After years of teasing, LG is finally selling a rollable OLED TV. The RX-branded Signature OLED R launched in South Korea today, offering a 65-inch 4K display that tucks away into its base at the press of a button. Besides being able to hide completely, as LG has promised in CES previews, the TV has different settings (Full View, Line View and Zero View) for different situations.
We all knew it was coming. Today, the US government’s Department of Justice filed an antitrust lawsuit against Google. The company, which is a part of Alphabet, is accused of having an unfair monopoly over search and search-related advertising. In addition, the department disagrees with the terms around Android, the most widely-used mobile operating system, that forces phone manufacturers to pre-load Google applications and set Google as the default search engine. That decision stops rival search providers from gaining traction and, as a consequence, ensures that Google continues to make enormous amounts of cash via search-related advertising.
“Google pays billions of dollars each year to distributors—including popular-device manufacturers such as Apple, LG, Motorola, and Samsung; major U.S. wireless carriers such as AT&T, T-Mobile, and Verizon; and browser developers such as Mozilla, Opera, and UCWeb— to secure default status for its general search engine and, in many cases, to specifically prohibit Google’s counterparties from dealing with Google’s competitors,” the lawsuit filing reads.
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Walker also argued that Google competes with platforms such as Twitter, Expedia and OpenTable, which let you search for news, flights and restaurant reservations respectively.” Every day, Americans choose to use all these services and thousands more,” he said.
Some of Google’s rivals feel differently. “We’re pleased the DOJ has taken this key step in holding Google accountable for the ways it has blocked competition, locked people into using its products, and achieved a market position so dominant they refuse to even talk about it out loud,” Gabriel Weinberg, CEO of search engine provider DuckDuckGo said in a Twitter thread. “While Google’s anti-competitive practices hurt companies like us, the negative impact on society and democracy wrought by their surveillance business model is far worse. People should be able to opt out in one click.”
As the Wall Street Journal explains, the Justice Department has been preparing to launch this case for over a year. “Over the course of the last 16 months, the Antitrust Division collected convincing evidence that Google no longer competes only on the merits but instead uses its monopoly power – and billions in monopoly profits – to lock up key pathways to search on mobile phones, browsers, and next generation devices, depriving rivals of distribution and scale,” the Department said in a statement today.
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Today’s lawsuit is arguably the biggest antitrust move since the government’s case against Microsoft in 1998. Back then, the technology company was accused of using its Windows monopoly to push Microsoft-made software such as Internet Explorer. A judge eventually ordered Microsoft to break up into two separate companies. The technology giant appealed, however, and by the end of 2001 it had reached a settlement with the department. “Back then, Google claimed Microsoft’s practices were anticompetitive, and yet, now, Google deploys the same playbook to sustain its own monopolies,” the Justice Department argues in today’s lawsuit filing.
eBay is taking on Amazon Warehouse with a new destination called Certified Refurbished, selling used goods from brands like Lenovo, Microsoft and Makita. The idea is that you can buy second-hand products at significant discounts over new, but still get a two-year warranty (from Allstate), a money-back guarantee and 30-day “hassle-free” returns, along with new accessories, manuals and manufacturer-sealed packaging.
eBay’s Certified Refurbished has five priority categories: laptops, portable audio,power tools, small kitchen appliances and vacuums. It offers several brand exclusives, including De’Longhi, Dirt Devil, Hoover, Makita and Philips, along with inventory exclusives from Dewalt, iRobot and Skullcandy. It’s also selling products from participating brands including Dell, Acer, Bissel, Black & Decker, Cuisinart, KitchenAid, Lenovo, Microsoft, Miele and Sennheiser.
To make the cut, manufacturers must offer items in “pristine, like-new condition that has been professionally inspected, cleaned, and refurbished by the manufacturer, or a manufacturer-approved vendor,” according to eBay. It also must be in new packaging with original or new accessories.
Flying is a highly controversial topic in climate debates. There are a few reasons for this.
