Tip Trick Here: 10/24/18

24 October 2018

Italian consumer watchdog hands down €15M in fines to Apple and Samsung for slowing devices

Italy’s Autorità garante della concorrenza e del mercato, roughly equivalent to this America’s FTC, has fined Apple and Samsung a total of $15 million for the companies’ practice of forcing updates on consumers that may slow or break their devices. The amount may be a drop in the bucket, but it’s a signal that governments won’t always let this type of behavior fly.

The “unfair commercial practices” are described by the AGCM as follows:

The two companies have induced consumers – by insistently proposing to proceed with the download and also because of the significant information asymmetry of consumers vis-a-vis the producers – to install software updates that are not adequately supported by their devices, without adequately informing them, nor providing them an effective way to recover the full functionality of their devices.

Sounds about right!

In case you don’t remember, essentially Apple was pushing updates to iPhones last year that caused performance issues with older phones. Everyone took this as part of the usual conspiracy theory that Apple slows phones to get you to upgrade, but it turns out to have been more like a lack of testing before they shipped.

Apple addresses why people are saying their iPhones with older batteries are running ‘slower’

Samsung, for its part, was pushing Android Mashmallow updates to a number of its devices, but failed to consider that it would cause serious issues in Galaxy Note 4s — issues it then would charge to repair.

The issue here wasn’t the bad updates exactly, but the fact that consumers were pressured into accepting them, at cost to themselves. It would be one thing if the updates were simply made available and these issues addressed as they came up, but both companies “insistently suggested” that the updates be installed despite the problems.

In addition to this, Apple was found to have “not adequately informed consumers about some essential characteristics of lithium batteries, such as their average duration and deterioration factors, nor about the correct procedures to maintain, verify and replace batteries in order to preserve full functionality of devices.” That would be when Apple revealed to iPhone 6 owners that their batteries were not functioning correctly and that they’d have to pay for a replacement if they wanted full functionality. This information, the AGCM, suggests, ought to have been made plain from the beginning.

Samsung gets €5 million in fines and Apple gets €10 million. Those may not affect either company’s bottom line, but they are the maximum possible fines, so it’s symbolic as well. If a dozen other countries were to come to the same conclusion, the fines would really start to add up. Apple has already made some amends, but if it fell afoul of the law it still has to pay the price.

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Italian consumer watchdog hands down €15M in fines to Apple and Samsung for slowing devices

The “unfair commercial practices” are described by the AGCM as follows:

The two companies have induced consumers – by insistently proposing to proceed with the download and also because of the significant information asymmetry of consumers vis-a-vis the producers – to install software updates that are not adequately supported by their devices, without adequately informing them, nor providing them an effective way to recover the full functionality of their devices.

Sounds about right!

Apple addresses why people are saying their iPhones with older batteries are running ‘slower’

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MySpace reborn! Facebook will let you pin song clips to your profile

Facebook will let friends learn about you by streaming clips of your favorite songs from your profile in a throwback to MySpace Music. You’ll be able to choose tracks to add to a revamped Music section of your profile that now actually plays songs instead of just showing what artists you Like, and you can pin your favorites right to the top of your profile.

While friends won’t be able to listen to the whole song to see how you express yourself, they’ll get to watch an accompanying video the collages artist photos and album art, like an algorithmic music video. Facebook could eventually strike streaming partnership with companies like Spotify or Apple Music to allow full-song streaming.

The new Music section of the profile comes alongside the rollout of two previously tested features that all build off of Facebook’s recently acquired music licenses from major record labels.

Lip Sync Live

Facebook’s Musical.ly-esque Lip Sync Live feature has now rolled out to all users in many countries, and today opens to Pages to let artists perform for and connect with fans. Lip Sync Live lets you broadcast a video stream of you singing or dancing to a popular song you’ve chosen. And to make singing easier, Facebook is starting to add lyrics to Lip Sync Live starting with hits like Dua Lupa’s “New Rules,” Khalid’s “Better,” and “Girls Like You” by Maroon 5.

Facebook Music For Stories And Feed

Facebook is finally rolling out its soundtracking feature for Stories. This lets you pick from a catalog of songs, choose the section you want, and overlay it on a Story. You can also share these clips to your News Feed. Facebook began testing Music Stories over the past few months following their launch on Instagram in June.

What started as licensing deals to make sure users’ videos wouldn’t be taken down for copyright infringement if they’d added a soundtrack or overhead songs in the background has now blossomed into music features across the app. Facebook clearly sees this as a way to deepen engagement, especially with the elusive teen audience that’s been slipping away to apps like Snapchat that lack the same licenses.

