Monthly Archives: December 2018

Your Cash Is No Good Here. Literally. – So how to pay if you don’t like plastic: which helps the banks but not your spending patterns

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As more retailers—including Drybar and Sweetgreen—ban paper money, it’s making things awkward for customers without plastic. [paywalled]

Source: Your Cash Is No Good Here. Literally. – WSJ

 

Oh dear, not accepting money – when the pain signals in your brain are not set off by clicking a bank pass, but are when you have to pay cash. Don’t be fooled people: cash is central to what money is – for the whole economy, but also for you as a person. See what happens when people with trillions start chucking it about (because what does that amount really mean, anyway!?) or the personal debt people spending on credit build up.

AI learns to Navigate the Web, fill in forms – without a human built training set

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Learning in environments with large state and action spaces, and sparse rewards, can hinder a Reinforcement Learning (RL) agent’s learning through trial-and-error. For instance, following natural language instructions on the Web (such as booking a flight ticket) leads to RL settings where input vocabulary and number of actionable elements on a page can grow very large. Even though recent approaches improve the success rate on relatively simple environments with the help of human demonstrations to guide the exploration, they still fail in environments where the set of possible instructions can reach millions. We approach the aforementioned problems from a different perspective and propose guided RL approaches that can generate unbounded amount of experience for an agent to learn from. Instead of learning from a complicated instruction with a large vocabulary, we decompose it into multiple sub-instructions and schedule a curriculum in which an agent is tasked with a gradually increasing subset of these relatively easier sub-instructions. In addition, when the expert demonstrations are not available, we propose a novel meta-learning framework that generates new instruction following tasks and trains the agent more effectively. We train DQN, deep reinforcement learning agent, with Q-value function approximated with a novel QWeb neural network architecture on these smaller, synthetic instructions. We evaluate the ability of our agent to generalize to new instructions on World of Bits benchmark, on forms with up to 100 elements, supporting 14 million possible instructions. The QWeb agent outperforms the baseline without using any human demonstration achieving 100% success rate on several difficult environments.

Source: [1812.09195] Learning to Navigate the Web

AI Automatically Sorts Cancer Cells to determine most effective treatment

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A team of researchers in Japan have devised an artificial intelligence (AI) system that can identify different types of cancer cells using microscopy images. Their method can also be used to determine whether the cancer cells are sensitive to radiotherapy. The researchers reported their findings in the journal Cancer Research. In cancer patients, there can be tremendous variation in the types of cancer cells in a single tumor. Identifying the specific cell types present in tumors can be very useful when choosing the most effective treatment. However, making accurate assessments of cell types is time consuming and often hampered by human error and the limits of human sight. To overcome these challenges, scientists led by Professor Hideshi Ishii of Osaka University, Japan, have developed an AI system that can identify different types of cancer cells from microscopy images, achieving higher accuracy than human judgement. The system is based on a convolutional neural network, a form of AI modeled on the human visual system. “We first trained our system on 8,000 images of cells obtained from a phase-contrast microscope,” said corresponding author Ishii. “We then tested [the AI system’s] accuracy on another 2,000 images and showed that it had learned the features that distinguish mouse cancer cells from human ones, and radioresistant cancer cells from radiosensitive ones.” The researchers noted that the automation and high accuracy of their system could be very useful for determining exactly which cells are present in a tumor or circulating in the body. Knowing whether or not radioresistant cells are present is vital when deciding whether radiotherapy would be effective. Furthermore, the same procedure can be applied post-treatment to assess patient outcomes. In the future, the team hopes to train the system on more cancer cell types, with the eventual goal of establishing a universal system that can automatically identify and distinguish all variants of cancer cells. The article can be found at: Toratani et al. (2018) A Convolutional Neural Network Uses Microscopic Images to Differentiate between Mouse and Human Cell Lines and Their Radioresistant Clones. Read more from Asian Scientist Magazine at: https://www.asianscientist.com/2018/12/in-the-lab/artificial-intelligence-microscopy-cancer-cell-radiotherapy/

Source: AI Automatically Sorts Cancer Cells | Asian Scientist Magazine | Science, technology and medical news updates from Asia

This Roomba can create its own Doom levels

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Game developer and designer Rich Whitehouse gave the world an unusual present this Christmas Eve. It’s called Doomba, and it uses the popular Roomba vacuuming robots to create levels for Doom, the classic first-person shooter.

Whitehouse is a 20-year veteran of the game industry, with credits on titles such as the original Prey and Star Wars Jedi Knight 2: Jedi Outcast. Along the way, he also built a tool called Neosis, which helps game developers and designers move digital assets between different platforms. The Doomba module works on similar principles; it just takes the digital maps created by the Roomba’s own internal software and converts them into Doom levels.

So what’s your Roomba doing creating maps of the inside of your house? Many of iRobot’s modern robotic vacuums rely on VSLAM, also known as visual simultaneous localization and mapping. Rather than wandering around like slow-moving ping-pong balls, modern Roomba devices methodically sweep back and forth in long passes like they’re mowing your lawn. That makes them much more efficient than previous models.

To do the work, some Roombas use a creepy little electronic eyeball to create detailed maps of your home. Doomba takes that map and makes it into a level of Hell.

As Whitehouse explains, it was fairly short work to turn his creation toward evil.

“I soon realized that there was a clear opportunity to serve the Dark Lord by conceiving a plethora of unholy algorithms in service to one of the finest works ever created in his name,” Whitehouse writes on his personal blog. “Simultaneously, I would be able to unleash a truly terrible pun to plague humankind. Now, the fruit of my labor is born. I bring forth DOOMBA, a half-goat, half-script creature, with native binary backing for the expensive parts, to be offered in place of my firstborn on this fine Christmas Eve.”

Source: This Roomba can create its own Doom levels – Polygon

In Blow to Amazon and Walmart, India Bans a Key Part of Their Business Strategy

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The Indian government sent a strong screw you to Amazon and the Walmart-owned Flipkart on Wednesday, banning e-commerce companies from selling products from companies that they have an equity interest in or “entering into exclusive agreements with sellers,” CNBC reported.

India already bans e-commerce sites from selling products directly, per the New York Times, which has led to them acquiring stakes in affiliate companies that serve much the same purpose at arm’s length. At issue is the power of e-commerce companies to make bulk purchases of goods that they then sell to “select sellers, such as their affiliates or other companies with which they have agreements,” CNBC wrote. The strategy allows giants like Amazon to offer products at low prices that smaller competitors often find hard to match.

In a statement to CNBC, India’s commerce ministry said the new rules would go into effect on Feb. 1, 2019, adding the new rules specify that: “An entity having equity participation by e-commerce marketplace entity or its group companies, or having control on its inventory by e-commerce marketplace entity or its group companies, will not be permitted to sell its products on the platform run by such marketplace entity.”