The first is the disconnect between its role in our personal and collective carbon emissions. Air travel dominates frequent travellers’ individual contributions to climate change. Yet aviation overall accounts for only 2.5% of global carbon dioxide (CO2) emissions. This is because there are large inequalities in how much people fly – many do not, or cannot afford to, fly at all [best estimates put this figure at around 80% of the world population – we will look at this in more detail in an upcoming article].
The second is how aviation emissions are attributed to countries. CO2 emissions from domestic flights are counted in a country’s emission accounts. International flights are not – instead they are counted as their own category: ‘bunker fuels’. The fact that they don’t count towards the emissions of any country means there are few incentives for countries to reduce them.
It’s also important to note that unlike the most common greenhouse gases – carbon dioxide, methane or nitrous oxide – non-CO2 forcings from aviation are not included in the Paris Agreement. This means they could be easily overlooked – especially since international aviation is not counted within any country’s emissions inventories or targets.
How much of a role does aviation play in global emissions and climate change? In this article we take a look at the key numbers that are useful to know.
Global aviation (including domestic and international; passenger and freight) accounts for:
3.5% of ‘radiative forcing’. Radiative forcing measures the difference between incoming energy and the energy radiated back to space. If more energy is absorbed than radiated, the atmosphere becomes warmer.
The latter two numbers refer to 2018, and the first to 2016, the latest year for which such data are available.
Aviation accounts for 2.5% of global CO2 emissions
As we will see later in this article, there are a number of processes by which aviation contributes to climate change. But the one that gets the most attention is its contribution via CO2 emissions. Most flights are powered by jet gasoline – although some partially run on biofuels – which is converted to CO2 when burned.
In a recent paper, researchers – David Lee and colleagues – reconstructed annual CO2 emissions from global aviation dating back to 1940.1 This was calculated based on fuel consumption data from the International Energy Agency (IEA), and earlier estimates from Robert Sausen and Ulrich Schumann (2000).2
The time series of global emissions from aviation since 1940 is shown in the accompanying chart. In 2018, it’s estimated that global aviation – which includes both passenger and freight – emitted 1.04 billion tonnes of CO2.
Aviation emissions have doubled since the mid-1980s. But, they’ve been growing at a similar rate as total CO2 emissions – this means its share of global emissions has been relatively stable: in the range of 2% to 2.5%.5
Non-CO2 climate impacts mean aviation accounts for 3.5% of global warming
Aviation accounts for around 2.5% of global CO2 emissions, but it’s overall contribution to climate change is higher. This is because air travel does not only emit CO2: it affects the climate in a number of more complex ways.
As well as emitting CO2 from burning fuel, planes affect the concentration of other gases and pollutants in the atmosphere. They result in a short-term decrease, but long-term increase in ozone (O3); a decrease in methane (CH4); emissions of water vapour; soot; sulfur aerosols; and water contrails. While some of these impacts result in warming, while others induce a cooling effect. Overall, the warming effect is stronger.
David Lee et al. (2020) quantified the overall effect of aviation on global warming when all of these impacts were included.6 To do this they calculated the so-called ‘Radiative Forcing’. Radiative forcing measures the difference between incoming energy and the energy radiated back to space. If more energy is absorbed than radiated, the atmosphere becomes warmer.
In this chart we see their estimates for the radiative forcing of the different elements. When we combine them, aviation accounts for approximately 3.5% of net radiative forcing: that is, 3.5% of warming.
Although CO2 gets most of the attention, it accounts for less than half of this warming. Two-thirds (66%) comes from non-CO2 forcings. Contrails – water vapor trails from aircraft exhausts – account for the largest share.
We don’t yet have the technologies to decarbonize air travel
Aviation’s contribution to climate change – 3.5% of warming, or 2.5% of CO2 emissions – is often less than people think. It’s currently a relatively small chunk of emissions compared to other sectors.
The key challenge is that it is particularly hard to decarbonize. We have solutions to reduce emissions for many of the largest emitters – such as power or road transport – and it’s now a matter of scaling them. We can deploy renewable and nuclear energy technologies, and transition to electric cars. But we don’t have proven solutions to tackle aviation yet.