Music is also such a core way that people express themselves. Celebrity dating app Raya, who’s COO Jared Morgenstern worked at Facebook for years, lets users pick soundtracks for slideshows of their photos. It’s almost surprising Facebook never acquired an audio app like Spotify in its infancy, or later Rdio or Deezer. But now through the licensing deals, it can get much of the social benefit of music without having to buy or build an entire streaming music service.

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Tim Berners-Lee on the huge sociotechnical design challenge

In a speech discussing ethics and the Internet, the inventor of the World Wide Web, Sir Tim Berners-Lee, has tasked the technology industry and its coder army with paying continuous attention to the world their software is consuming as they go about connecting humanity through technology.

Coding must mean consciously grappling with ethical choices in addition to architecting systems that respect core human rights like privacy, he suggested.

“Ethics, like technology, is design,” he told delegates at the 40th International Conference of Data Protection and Privacy Commissioners (ICDPPC) which is taking place in Brussels this week.

“As we’re designing the system, we’re designing society. Ethical rules that we choose to put in that design [impact the society]… Nothing is self evident. Everything has to be put out there as something that we think we will be a good idea as a component of our society.”

If your tech philosophy is the equivalent of ‘move fast and break things’ it’s a failure of both imagination and innovation to not also keep rethinking policies and terms of service — “to a certain extent from scratch” — to account for fresh social impacts, he argued in the speech.

He pointed to how Wikipedia had to rapidly adapt its policies after putting online the power for anyone to edit its encyclopedia, noting: “They introduced a whole lot of bureaucracy around it but that actually makes it work, and it ended up be coming very functional.”

He described today’s digital platforms as “sociotechnical systems” — meaning “it’s not just about the technology when you click on the link it is about the motivation someone has to make such a great thing because then they are read and the excitement they get just knowing that other people are reading the things that they have written”.

“We must consciously decide on both of these, both the social side and the technical side,” he said. “[These platforms are] anthropogenic, made by people… Facebook and Twitter are anthropogenic. They’re made by people. They’ve coded by people. And the people who code them are constantly trying to figure out how to make them better.”

His keynote touched on the Cambridge Analytica data misuse scandal as an illustration of how sociotechnical systems are exploding simple notions of individual rights as people’s data is being cumulatively pooled and linked so that it can be repurposed and used to manipulate entire groups and even societies as a whole.

“You data is being taken and mixed with that of millions of other people, billions of other people in fact, and then used to manipulate everybody.

“Privacy is not just about not wanting your own data to be exposed — it’s not just not wanting the pictures you took of yourself to be distributed publicly. But that is important too.”

Given how the Internet’s ballooning connectivity has swept up and swept along personal data, enabling it to flow and pool far from the individuals who generated it in the first place, Berners-Lee also impressed the need for web users to have “the right to be able to share my data with whoever I want”.

And “the right to be able to get at all my data” — praising recent data download efforts from Apple, Twitter and others that let people take their information elsewhere, and lauding the companies for “recognizing that my data is mine to control”.

He also touched on his new startup: Solid, which is on a mission to push the envelope of interoperability, via decentralization, in order to transform how people control and share their own data.

Tim Berners-Lee is on a mission to decentralize the web

“The principle of Solid is it’s a new platform in which you as a user have complete control of your data,” he explained. “It is revolutionary in the sense that it makes any app ask you where you want to put your data. So you can run your photo app or take pictures on your phone and say I want to store them on Dropbox, and I will store them on my own home computer. And it does this with a new technology which provides interoperability between any app and any store.”

Free speech and fighting censorship are other causes helped by putting people in control of their own data, he argued.

“We are not ready for people to use this at home,” he said of Solid. “We are ready for developers to join us in the quest to make new apps, and to make our service more powerful and more secure.

“The platform turns the privacy world upside down — or, I should say, it turns the privacy world right side up. You are in control of you data life… Wherever you store it you can control and get access to it.”

On the wider societal challenges, as regulators are paying increasing attention to powerful tech platforms, Berners-Lee added: “We have to get commitments from companies to make their platforms constructive and we have to get commitments from governments to look at whenever they see that a new technology allows people to be taken advantage of, allows a new form of crime to get onto it by producing new forms of the law. And to make sure that the policies that they do are thought about in respect to every new technology as they come out.

“We’ve got a lot of work to do, and a lot of discussion — across the boundaries of individuals, companies and governments. But very important work.”

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Quoth the Robo-Raven, “Recharge me!”