The move could mean Amazon would be forced “to stop competing with independent sellers and end its offerings of proprietary products like its Echo smart speakers in India, its top emerging market,” the Times wrote. It’s also a blow to Walmart, which bought a 77 percent stake in Flipkart for $16 billion this year, and may be forced to stop selling products produced by companies it owns. As the paper noted, both companies’ competitive strategies rely on highly efficient supply chains and pressuring retailers to comply with their requirements, so this is not a good sign for their Indian ambitions.

The Times wrote that the decision appears to have been motivated by concerns from India’s prime minister, right-wing populist culture warrior Narendra Modi, that his party is losing ground ahead of upcoming elections:

Prime Minister Narendra Modi of India initially courted foreign companies to invest more in the country after his 2014 election victory, but his administration has turned protectionist as his party’s re-election prospects have dimmed in recent months. Mr. Modi has increasingly sought to bolster Indian firms and curb foreign ones through new policies, including one that requires foreign companies like Visa, Mastercard and American Express to store all data about Indians on computers inside the country. The government has also declared its intention to impose tough new rules on the technology industry.

According to CNBC, beneficiaries of the move will likely include owners of small businesses like farms and corner stores, the latter of which “dominate Indian retailing,” who believe that U.S.-based tech giants are trying to undermine their economic position. The site added that the Confederation of All India Traders issued a statement saying that tech giants will no longer to be able to commit “malpractices, predatory pricing policies and deep discounting.”

However, the law was vaguely written and contains some sections that appear to contradict each other, lawyer Salman Waris of New Delhi’s TechLegis told the Times, which means that its ultimate impact remains unclear. The paper also noted that Amazon is well-known for navigating Indian law to remain in compliance without losing its ability to steer markets, though Walmart’s decision to acquire Flipkart has already been questioned by analysts as a potentially unwise financial move.

Source: In Blow to Amazon and Walmart, India Bans a Key Part of Their Business Strategy

It is way beyond time to start breaking up the monopolies and 0.00000001%ers. Way to go, India!

Mapping All of the Trees with Machine Learning

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Much fuss has been made over city trees in recent years. Urban trees reduce crime and help stormwater management (yay!). Cities and towns across the U.S. are losing 36 million trees a year (boo!). But, hold up—climate change is accelerating the growth of urban trees in metropolises worldwide (boo/yay?). Urban trees are under such scrutiny right now that the U.N. even had a World Forum on Urban Forests a few weeks ago to discuss the planning, design and management of urban forests and green infrastructure.

The Descartes Labs tree canopy layer around the Baltimore Beltway. Treeless main roads radiate from the dense pavement of the city to leafy suburbs.

All this fuss is not without good reason. Trees are great! They make oxygen for breathing, suck up CO₂, provide shade, reduce noise pollution, and just look at them — they’re beautiful!

[…]

So Descartes Labs built a machine learning model to identify tree canopy using a combination of lidar, aerial imagery and satellite imagery. Here’s the area surrounding the Boston Common, for example. We clearly see that the Public Garden, Common and Commonwealth Avenue all have lots of trees. But we also see some other fun artifacts. The trees in front of the CVS in Downtown Crossing, for instance, might seem inconsequential to a passer-by, but they’re one of the biggest concentrations of trees in the neighborhood.

[…]

The classifier can be run over any location in the world where we have approximately 1-meter resolution imagery. When using NAIP imagery, for instance, the resolution of the tree canopy map is as high as 60cm. Drone imagery would obviously yield an even higher resolution.

Washington, D.C. tree canopy created with NAIP source imagery shown at different scales—all the way down to individual “TREES!” on The Ellipse.

The ability to map tree canopy at a such a high resolution in areas that can’t be easily reached on foot would be helpful for utility companies to pinpoint encroachment issues—or for municipalities to find possible trouble spots beyond their official tree census (if they even have one). But by zooming out to a city level, patterns in the tree canopy show off urban greenspace quirks. For example, unexpected tree deserts can be identified and neighborhoods that would most benefit from a surge of saplings revealed.

Source: Mapping All of the Trees with Machine Learning – Tim Wallace – Medium

The Amazon Alexa Eavesdropping Nightmare Came True: Creepy Recordings sent to random stranger

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An Amazon user in Germany recently requested data about his personal activities and inadvertently gained access to 1,700 audio recordings of someone he didn’t know.

Germany’s c’t magazine reports that in August the Amazon user—exercising his rights under the EU’s General Data Protection Regulation—requested his own data that Amazon has stored. Two months later, Amazon sent him a downloadable 100Mb zip file.

Some of the files reportedly related to his Amazon searches. But according to the report there were also hundreds of Wav files and a PDF cataloging transcripts of Alexa’s interpretations of voice commands. According to c’t magazine, this was peculiar to this user because he doesn’t own any Alexa devices and had never used the service. He also didn’t recognize the voices in the files.

The user reported the matter to Amazon and asked for information. He reportedly didn’t receive a response, but soon found that the link to the data was dead. However, he had already saved the files, and he shared his experience with c’t magazine out of concern that the person whose privacy had been compromised was not told about the mistake.

C’t magazine listened to many of the files and was able “to piece together a detailed picture of the customer concerned and his personal habits.” It found that he used Alexa in various places, has an Echo at home, and has a Fire device on his TV. They noticed that a woman was around at times. They listened to him in the shower.

We were able to navigate around a complete stranger’s private life without his knowledge, and the immoral, almost voyeuristic nature of what we were doing got our hair standing on end. The alarms, Spotify commands, and public transport inquiries included in the data revealed a lot about the victims’ personal habits, their jobs, and their taste in music. Using these files, it was fairly easy to identify the person involved and his female companion. Weather queries, first names, and even someone’s last name enabled us to quickly zero in on his circle of friends. Public data from Facebook and Twitter rounded out the picture.

Using the information they gathered from the recordings, the magazine contacted the victim of the data leak. He “was audibly shocked,” and confirmed it was him in the recordings and that the outlet had figured out the identity of his girlfriend. He said Amazon did not contact him.

Days later, both the victim and the receiver of the files were called by Amazon to discuss the incident. Both were reportedly called three days after c’t magazine contacted Amazon about the matter. An Amazon representative reportedly told them that one of their staff members had made a one-time error.

When asked for comment on the matter, Amazon sent Gizmodo the same statement it had shared with Reuters. “This was an unfortunate case of human error and an isolated incident. We have resolved the issue with the two customers involved and have taken steps to further improve our processes. We were also in touch on a precautionary basis with the relevant regulatory authorities.”

