelligence-Driven Robots: More Brains Than Brawn Forbes Automation and robots for manufacturing have come a long way since Unimate was introduced in the 1960's. The machines that manufacturers are using today are smaller, safer and able to perform more than a single task without expensive programming. |
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Why C-Levels Need To Think About eLearning And Artificial Intelligence – Forbes
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Forbes | Why C-Levels Need To Think About eLearning And Artificial Intelligence Forbes ... proprietary Artificial Intelligence to analyze each learner's behavior, cognition, engagement and performance to predict learning and future performance, optimize learning content and to create a deep personalized individual and social learning ... |
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