There are some design concepts emerging – Airbus, for example, have announced plans to have the first zero-emission aircraft by 2035, using hydrogen fuel cells. Electric planes may be a viable concept, but are likely to be limited to very small aircraft due to the limitations of battery technologies and capacity.
Innovative solutions may be on the horizon, but they’re likely to be far in the distance.
Towards zero-carbon transport: how can we expect the sector’s CO2 emissions to change in the future?
Appendix: Efficiency improvements means air traffic has increased more rapidly than emissions
Global emissions from aviation have increased a lot over the past half-century. However, air travel volumes increased even more rapidly.
Since 1950, aviation emissions increased almost seven-fold; since 1960 they’ve tripled. Air traffic volume – here defined as revenue passenger kilometers (RPK) traveled – increased by orders of magnitude more: almost 300-fold since 1950; and 75-fold since 1960 [you find this data in our interactive chart here].7
The much slower growth in emissions means aviation efficiency has seen massive improvements. In the chart we show both the increase in global airline traffic since 1950, and aviation efficiency, measured as the quantity of CO2 emitted per revenue passenger kilometer traveled. In 2018, approximately 125 grams of CO2 were emitted per RPK. In 1960, this was eleven-fold higher; in 1950 it was twenty-fold higher. Aviation has seen massive efficiency improvements over the past 50 years.
These improvements have come from several sources: improvements in the design and technology of aircraft; larger aircraft sizes (allowing for more passengers per flight); and an increase in how ‘full’ passenger flights are. This last metric is termed the ‘passenger load factor’. The passenger load factor measures the actual number of kilometers traveled by paying customers (RPK) as a percentage of the available seat kilometers (ASK) – the kilometers traveled if every plane was full. If every plane was full the passenger load factor would be 100%. If only three-quarters of the seats were filled, it would be 75%.
The global passenger load factor increased from 61% in 1950 to 82% in 2018 [you find this data in our interactive chart here].
Google exempts its own websites from Chrome’s automatic data-scrubbing feature, allowing the ads giant to potentially track you even when you’ve told it not to.
Programmer Jeff Johnson noticed the unusual behavior, and this month documented the issue with screenshots. In his assessment of the situation, he noted that if you set up Chrome, on desktop at least, to automatically delete all cookies and so-called site data when you quit the browser, it deletes it all as expected – except your site data for Google.com and YouTube.com.
While cookies are typically used to identify you and store some of your online preferences when visiting websites, site data is on another level: it includes, among other things, a storage database in which a site can store personal information about you, on your computer, that can be accessed again by the site the next time you visit. Thus, while your Google and YouTube cookies may be wiped by Chrome, their site data remains on your computer, and it could, in future, be used to identify you.
Johnson noted that after he configured Chrome to wipe all cookies and site data when the application closed, everything was cleared as expected for sites like apple.com. Yet, the main Google search site and video service YouTube were allowed to keep their site data, though the cookies were gone. If Google chooses at some point to stash the equivalent of your Google cookies in the Google.com site data storage, they could be retrieved next time you visit Google, and identify you, even though you thought you’d told Chrome not to let that happen.
Ultimately, it potentially allows Google, and only Google, to continue tracking Chrome users who opted for some more privacy; something that is enormously valuable to the internet goliath in delivering ads. Many users set Chrome to automatically delete cookies-and-site-data on exit for that reason – to prevent being stalked around the web – even though it often requires them to log back into websites the next time they visit due to their per-session cookies being wiped.
Yet Google appears to have granted itself an exception. The situation recalls a similar issue over location tracking, where Google continued to track people’s location through their apps even when users actively selected the option to prevent that. Google had put the real option to start location tracking under a different setting that didn’t even include the word “location.”
In this case, “Clear cookies and site data when you quit Chrome” doesn’t actually mean what it says, at least not for Google.
There is a workaround: you can manually add “Google.com” and “YouTube.com” within the browser to a list of “Sites that can never use cookies.” In that case, no information, not even site data, is saved from those sites, which is all in all a little confusing.
We’re delighted to announce you can now take advantage of graph-native machine learning (ML) inside of Neo4j! We’ve just released a preview of Neo4j’s Graph Data Science™ Library version 1.4, which includes graph embeddings and an ML model catalog.