Amazon did not answer Gizmodo’s questions about how a human error led to this privacy infringement, or whether the company had initially contacted the victim to inform them their sensitive information was shared with a stranger.

Source: The Amazon Alexa Eavesdropping Nightmare Came True

Breakthrough ultrasound treatment to reverse dementia moves to human trials

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An extraordinarily promising new technique using ultrasound to clear the toxic protein clumps thought to cause dementia and Alzheimer’s disease is moving to the first phase of human trials next year. The innovative treatment has proven successful across several animal tests and presents an exciting, drug-free way to potentially battle dementia.

The ultrasound treatment was first developed back in 2015 at the University of Queensland. The initial research was working to find a way to use ultrasound to temporarily open the blood-brain barrier with the goal of helping dementia-battling antibodies better reach their target in the brain. However, early experiments with mice surprisingly revealed the targeted ultrasound waves worked to clear toxic amyloid protein plaques from the brain without any additional therapeutic drugs.

“The ultrasound waves oscillate tremendously quickly, activating microglial cells that digest and remove the amyloid plaques that destroy brain synapses,” explained Jürgen Götz, one of the researchers on the project back in 2015. “The word ‘breakthrough’ is often mis-used, but in this case I think this really does fundamentally change our understanding of how to treat this disease, and I foresee a great future for this approach.”

Source: Breakthrough ultrasound treatment to reverse dementia moves to human trials

At Blind – a whistleblower site -, a security lapse revealed private complaints from Silicon Valley employees. Turns out it’s not very safe to blow your whistle there after all.

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Thousands of people trusted Blind, an app-based “anonymous social network,” as a safe way to reveal malfeasance, wrongdoing and improper conduct at their companies.But Blind left one of its database servers exposed without a password, making it possible (for anyone who knew where to look) to access each user’s account information and identify would-be whistleblowers.

[…]

The exposed server was found by a security researcher, who goes by the name Mossab H, who informed the company of the security lapse. The security researcher found one of the company’s Kibana dashboards for its backend ElasticSearch database, which contained several tables, including private messaging data and web-based content, for both of its U.S. and Korean sites. Blind said the exposure only affects users who signed up or logged in between November 1 and December 19, and that the exposure relates to “a single server, one among many servers on our platform,” according to Blind executive Kyum Kim in an email.

Blind only pulled the database after TechCrunch followed up by email a week later. The company began emailing its users on Thursday after we asked for comment.

“While developing an internal tool to improve our service for our users, we became aware of an error that exposed user data,” the email to affected users said.

Kim said there is “no evidence” that the database was misappropriated or misused, but did not say how it came to that conclusion. When asked, the company would not say if it will notify U.S. state regulators of the breach.

[…]

At its core, the app and anonymous social network allows users to sign up using their corporate email address, which is said to be linked only to Blind’s member ID. Email addresses are “only used for verification” to allow users to talk to other anonymous people in their company, and the company claims that email addresses aren’t stored on its servers.

But after reviewing a portion of the exposed data, some of the company’s claims do not stand up.

We found that the database provided a real-time stream of user logins, user posts, comments and other interactions, allowing anyone to read private comments and posts. The database also revealed the unencrypted private messages between members but not their associated email addresses. (Given the high sensitivity of the data and the privacy of the affected users, we’re not posting data, screenshots or specifics of user content.)

Blind claims on its website that its email verification “is safe, as our patented infrastructure is set up so that all user account and activity information is completely disconnected from the email verification process.” It adds: “This effectively means there is no way to trace back your activity on Blind to an email address, because even we can’t do it.” Blind claims that the database “does not show any mapping of email addresses to nicknames,” but we found streams of email addresses associated with members who had not yet posted. In our brief review, we didn’t find any content, such as comments or messages, linked to email addresses, just a unique member ID, which could identify a user who posts in the future.

Many records did, however, contain plain text email addresses. When other records didn’t store an email address, the record contained the user’s email as an unrecognized encrypted hash — which may be decipherable to Blind employees, but not to anyone else.

The database also contained passwords, which were stored as an MD5 hash, a long-outdated algorithm that is nowadays easy to crack. Many of the passwords were quickly unscrambled using readily available tools when we tried. Kim denied this. “We don’t use MD5 for our passwords to store them,” he said. “The MD5 keys were a log and it does not represent how we are managing data. We use more advanced methods like salted hash and SHA2 on securing users’ data in our database.” (Logging in with an email address and unscrambled password would be unlawful, therefore we cannot verify this claim.) That may pose a risk to employees who use the same password on the app as they do to log in to their corporate accounts.

Despite the company’s apparent efforts to disassociate email addresses from its platform, login records in the database also stored user account access tokens — the same kind of tokens that recently put Microsoft and Facebook accounts at risk. If a malicious actor took and used a token, they could log in as that user — effectively removing any anonymity they might have had from the database in the first place.

As well-intentioned as the app may be, the database exposure puts users — who trusted the app to keep their information safe and their identities anonymous — at risk.

These aren’t just users, but also employees of some of the largest companies in Silicon Valley, who post about sexual harassment in the workplace and discussing job offers and workplace culture. Many of those who signed up in the past month include senior executives at major tech companies but don’t realize that their email address — which identifies them — could be sitting plain text in an exposed database. Some users sent anonymous, private messages, in some cases made serious allegations against their colleagues or their managers, while others expressed concern that their employers were monitoring their emails for Blind sign-up emails.

Yet, it likely escaped many that the app they were using — often for relief, for empathy or as a way to disclose wrongdoing — was almost entirely unencrypted and could be accessed, not only by the app’s employees but also for a time anyone on the internet.

Source: At Blind, a security lapse revealed private complaints from Silicon Valley employees | TechCrunch

New Photo Wake-Up System Turns Still Images Into 3D animations

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The system, called Photo Wake-Up, creates a 3D animation from a single photo. In the paper, the researchers compare it to the moving portraits at Hogwarts, a fictitious part of the Harry Potter world that a number of tech companies have tried to recreate. Previous attempts have been mildly successful, but this system is impressive in its ability to isolate and create a pretty realistic 3D animation from a single image.

The researchers tested the system on 70 different photos they downloaded online, which included pictures of Stephen Curry, the anime character Goku, a Banksy artwork, and a Picasso painting. The team used a program called SMPL and deep learning, starting with a 2D cutout of the subject and then superimposing a 3D skeleton onto it. “Our key technical contribution, then, is a method for constructing an animatable 3D model that matches the silhouette in a single photo,” the team told MIT Technology Review.

The team reportedly used a warping algorithm to ensure the cutout and the skeleton were aligned. The team’s algorithm is also reportedly able to detect the direction a subject is looking and the way their head is angled. What’s more, in order to make sure the final animation is realistic and precise, the team used a proprietary user interface to correct for any errors and help with the animation’s texturing. An algorithm then isolates the subject from the 2D image, fills in the remaining space, and animates the subject.