Researchers at the University of Maryland A. James Clark School of Engineering have been working on the so-called Robo Raven for years. The ongoing project resulted in the first flying drone with independent wing movement, a feature that made these U of M UAV’s closer to birds than ever before.

Now Lena Johnson, a Ph.D. candidate in mechanical engineering, has created the Robo Raven V, an advanced version of the flying drone.

“Robo Raven has given me an entire platform to explore how engineers can take advantage of avian flight to improve drone capabilities,” she told IEEE< ?A>. “As a Ph.D. student, my research is focused on achieving something new with this UAV platform that has already made aviation history by flying on wings that can move independently of each other.”

The new raven has two propellers for faster takeoff and has improved maneuverability thanks to better wing design. As you can see above, it flies like a big butterfly, lightly taking to the breeze with massive mylar wings. It’s a pretty – and clever – version of the typical flying drone and it will be interesting to see how far Johnson can take the technology.

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Curiosity and Procrastination in Reinforcement Learning

Posted by Nikolay Savinov, Research Intern, Google Brain Team and Timothy Lillicrap, Research Scientist, DeepMind

Reinforcement learning (RL) is one of the most actively pursued research techniques of machine learning, in which an artificial agent receives a positive reward when it does something right, and negative reward otherwise. This carrot-and-stick approach is simple and universal, and allowed DeepMind to teach the DQN algorithm to play vintage Atari games and AlphaGoZero to play the ancient game of Go. This is also how OpenAI taught its OpenAI-Five algorithm to play the modern video game Dota, and how Google taught robotic arms to grasp new objects. However, despite the successes of RL, there are many challenges to making it an effective technique.

Standard RL algorithms struggle with environments where feedback to the agent is sparse — crucially, such environments are common in the real world. As an example, imagine trying to learn how to find your favorite cheese in a large maze-like supermarket. You search and search but the cheese section is nowhere to be found. If at every step you receive no “carrot” and no “stick”, there’s no way to tell if you are headed in the right direction or not. In the absence of rewards, what is to stop you from wandering around in circles? Nothing, except perhaps your curiosity, which motivates you go into a product section that looks unfamiliar to you in pursuit of your sought-after cheese.

In “Episodic Curiosity through Reachability” — the result of a collaboration between the Google Brain team, DeepMind and ETH Zürich — we propose a novel episodic memory-based model of granting RL rewards, akin to curiosity, which leads to exploring the environment. Since we want the agent not only to explore the environment but also to solve the original task, we add a reward bonus provided by our model to the original sparse task reward. The combined reward is not sparse anymore which allows standard RL algorithms to learn from it. Thus, our curiosity method expands the set of tasks which are solvable with RL.

Episodic Curiosity through Reachability: Observations are added to memory, reward is computed based on how far the current observation is from the most similar observation in memory. The agent receives more reward for seeing observations which are not yet represented in memory.

The key idea of our method is to store the agent's observations of the environment in an episodic memory, while also rewarding the agent for reaching observations not yet represented in memory. Being “not in memory” is the definition of novelty in our method — seeking such observations means seeking the unfamiliar. Such a drive to seek the unfamiliar will lead the artificial agent to new locations, thus keeping it from wandering in circles and ultimately help it stumble on the goal. As we will discuss later, our formulation can save the agent from undesired behaviours which some other formulations are prone to. Much to our surprise, those behaviours bear some similarity to what a layperson would call “procrastination”.

Previous Curiosity Formulations
While there have been many attempts to formulate curiosity in the past^[1][2][3][4], in this post we focus on one natural and very popular approach: curiosity through prediction-based surprise, explored in the recent paper “Curiosity-driven Exploration by Self-supervised Prediction” (commonly referred to as the ICM method). To illustrate how surprise leads to curiosity, again consider our analogy of looking for cheese in a supermarket.

Illustration © Indira Pasko, used under CC BY-NC-ND 4.0 license.

As you wander throughout the market, you try to predict the future (“Now I’m in the meat section, so I think the section around the corner is the fish section — those are usually adjacent in this supermarket chain”). If your prediction is wrong, you are surprised (“No, it’s actually the vegetables section. I didn’t expect that!”) and thus rewarded. This makes you more motivated to look around the corner in the future, exploring new locations just to see if your expectations about them meet the reality (and, hopefully, stumble upon the cheese).