Together, these enable you to create representations of your graph and make graph predictions – all within Neo4j.
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Graph Embeddings
The graph embedding algorithms are the star of the show in this release.
These algorithms are used to transform the topology and features of your graph into fixed-length vectors (or embeddings) that uniquely represent each node.
Graph embeddings are powerful, because they preserve the key features of the graph while reducing dimensionality in a way that can be decoded. This means you can capture the complexity and structure of your graph and transform it for use in various ML predictions.
Graph embeddings capture the nuances of graphs in a way that can be used to make predictions or lower dimensional visualizations.
In this release, we are offering three embedding options that learn the graph topology and, in some cases, node properties to calculate more accurate representations:
This is probably the most well-known graph embedding algorithm. It uses random walks to sample a graph, and a neural network to learn the best representation of each node.
A more recent graph embedding algorithm that uses linear algebra to project a graph into lower dimensional space. In GDS 1.4, we’ve extended the original implementation to support node features and directionality as well.
FastRP is up to 75,000 times faster than Node2Vec, while providing equivalent accuracy!
This is an embedding technique using inductive representation learning on graphs, via graph convolutional neural networks, where the graph is sampled to learn a function that can predict embeddings (rather than learning embeddings directly). This means you can learn on a subset of your graph and use that representative function for new data and make continuous predictions as your graph updates. (Wow!)
If you’d like a deeper dive into how it works, check out the GraphSAGE session from the NODES event.
Graph embeddings available in the Neo4j Graph Data Science Library v1.4 . The caution marks indicate that, while directions are supported, our internal benchmarks don’t show performance improvements.
Graph ML Model Catalog
GraphSAGE trains a model to predict node embeddings for unseen parts of the graph, or new data as mentioned above.
To really capitalize on what GraphSAGE can do, we needed to add a catalog to be able to store and reference these predictive models. This model catalog lives in the Neo4j analytics workspace and contains versioning information (what data was this trained on?), time stamps and, of course, the model names.
When you want to use a model, you can provide the name of the model to GraphSAGE, along with the named graph you want to apply it to.
GraphSAGE ML Models are stored in the Neo4j analytics workspace.
After spending years promising Congress that the data it collected from third-party sellers wasn’t used to beef up its private-label products, today Amazon decided to roll out a product meant to do exactly that. The Amazon Shopper Panel, as it’s called, promises to pay Amazon customers that offer intel to the ecommerce giant about where they shop when they’re not shopping on Amazon dot com.
Here’s how the Shopper Panel works: After getting an IRL or e-receipt from any business that isn’t owned by Amazon (so Whole Foods or Four Star locations are not eligible), panelists can either submit a picture of that receipt through the app, or in the case of digital copies, forward their emailed details to a panel-specific email address. According to the Panel website, folks that upload “at least” 10 receipts per month can either cash that in for $10 in Amazon credit or $10 donated to their charity of choice. Along with that baseline payout, the app will also dole out additional earnings to panelists who answer the occasional survey about certain brands or products within the app.
Not every receipt counts toward this program. Per Amazon, receipts from grocery stores, drug stores, restaurants, and movie theaters—along with just about any other “retailer” or “entertainment outlet”—are fair game. Receipts from casinos, gun stores, transit fare, tuition or apartment rentals aren’t.
While the program is invite-only for now, any curious Amazon customer based in the U.S. can download the Panel app from the iOS App Store or the Google Play Store if they want to put their name on the waitlist.
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nder the Amazon Panel site’s “Privacy” tab, the company notes that any receipts that you share will go toward “[helping] brands offer better products and [making] ads more relevant on Amazon.” The company also notes any data gleaned from these receipts or surveys might also be used to “ improve the product selection on Amazon.com and affiliate stores such as Whole Foods Market,” and to “improve the content offered through Amazon services such as Prime Video.”