Source: New Photo Wake-Up System Turns Still Images Into 3D animations

An Amoeba-Based Computer Calculated Approximate Solutions to an 8 city Travelling Salesman Problem

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A team of Japanese researchers from Keio University in Tokyo have demonstrated that an amoeba is capable of generating approximate solutions to a remarkably difficult math problem known as the “traveling salesman problem.”

The traveling salesman problem goes like this: Given an arbitrary number of cities and the distances between them, what is the shortest route a salesman can take that visits each city and returns to the salesman’s city of origin. It is a classic problem in computer science and is used as a benchmark test for optimization algorithms.

The traveling salesman problem is considered “NP hard,” which means that the complexity of calculating a correct solution increases exponentially the more cities are added to the problem. For example, there are only three possible solutions if there are four cities, but there are 360 possible solutions if there are six cities. It continues to increase exponentially from there.

Despite the exponential increase in computational difficulty with each city added to the salesman’s itinerary, computer scientists have been able to calculate the optimal solution to this problem for thousands of cities since the early 90s and recent efforts have been able to calculate nearly optimal solutions for millions of cities.

Amoebas are single-celled organisms without anything remotely resembling a central nervous system, which makes them seem like less than suitable candidates for solving such a complex puzzle. Yet as these Japanese researchers demonstrated, a certain type of amoeba can be used to calculate nearly optimal solutions to the traveling salesman problem for up to eight cities. Even more remarkably, the amount of time it takes the amoeba to reach these nearly optimal solutions grows linearly, even though the number of possible solutions increases exponentially.

As detailed in a paper published this week in Royal Society Open Science, the amoeba used by the researchers is called Physarum polycephalum, which has been used as a biological computer in several other experiments. The reason this amoeba is considered especially useful in biological computing is because it can extend various regions of its body to find the most efficient way to a food source and hates light.

To turn this natural feeding mechanism into a computer, the Japanese researcher placed the amoeba on a special plate that had 64 channels that it could extend its body into. This plate is then placed on top of a nutrient rich medium. The amoeba tries to extend its body to cover as much of the plate as possible and soak up the nutrients. Yet each channel in the plate can be illuminated, which causes the light-averse amoeba to retract from that channel.

To model the traveling salesman problem, each of the 64 channels on the plate was assigned a city code between A and H, in addition to a number from 1 to 8 that indicates the order of the cities. So, for example, if the amoeba extended its body into the channels A3, B2, C4, and D1, the correct solution to the traveling salesman problem would be D, B, A, C, D. The reason for this is that D1 indicates that D should be the first city in the salesman’s itinerary, B2 indicates B should be the second city, A3 that A should be the third city and so on.

To guide the amoeba toward a solution to the traveling salesman problem, the researchers used a neural network that would incorporate data about the amoeba’s current position and distance between the cities to light up certain channels. The neural network was designed such that cities with greater distances between them are more likely to be illuminated than channels that are not.

When the algorithm manipulates the chip that the amoeba is on it is basically coaxing it into taking forms that represent approximate solutions to the traveling salesman problem. As the researchers told Phys.org, they expect that it would be possible to manufacture chips that contain tens of thousands of channels so that the amoeba is able to solve traveling salesman problems that involve hundreds of cities.

For now, however, the Japanese researchers’ experiment remains in the lab, but it provides the foundation for low-energy biological computers that harness the natural mechanisms of amoebas and other microorganisms to compute.

Source: An Amoeba-Based Computer Calculated Approximate Solutions to a Very Hard Math Problem – Motherboard

FCC fines Swarm $900,000 for unauthorized satellite launch

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Swarm Technologies Inc will pay a $900,000 fine for launching and operating four small experimental communications satellites that risked “satellite collisions” and threatened “critical commercial and government satellite operations,” the Federal Communications Commission said on Thursday.

The Federal Communications Commission (FCC) logo is seen before the FCC Net Neutrality hearing in Washington February 26, 2015. REUTERS/Yuri Gripas

The California-based start-up founded by former Google and Apple engineers in 2016 also agreed to enhanced FCC oversight and a requirement of pre-launch notices to the FCC for three years.

Swarm launched the satellites in India last January after the FCC rejected its application to deploy and operate them, citing concerns about the company’s tracking ability.

It said Swarm had unlawfully transmitted signals between earth stations in the state of Georgia and the satellites for over a week. The investigation also found that Swarm performed unauthorized weather balloon-to-ground station tests and other unauthorized equipment tests prior to the satellites’ launch.

Swarm aims to provide low-cost space-based internet service and plans eventually to use a constellation of 100 satellites.

Swarm won permission in August from the FCC to reactivate the satellites and said then it is “fully committed to complying with all regulations and has been working closely with the FCC,” noting that its satellites are “100 percent trackable.”

Source: FCC fines Swarm $900,000 for unauthorized satellite launch | Reuters

EU Diplomatic Comms Network, Which the NSA Reportedly Warned Could Be Easily Hacked, Was Hacked. But contents were boring.

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The European Union’s network used for diplomatic communications, COREU, was infiltrated “for years” by hackers, the New York Times reported on Tuesday, with the unknown rogues behind the attack reportedly reposting the stolen communiqués to an “open internet site.”

The network in question connects EU leadership with other EU organizations, as well as the foreign ministries of member states. According to the Times, the attack was first discovered by security firm Area 1, which provided a bit more than 1,100 of the cables to the paper for examination. Some of the documents show unease over Donald Trump’s presidency and his relationship with the Russian government, while others contain tidbits such as Chinese President Xi Jinping’s feelings about the U.S.’s brimming trade war with his country and rumors about nuclear weapons deployment on the Crimean peninsula:

In one cable, European diplomats described a meeting between President Trump and President Vladimir V. Putin of Russia in Helsinki, Finland, as “successful (at least for Putin).”

Another cable, written after a July 16 meeting, relayed a detailed report and analysis of a discussion between European officials and President Xi Jinping of China, who was quoted comparing Mr. Trump’s “bullying” of Beijing to a “no-rules freestyle boxing match” … The cables include extensive reports by European diplomats of Russia’s moves to undermine Ukraine, including a warning on Feb. 8 that Crimea, which Moscow annexed four years ago, had been turned into a “hot zone where nuclear warheads might have already been deployed.”

Hackers were able to breach COREU after a phishing campaign aimed at officials in Cyprus gave them access to passwords that compromised the whole network, Area 1 chief executive Oren Falkowitz told the Times. An anonymous official at the U.S.’s National Security Agency added that the agency had warned the EU had received numerous warnings that the aging system could easily be infiltrated by malicious parties.