Similarly, the ICM method builds a predictive model of the dynamics of the world and gives the agent rewards when the model fails to make good predictions — a marker of surprise or novelty. Note that exploring unvisited locations is not directly a part of the ICM curiosity formulation. For the ICM method, visiting them is only a way to obtain more “surprise” and thus maximize overall rewards. As it turns out, in some environments there could be other ways to inflict self-surprise, leading to unforeseen results.

Agent imbued with surprise-based curiosity gets stuck when it encounters TV. GIF adopted from a video by © Deepak Pathak, used under CC BY 2.0 license.

The Dangers of “Procrastination”
In "Large-Scale Study of Curiosity-Driven Learning", the authors of the ICM method along with researchers from OpenAI show a hidden danger of surprise maximization: agents can learn to indulge procrastination-like behaviour instead of doing something useful for the task at hand. To see why, consider a common thought experiment the authors call the “noisy TV problem”, in which an agent is put into a maze and tasked with finding a highly rewarding item (akin to “cheese” in our previous supermarket example). The environment also contains a TV for which the agent has the remote control. There is a limited number of channels (each with a distinct show) and every press on the remote control switches to a random channel. How would an agent perform in such an environment?

For the surprise-based curiosity formulation, changing channels would result in a large reward, as each change is unpredictable and surprising. Crucially, even after cycling through all the available channels, the random channel selection ensures every new change will still be surprising — the agent is making predictions about what will be on the TV after a channel change, and will very likely be wrong, leading to surprise. Importantly, even if the agent has already seen every show on every channel, the change is still unpredictable. Because of this, the agent imbued with surprise-based curiosity would eventually stay in front of the TV forever instead of searching for a highly rewarding item — akin to procrastination. So, what would be a definition of curiosity which does not lead to such behaviour?

Episodic Curiosity
In “Episodic Curiosity through Reachability”, we explore an episodic memory-based curiosity model that turns out to be less prone to “self-indulging” instant gratification. Why so? Using our example above, after changing channels for a while, all of the shows will end up in memory. Thus, the TV won’t be so attractive anymore: even if the order of shows appearing on the screen is random and unpredictable, all those shows are already in memory! This is the main difference to the surprise-based methods: our method doesn’t even try to make bets about the future which could be hard (or even impossible) to predict. Instead, the agent examines the past to know if it has seen observations similar to the current one. Thus our agent won’t be drawn that much to the instant gratification provided by the noisy TV. It will have to go and explore the world outside of the TV to get more reward.

But how do we decide whether the agent is seeing the same thing as an existing memory? Checking for an exact match could be meaningless: in a realistic environment, the agent rarely sees exactly the same thing twice. For example, even if the agent returned to exactly the same room, it would still see this room under a different angle compared to its memories.

Instead of checking for an exact match in memory, we use a deep neural network that is trained to measure how similar two experiences are. To train this network, we have it guess whether two observations were experienced close together in time, or far apart in time. Temporal proximity is a good proxy for whether two experiences should be judged to be part of the same experience. This training leads to a general concept of novelty via reachability which is illustrated below.

Graph of reachabilities would determine novelty. In practice, this graph is not available — so we train a neural network approximator to estimate a number of steps between observations.

Experimental Results
To compare the performance of different approaches to curiosity, we tested them in two visually rich 3D environments: ViZDoom and DMLab. In those environments, the agent was tasked with various problems like searching for a goal in a maze or collecting good and avoiding bad objects. The DMLab environment happens to provide the agent with a laser-like science fiction gadget. The standard setting in the previous work on DMLab was to equip the agent with this gadget for all tasks, and if the agent does not need a gadget for a particular task, it is free not to use it. Interestingly, similar to the noisy TV experiment described above, the surprise-based ICM method actually uses this gadget a lot even when it is useless for the task at hand! When tasked with searching for a high-rewarding item in the maze, it instead prefers to spend time tagging walls because this yields a lot of “surprise” reward. Theoretically, predicting the result of tagging should be possible, but in practice is too hard as it apparently requires a deeper knowledge of physics than is available to a standard agent.

Surprise-based ICM method is persistently tagging the wall instead of exploring the maze.

Our method instead learns reasonable exploration behaviour under the same conditions. This is because it does not try to predict the result of its actions, but rather seeks observations which are “harder” to achieve from those already in the episodic memory. In other words, the agent implicitly pursues goals which require more effort to reach from memory than just a single tagging action.

Our method shows reasonable exploration.

It is interesting to see that our approach to granting reward penalizes an agent running in circles. This is because after completing the first circle the agent does not encounter new observations other than those in memory, and thus receives no reward:

Our reward visualization: red means negative reward, green means positive reward. Left to right: map with rewards, map with locations currently in memory, first-person view.