That’s why this rollout is a particularly gutsy move for Amazon to take right now. Recent months have seen the company come under an increasing barrage of regulatory fire from authorities both in the U.S. and in Europe over a scandal that largely revolved around tracking consumers’ purchase data—not unlike the data pulled from the average receipt—on its platform. This past spring, an investigation from the Wall Street Journal revealed that Amazon had spent years surveilling the purchases earned by the platform’s third party sellers specifically to create its own competing products under the Amazon private label. This story came out barely a year after Amazon’s associate general council, Nate Sutton, told Congress that the company didn’t use “individual seller data” to do just that.
Never mind the Feds. American police forces routinely “circumvent most security features” in smartphones to extract mountains of personal information, according to a report that details the massive, ubiquitous cracking of devices by cops.
Two years of public records requests by Upturn, a Washington DC non-profit, has revealed that every one of the United States’ largest 50 police departments, as well as half of the largest sheriff’s offices and two-thirds of the largest prosecuting attorney’s offices, regularly use specialist hardware and software to access the contents of suspects’ handhelds. There isn’t a state in the Union that hasn’t got some advanced phone-cracking capabilities.
The report concludes that, far from modern phones being a bastion of privacy and security, there are in fact routinely rifled through for trivial crimes without a warrant in sight. In one case, the cops confiscated and searched the phones of two men who were caught arguing over a $70 debt in a McDonalds.
In another, officers witnessed “suspicious behavior” in a Whole Foods grocery store parking lot and claimed to have smelt “the odor of marijuana” coming from a car. The car was stopped and searched, and the driver’s phone was seized and searched for “further evidence of the nature of the suspected controlled substance exchange.”
A third example given saw police officers shot and kill a man after he “ran from the driver’s side of the vehicle” during a traffic stop. They apparently discovered a small orange prescription pill container next to the victim, and tested the pills, which contained acetaminophen and fentanyl. They also discovered a phone in the empty car, and searched it for evidence related to “counterfeit Oxycodone” and “evidence relating to… motives for fleeing from the police.”
The report gives numerous other examples of phones taken from their owners and searched for evidence, without a warrant – many in cases where the value of the information was negligible such as cases involving graffiti, shoplifting, marijuana possession, prostitution, vandalism, car crashes, parole violations, petty theft, and public intoxication.
Not what you imagined
That is a completely different picture to the one, we imagine, most Americans assumed, particularly given the high legal protections afforded smartphones in recent high-profile court cases.
In 2018, the Supreme Court ruled that the government needs a warrant to access its citizens’ cellphone location data and talked extensively about a citizen’s expectation of privacy limiting “official intrusion” when it comes to smartphones.
In 2014, the court decided a warrant was required to search a mobile phone, and that the “reasonable expectation of privacy” that people have in their “physical movements” should extend to records stored by third parties. But the reality on the grounds is that those grand words mean nothing if the cops decide they want to look through your phone.
The report was based on reports from 44 law enforcement agencies across the US and covered 50,000 extractions of data from cellphones between 2015 and 2019, a figure that Upturn notes “represents a severe undercount” of the actual number of cellphone extractions.
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They include banning the use of “consent searches” where the police ask the owner if they can search their phone and then require no further approval to go through a device. “Courts pretend that ‘consent searches’ are voluntary, when they are effectively coerced,” the report argues and notes that most people are probably unaware they by agreeing to it, they can have their phone’s entire contents downloaded and perused at will later on.
It also reckons that the argument that the contents of a phone are in “plain view” because a police officer can see a phone when at the scene of a crime, an important legal distinction that allows the police to search phones, is legally untenable because people carry their phones with them as a rule, and the contents are not themselves also visible – only the device itself.
The report also argues for more extensive audit logs of phone searches so there is a degree of accountability, particularly if evidence turned up is later used in court. And it argues for better and clearer data deletion rules, as well as more reporting requirements around phone searches by law enforcement.
It concludes: “For too long, public debate and discussion regarding these tools has been abstracted to the rarest and most sensational cases in which law enforcement cannot gain access to cellphone data. We hope that this report will help recenter the conversation regarding law enforcement’s use of mobile device forensic tools to the on-the-ground reality of cellphone searches today in the United States.”