[…]

Fortunately for the EU, the Times wrote, the stolen information is primarily “low-level classified documents that were labeled limited and restricted,” while more sensitive communiqués were sent via a separate system (EC3IS) that European officials said is being upgraded and replaced. Additionally, although the documents were uploaded to an “open internet site,” the hackers apparently made no effort to publicize them, the paper added.

Source: EU Diplomatic Comms Network, Which the NSA Reportedly Warned Could Be Easily Hacked, Was Hacked

This AI Just Mapped Every Solar Panel in the United States

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n some states, solar energy accounts for upwards of 10 percent of total electricity generation. It’s definitely a source of power that’s on the rise, whether it be to lessen our dependence on fossil fuels, nuclear power, or the energy grid, or simply to take advantage of the low costs. This form of energy, however, is highly decentralized, so it’s tough to know how much solar energy is being extracted, where, and by whom.

[…]

The system developed by Rajagopal, along with his colleagues Jiafan Yu and Zhecheng Wang, is called DeepSolar, and it’s an automated process whereby hi-res satellite photos are analyzed by an algorithm driven by machine learning. DeepSolar can identify solar panels, register their locations, and calculate their size. The system identified 1.47 million individual solar installations across the United States, whether they be small rooftop configurations, solar farms, or utility-scale systems. This exceeds the previous estimate of 1.02 million installations. The researchers have made this data available at an open-source website.

By using this new approach, the researchers were able to accurately scan billions of tiles of high-resolution satellite imagery covering the continental U.S., allowing them to classify and measure the size of solar systems in a few weeks rather than years, as per previous methods. Importantly, DeepSolar requires minimal human supervision.

DeepSolar map of solar panel usage across the United States.
Image: Deep Solar/Stanford University

“The algorithm breaks satellite images into tiles. Each tile is processed by a deep neural net to produce a classification for each pixel in a tile. These classifications are combined together to detect if a system—or part of—is present in the tile,” Rajagopal told Gizmodo.

The neural net can then determine which tile is a solar panel, and which is not. The network architecture is such that after training, the layers of the network produce an activation map, also known as a heat map, that outlines the panels. This can be used to obtain the size of each solar panel system.

Source: This AI Just Mapped Every Solar Panel in the United States

Turning Off Facebook Location Services Doesn’t Stop Tracking – you have to hide your IP address

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Aleksandra Korolova has turned off Facebook’s access to her location in every way that she can. She has turned off location history in the Facebook app and told her iPhone that she “Never” wants the app to get her location. She doesn’t “check-in” to places and doesn’t list her current city on her profile.

Despite all this, she constantly sees location-based ads on Facebook. She sees ads targeted at “people who live near Santa Monica” (where she lives) and at “people who live or were recently near Los Angeles” (where she works as an assistant professor at the University of Southern California). When she traveled to Glacier National Park, she saw an ad for activities in Montana, and when she went on a work trip to Cambridge, Massachusetts, she saw an ad for a ceramics school there.

Facebook was continuing to track Korolova’s location for ads despite her signaling in all the ways that she could that she didn’t want Facebook doing that.

This was especially perturbing for Korolova, as she recounts on Medium, because she has studied the privacy harms that come from Facebook advertising, including how it could be previously used to gather data about an individual’s likes, estimated income and interests (for which she and her co-author Irfan Faizullabhoy got a $2,000 bug bounty from Facebook), and how it can currently be used to target ads at a single house or building, if, say, an anti-choice group wanted to target women at a Planned Parenthood with an ad for baby clothes.

Korolova thought Facebook must be getting her location information from the IP addresses she used to log in from, which Facebook says it collects for security purposes. (It wouldn’t be the first time Facebook used information gathered for security purposes for advertising ones; advertisers can target Facebook users with the phone number they provided for two-factor protection of their account.) As the New York Times recently reported, lots of apps are tracking users’ movements with surprising granularity. The Times suggested turning off location services in your phone’s privacy settings to stop the tracking, but even then the apps can still get location information, by looking at the wifi network you use or your IP address.

When asked about this, Facebook said that’s exactly what it’s doing and that it considers this a completely normal thing to do and that users should know this will happen if they closely read various Facebook websites.

“Facebook does not use WiFi data to determine your location for ads if you have Location Services turned off,” said a Facebook spokesperson by email. “We do use IP and other information such as check-ins and current city from your profile. We explain this to people, including in our Privacy Basics site and on the About Facebook Ads site.”

On Privacy Basics, Facebook gives advice for “how to manage your privacy” with regards to location but says that regardless of what you do, Facebook can still “understand your location using things like… information about your Internet connection.” This is reiterated on the “About Facebook Ads” site that says that ads might be based on your location which is garnered from “where you connect to the Internet” among other things.

Strangely, back in 2014, Facebook told businesses in a blog post that “people have control over the recent location information they share with Facebook and will only see ads based on their recent location if location services are enabled on their phone.” Apparently, that policy has changed. (Facebook said it would update this old post.)

Hey, maybe this is to be expected. You need an IP address to use the internet and, by the nature of how the internet works, you reveal it to an app or a website when you use them (though you can hide your IP address by using one provided by the Tor browser or a VPN). There are various companies that specialize in mapping the locations of IP addresses, and while it can sometimes be wildly inaccurate, an IP address will give you a rough approximation of your whereabouts, such as the state, city or zip code you are currently in. Many websites use IP address-derived location to personalize their offerings, and many advertisers use it to show targeted online ads. It means showing you ads for restaurants in San Francisco if you live there instead of ads for restaurants in New York. In that context, Facebook using this information to do the same thing is not terribly unusual.

“There is no way for people to opt out of using location for ads entirely,” said a Facebook spokesperson by email. “We use city and zip level location which we collect from IP addresses and other information such as check-ins and current city from your profile to ensure we are providing people with a good service—from ensuring they see Facebook in the right language, to making sure that they are shown nearby events and ads for businesses that are local to them.”

Source: Turning Off Facebook Location Services Doesn’t Stop Tracking

NASA fears internal server hacked, staff personal info swiped by miscreants

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A server containing personal information, including social security numbers, of current and former NASA workers may have been hacked, and its data stolen, it emerged today.

According to an internal memo circulated among staff on Tuesday, in mid-October the US space agency investigated whether or not two of its machines holding employee records had been compromised, and discovered one of them may have been infiltrated by miscreants.

It was further feared that this sensitive personal data had been siphoned from the hijacked server. The agency’s top brass stressed no space missions were affected, and identity theft protection will be offered to all affected workers, past and present. The boffinry nerve-center’s IT staff have since secured the servers, and are combing through other systems to ensure they are fully defended, we’re told.

Anyone who joined, left, or transferred within the agency from July 2006 to October 2018 may have had their personal records swiped, according to NASA bosses. Right now, the agency employs roughly 17,300 people.

Source: Houston, we’ve had a problem: NASA fears internal server hacked, staff personal info swiped by miscreants • The Register

Facebook Allowed Netflix, Spotify and A Bank To Read And Delete Users’ Private Messages. And around 150 other companies got to see other private information without user consent.

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Facebook gave more than 150 companies, including Microsoft, Netflix, Spotify, Amazon, and Yahoo, unprecedented access to users’ personal data, according to a New York Times report published Tuesday.

The Times obtained hundreds of pages of Facebook documents, generated in 2017, that show that the social network considered these companies business partners and effectively exempted them from its privacy rules.

Facebook allowed Microsoft’s search engine Bing to see the names of nearly all users’ friends without their consent, and allowed Spotify, Netflix, and the Royal Bank of Canada to read, write, and delete users’ private messages, and see participants on a thread.

It also allowed Amazon to get users’ names and contact information through their friends, let Apple access users’ Facebook contacts and calendars even if users had disabled data sharing, and let Yahoo view streams of friends’ posts “as recently as this summer,” despite publicly claiming it had stopped sharing such information a year ago, the report said. Collectively, applications made by these technology companies sought the data of hundreds of millions of people a month.

On Tuesday night, a Facebook spokesperson explained to BuzzFeed News that the social media giant solidified different types of partnerships with major tech and media companies for specific reasons. Apple, Amazon, Yahoo, and Microsoft, for example, were known as “integration partners,” and Facebook helped them build versions of the app “for their own devices and operating systems,” the spokesperson said.

Facebook solidified its first partnerships around 2009–2010, when the company was still a fledgling social network. Many of them were still active in 2017, the spokesperson said. The Times reported that some of them were still in effect this year.

Around 2010, Facebook linked up with Spotify, the Bank of Canada, and Netflix. Once a user logged in and connected their Facebook profile with these accounts, these companies had access to that person’s private messages. The spokesperson confirmed that there are probably other companies that also had this capability, but stressed that these partners were removed in 2015 and, “right now there is no evidence of any misuse of data.”

Other companies, such as Bing and Pandora, were able to see users’ public information, like their friend lists and what types of songs and movies they liked.

Source: Facebook Allowed Netflix, Spotify, And A Bank To Read And Delete Users’ Private Messages

The finger here is being justly pointed at Facebook – but what they are missing is the other companies also knew they were acting unethically by asking for and using this information. It also shows that privacy is something that none of these companies respect and the only way of safeguarding it is by having legal frameworks that respect it.

Amazon and Facebook Reportedly Had a Secret Data-Sharing Agreement, and It Explains So Much

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Back in 2015, a woman named Imy Santiago wrote an Amazon review of a novel that she had read and liked. Amazon immediately took the review down and told Santiago she had “violated its policies.” Santiago re-read her review, didn’t see anything objectionable about it, so she tried to post it again. “You’re not eligible to review this product,” an Amazon prompt informed her.

When she wrote to Amazon about it, the company told her that her “account activity indicates you know the author personally.” Santiago did not know the author, so she wrote an angry email to Amazon and blogged about Amazon’s “big brother” surveillance.

I reached out to both Santiago and Amazon at the time to try to figure out what the hell happened here. Santiago, who is an indie book writer herself, told me that she’d been in the same ballroom with the author in New York a few months before at a book signing event, but had not talked to her, and that she had followed the author on Twitter and Facebook after reading her books. Santiago had never connected her Facebook account to Amazon, she said.

Amazon wouldn’t tell me much back in 2015. Spokesperson Julie Law told me by email at the time that the company “didn’t comment on individual accounts” but said, “when we detect that elements of a reviewer’s Amazon account match elements of an author’s Amazon account, we conclude that there is too much risk of review bias. This can erode customer trust, and thus we remove the review. I can assure you that we investigate each case.”

“We have built mechanisms, both manual and automated over the years that detect, remove or prevent reviews which violate guidelines,” Law added.

A new report in the New York Times about Facebook’s surprising level of data-sharing with other technology companies may shed light on those mechanisms:

Facebook allowed Microsoft’s Bing search engine to see the names of virtually all Facebook users’ friends without consent, the records show, and gave Netflix and Spotify the ability to read Facebook users’ private messages.

The social network permitted Amazon to obtain users’ names and contact information through their friends, and it let Yahoo view streams of friends’ posts as recently as this summer, despite public statements that it had stopped that type of sharing years earlier.

If Amazon was sucking up data from Facebook about who knew whom, it may explain why Santiago’s review was blocked. Because Santiago had followed the author on Facebook, Amazon or its algorithms would see her name and contact information as being connected to the author there, according to the Times. Facebook reportedly didn’t let users know this data-sharing was happening nor get their consent, so Santiago, as well as the author presumably, wouldn’t have known this had happened.

Amazon declined to tell the New York Times about its data-sharing deal with Facebook but “said it used the information appropriately.” I asked Amazon how it was using the data obtained from Facebook, and whether it used it to make connections like the one described by Santiago. The answer was underwhelming.

“Amazon uses APIs provided by Facebook in order to enable Facebook experiences for our products,” said an Amazon spokesperson in a statement that didn’t quite answer the question. “For example, giving customers the option to sync Facebook contacts on an Amazon Tablet. We use information only in accordance with our privacy policy.”

Amazon declined our request to comment further.

Why was Facebook giving out this data about its users to other tech giants? The Times report is frustratingly vague, but it says Facebook “got more users” by partnering with the companies (though it’s unclear how), but also that it got data in return, specifically data that helped power its People You May Know recommendations. Via the Times:

The Times reviewed more than 270 pages of reports generated by the system — records that reflect just a portion of Facebook’s wide-ranging deals. Among the revelations was that Facebook obtained data from multiple partners for a controversial friend-suggestion tool called “People You May Know.”

The feature, introduced in 2008, continues even though some Facebook users have objected to it, unsettled by its knowledge of their real-world relationships. Gizmodo and other news outlets have reported cases of the tool’s recommending friend connections between patients of the same psychiatrist, estranged family members, and a harasser and his victim.

Facebook, in turn, used contact lists from the partners, including Amazon, Yahoo and the Chinese company Huawei — which has been flagged as a security threat by American intelligence officials — to gain deeper insight into people’s relationships and suggest more connections, the records show.

‘You scratch my algorithm’s back. I’ll scratch your algorithm’s back,’ or so the arrangement apparently went.

Back in 2017, I asked Facebook whether it was getting information from “third parties such as data brokers” to help power its creepily accurate friend recommendations. A spokesperson told me by email, “Facebook does not use information from data brokers for People You May Know,” in what now seems to be a purposefully evasive answer.

Facebook doesn’t want to tell us how its systems work. Amazon doesn’t want to tell us how its systems work. These companies are data mining us, sometimes in concert, to make uncomfortably accurate connections but also erroneous assumptions. They don’t want to tell us how they do it, suggesting they know it’s become too invasive to reveal. Thank god for leakers and lawsuits.

Source: Amazon and Facebook Reportedly Had a Secret Data-Sharing Agreement, and It Explains So Much

Ancient Hidden City Discovered Under Lake Titicaca

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Five minutes away from the town of Tiquina, on the shores of Lake Titicaca, archaeologists found the remains of an ancient civilization under the waters of the lake.

The find was made 10 years ago, by Christophe Delaere, an archaeologist from the Free University of Belgium, by following information provided by the locals. 24 submerged archaeological sites have been identified under the lake, according to the BBC.

The most significant of these sites is at Santiago de Ojjelaya, and the Bolivian government has recently agreed to build a museum there to preserve both the underwater structures and those which are on land.

Lake Titicaca. Photo by Alex Proimos CC BY SA 2.0

The project is supposed to be finished in 2020 and will cost an estimated $10 million. The Bolivian government is funding the project with help from UNESCO and is backed by the Belgian development cooperation agency.

The proposed building will have two parts and cover an area of about 2.3 acres (9,360 square meters). One part of the museum will be on the shore, and it will display artifacts that have been raised from the lake bottom. The second part will be partially submerged, with enormous glass walls that will look out under the lake, allowing visitors to see the “hidden city” below.

Old pottery from Tiwanaku at the Ethnologisches Museum, Berlin-Dahlem.

According to the Bolivia Travel Channel, the museum will facilitate the beginning of an archaeological tourism enterprise, which “will be a resort and archaeology research center, geology and biology, characteristics that typified it unique in the world [sic],” according to Wilma Alanoca Mamani, holder of the portfolio of the Plurinational State. Christophe Delaere said that the building’s design incorporates elements of architecture used by the Andean cultures who inhabited the area.

Jose Luis Paz, who is the director of heritage for Bolivia’s Ministry of Culture, says that two types of underwater ruins will be visible when the building is complete: religious/spiritual offering sites, primarily underwater, and places where people lived and worked, which were primarily on the shoreline. He went on to say that the spiritual sites were likely flooded much later than the settlements.

Chullpas from Tiwanaku epoch. Photo by Diego Delso CC BY-SA 4.0

A team of archaeological divers and Bolivian and Belgian experts have located thousands of items in the underwater sites. Some of these pieces will be brought up, but the majority will remain underwater as they are quite well-preserved.

Wilma Mamani said that more than 10,000 items have been found including gold and ceramic pieces and various kinds of bowls and other vessels. The items are of pre-Inca Tiwanaku civilizations. Some of the artifacts have been estimated to be 2,000 years old, and others have been dated back to when the Tiwanaku empire was one of the primary Andean civilizations.

Gateway of the Sun, Tiwanaku, drawn by Ephraim Squier in 1877.

Tiwanaku was a major civilization in Bolivia, with the main city built around 13,000 feet above sea level, near Lake Titicaca, which made it one of the highest urban centers ever built.

The city reached its zenith between 500 AD and 1000 AD, and, at its height, was home to about 10,000 people. It’s unclear exactly when the civilization took hold, but it is known that people started settling around Lake Titicaca about 2,000 BC.

The Gateway of the Sun from the Tiwanaku civilization in Bolivia.

According to Live Science, the city’s ancient name is unknown, since they never developed a written language, but archaeological evidence suggests that Tiwanaku cultural influence reached across the southern Andes, into Argentina, Peru, and Chile, as well as Bolivia.

Tiwanaku began to decline around 1,000 AD, and the city was eventually abandoned. Even when it fell out of use, it stayed an important place in the mythology of the Andean people, who viewed it as a religious site.

Source: Ancient Hidden City Discovered Under Lake Titicaca

Machine learning-detected signal predicts time to earthquake

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Machine-learning research published in two related papers today in Nature Geoscience reports the detection of seismic signals accurately predicting the Cascadia fault’s slow slippage, a type of failure observed to precede large earthquakes in other subduction zones.

Los Alamos National Laboratory researchers applied machine learning to analyze Cascadia data and discovered the megathrust broadcasts a constant tremor, a fingerprint of the fault’s displacement. More importantly, they found a direct parallel between the loudness of the fault’s acoustic signal and its physical changes. Cascadia’s groans, previously discounted as meaningless noise, foretold its fragility.

“Cascadia’s behavior was buried in the data. Until machine learning revealed precise patterns, we all discarded the continuous signal as noise, but it was full of rich information. We discovered a highly predictable sound pattern that indicates slippage and fault failure,” said Los Alamos scientist Paul Johnson. “We also found a precise link between the fragility of the fault and the signal’s strength, which can help us more accurately predict a megaquake.”

Read more at: https://phys.org/news/2018-12-machine-learning-detected-earthquake.html#jCp

Source: Machine learning-detected signal predicts time to earthquake

Google isn’t the company that we should have handed the Web over to: why MS switching to Chromium is a bad idea

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With Microsoft’s decision to end development of its own Web rendering engine and switch to Chromium, control over the Web has functionally been ceded to Google. That’s a worrying turn of events, given the company’s past behavior.

[…]

Google is already a company that exercises considerable influence over the direction of the Web’s development. By owning both the most popular browser, Chrome, and some of the most-visited sites on the Web (in particular the namesake search engine, YouTube, and Gmail), Google has on a number of occasions used its might to deploy proprietary tech and put the rest of the industry in the position of having to catch up.

[…]

This is a company that, time and again, has tried to push the Web into a Google-controlled proprietary direction to improve the performance of Google’s online services when used in conjunction with Google’s browser, consolidating Google’s market positioning and putting everyone else at a disadvantage. Each time, pushback has come from the wider community, and so far, at least, the result has been industry standards that wrest control from Google’s hands. This action might already provoke doubts about the wisdom of handing effective control of the Web’s direction to Google, but at least a case could be made that, in the end, the right thing was done.

But other situations have had less satisfactory resolutions. YouTube has been a particular source of problems. Google controls a large fraction of the Web’s streaming video, and the company has, on a number of occasions, made changes to YouTube that make it worse in Edge and/or Firefox. Sometimes these changes have improved the site experience in Chrome, but even that isn’t always the case.

A person claiming to be a former Edge developer has today described one such action. For no obvious reason, Google changed YouTube to add a hidden, empty HTML element that overlaid each video. This element disabled Edge’s fastest, most efficient hardware accelerated video decoding. It hurt Edge’s battery-life performance and took it below Chrome’s. The change didn’t improve Chrome’s performance and didn’t appear to serve any real purpose; it just hurt Edge, allowing Google to claim that Chrome’s battery life was actually superior to Edge’s. Microsoft asked Google if the company could remove the element, to no avail.

The latest version of Edge addresses the YouTube issue and reinstated Edge’s performance. But when the company talks of having to do extra work to ensure EdgeHTML is compatible with the Web, this is the kind of thing that Microsoft has been forced to do.

[…]

Microsoft’s decision both gives Google an ever-larger slice of the pie and weakens Microsoft’s position as an opposing voice. Even with Edge and Internet Explorer having a diminished share of the market, Microsoft has retained some sway; its IIS Web server commands a significant Web presence, and there’s still value in having new protocols built in to Windows, as it increases their accessibility to software developers.

But now, Microsoft is committed to shipping and supporting whatever proprietary tech Google wants to develop, whether Microsoft likes it or not. Microsoft has been very explicit that its adoption of Chromium is to ensure maximal Chrome compatibility, and the company says that it is developing new engineering processes to ensure that it can rapidly integrate, test, and distribute any changes from upstream—it doesn’t ever want to be in the position of substantially lagging behind Google’s browser.

[…]

Web developers have historically only bothered with such trivia as standards compliance and as a way to test their pages in multiple browsers when the market landscape has forced them to. This is what made Firefox’s early years so painful: most developers tested in Internet Explorer and nothing else, leaving Firefox compatibility to chance. As Firefox, and later Chrome, rose to challenge Internet Explorer’s dominance, cross-browser testing became essential, and standards adherence became more valuable.

With Chrome, Firefox, and Edge all as going concerns, a fair amount of discipline is imposed on Web developers. But with Edge removed and Chrome taking a large majority of the market, making the effort to support Firefox becomes more expensive.

Mozilla CEO Chris Beard fears that this consolidation could make things harder for Mozilla—an organization that exists to ensure that the Web remains a competitive landscape that offers meaningful options and isn’t subject to any one company’s control. Mozilla’s position is already tricky, dependent as it is on Google’s funding.

[…]

By relegating Firefox to being the sole secondary browser, Microsoft has just made it that much harder to justify making sites work in Firefox. The company has made designing for Chrome and ignoring everything else a bit more palatable, and Mozilla’s continued existence is now that bit more marginal. Microsoft’s move puts Google in charge of the direction of the Web’s development. Google’s track record shows it shouldn’t be trusted with such a position.

Source: Google isn’t the company that we should have handed the Web over to | Ars Technica

Google’s Feature for Predicting Flight Delays

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Google is adding its flight delay predictions feature to the Google Assistant.

That means starting this holiday season, you should be able to ask the Google Assistant if your flight is on time and get a response showing the status of your flight, the length of a delay (if there is one), and even the cause (assuming that info is available)

“Over the next few weeks,” Google says its flight delay predictor will also start notifying you in cases where its system is 85 percent confident, which is deduced by looking at data from past flight records and combining that with a bit a machine learning smarts to determine if your flight might be late. That leaves some room for error, so it’s also important to note that even when Google predicts that your flight is delayed, it may still recommend for you to show up to the airport normally.

Still, in the space of a year, Google seems to have upped its confidence threshold for predicted delays from 80 to 85 percent

Source: Google’s Feature for Predicting Flight Delays Actually Sounds Useful Now

‘Farout,’ the most-distant solar system object discovered yet

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For the first time, an object in our solar system has been found more than 100 times farther than Earth is from the sun.

The International Astronomical Union’s Minor Planet Center announced the discovery Monday, calling the object 2018 VG18. But the researchers who found it are calling it “Farout.”
They believe the spherical object is a dwarf planet more than 310 miles in diameter, with a pinkish hue. That color has been associated with objects that are rich in ice, and given its distance from the sun, that isn’t hard to believe. Its slow orbit probably takes more than 1,000 years to make one trip around the sun, the researchers said.
The distance between the Earth and the sun is an AU, or astronomical unit — the equivalent of about 93 million miles. Farout is 120 AU from the sun. Eris, the next most distant object known, is 96 AU from the sun. For reference, Pluto is 34 AU away.
The object was found by the Carnegie Institution for Science’s Scott S. Sheppard, the University of Hawaii’s David Tholen and Northern Arizona University’s Chad Trujillo — and it’s not their first discovery.
The team has been searching for a super-Earth-size planet on the edge of our solar system, known as Planet Nine or Planet X, since 2014. They first suggested the existence of this possible planet in 2014 after finding “Biden” at 84 AU. Along the way, they have discovered more distant solar system objects suggesting that the gravity of something massive is influencing their orbit.

Source: ‘Farout,’ the most-distant solar system object discovered – CNN

Researchers demonstrate teleportation using on-demand photons from quantum dots

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A team of researchers from Austria, Italy and Sweden has successfully demonstrated teleportation using on-demand photons from quantum dots. In their paper published in the journal Science Advances, the group explains how they accomplished this feat and how it applies to future quantum communications networks.

Scientists and many others are very interested in developing truly —it is believed that such networks will be safe from hacking or eavesdropping due to their very nature. But, as the researchers with this new effort point out, there are still some problems standing in the way. One of these is the difficulty in amplifying signals. One way to get around this problem, they note, is to generate photons on-demand as part of a quantum repeater—this helps to effectively handle the high clock rates. In this new effort, they have done just that, using semiconductor .

Prior work surrounding the possibility of using has shown that it is a feasible way to demonstrate teleportation, but only under certain conditions, none of which allowed for on-demand applications. Because of that, they have not been considered a push-button technology. In this new effort, the researchers overcame this problem by creating quantum dots that were highly symmetrical using an etching method to create the hole pairs in which the quantum dots develop. The process they used was called a XX (biexciton)–X (exciton) cascade. They then employed a dual-pulsed excitation scheme to populate the desired XX state (after two pairs shed photons, they retained their entanglement). Doing so allowed for the production of on-demand single photons suitable for use in teleportation. The dual pulsed excitation scheme was critical to the process, the team notes, because it minimized re-excitation.

The researchers tested their process first on subjective inputs and then on different quantum dots, proving that it could work across a broad range of applications. They followed that up by creating a framework that other researchers could use as a guide in replicating their efforts. But they also acknowledged that there is still more work to be done (mostly in raising the clock rates) before the could be used in real-world applications. They expect it will be just a few more years.

Read more at: https://phys.org/news/2018-12-teleportation-on-demand-photons-quantum-dots.html#jCp

Source: Researchers demonstrate teleportation using on-demand photons from quantum dots