At the same time, our method favors good exploration behavior:

Our reward visualization: red means negative reward, green means positive reward. Left to right: map with rewards, map with locations currently in memory, first-person view.

We hope that our work will help lead to a new wave of exploration methods, going beyond surprise and learning more intelligent exploration behaviours. For an in-depth analysis of our method, please take a look at the preprint of our research paper.

Acknowledgements:
This project is a result of a collaboration between the Google Brain team, DeepMind and ETH Zürich. The core team includes Nikolay Savinov, Anton Raichuk, Raphaël Marinier, Damien Vincent, Marc Pollefeys, Timothy Lillicrap and Sylvain Gelly. We would like to thank Olivier Pietquin, Carlos Riquelme, Charles Blundell and Sergey Levine for the discussions about the paper. We are grateful to Indira Pasko for the help with illustrations.

References:
[1] "Count-Based Exploration with Neural Density Models", Georg Ostrovski, Marc G. Bellemare, Aaron van den Oord, Remi Munos
[2] "#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning", Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
[3] "Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration", Alexandre Péré, Sébastien Forestier, Olivier Sigaud, Pierre-Yves Oudeyer
[4] "VIME: Variational Information Maximizing Exploration", Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel

Carnot Cycle

Facebook’s Ad Archive Report highlights top political spenders

For obvious reasons, Facebook’s looking to up political advertising transparency ahead of the midterms. Back in May, the social network introduced Ad Archive, a searchable database of political ads in the U.S. It’s following up the feature with a new Ad Archive Report, a weekly snapshot of political spending.

The survey offerings a breakdown of top spenders by campaign, including the amount spent and the number of ads run. The first report for ads on Facebook and Instagram from between May and October 20, shows a total of $256 million spent across 1.6 million ads.

The number includes $12 million related to Facebook’s own election integrity and getting out the vote ads. Other than that, it probably won’t come as a surprise that Beto O’Rourke’s tooth and nail Texas fight leads the way. The Beto for Texas campaign has spent $5.3 million across just over six thousand ads in that period.

Donald Trump’s “The Trump Make America Great Again Committee” is in second place at $1.9 million, while “Donald J. Trump for President, Inc.” is in eighth place at $1.6 million. That’s just behind the $1.7 million spent on Tom Steyer’s “Need to Impeach.” Those will no doubt see a boost as we head toward 2020.

The archive houses ads reaching back to seven years. The site is also offering up an API for researchers to tap into the data.

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A closer look at Mirror

At Disrupt SF, CEO Brynn Putnam demoed and launched Mirror, a smart gadget that sits on your wall and offers virtual fitness classes.

The $1500 device can be paired with a monthly subscription to let the user browse fitness classes, mark their progress, and follow along with other Mirror users. The idea here is that people spend thousands of dollars on gym memberships and/or huge fitness machines like the Peloton, but that Mirror offers a way to get a similar experience at home without taking up all that space.

We caught up with Putnam at the Mirror offices in NYC to check out the product and get more info.

Enjoy the video!

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Subscription management startup RevenueCat raises $1.5M

RevenueCat, a startup that helps developers manage their in-app subscriptions, has raised $1.5 million in new funding.

The company was part of the most recent batch at Y Combinator, and CEO Jacob Eiting said growth has been “a rocket ship” for the past few months. As of this week, RevenueCat is working with 100 live apps, and it’s crossing $1 million in tracked revenue.

The startup offers an API to address what sounds like a straightforward task, supporting in-app subscriptions in iOS and Android. As Eiting put it when I first interviewed him a few months ago, it’s “boring work” solving a “boring problem” — but that’s one of the reasons why developers don’t want to deal with it. It also means they don’t have to spend time dealing with bugs and updates on the subscription side of either platform.

And RevenueCat continues to add new features, like allowing developers to bring their revenue data into analytics and attribution services. That, in turn, makes it easier for them to see which ads are driving real revenue.

The long-term goal is to build what Eiting (who’s pictured above with his co-founder Miguel Carranza) calls a “revenue management platform.”

“Our mission as a company is to help developers make more money,” he said. “I think we do become this one-stop shop, a service that you integrate with all the payment touch points in your app to help you track your revenue and help you understand how customers are spending.”

The new funding (which is on top of the $120,000 RevenueCat received from YC) was led by Jason Lemkin of SaaStr. Eiting said it’s “an obvious fit,” since the software-as-a-service entrepreneurs who read SaaStr articles, listen to its podcasts and attend its events form “this huge community of companies that are potential customers for us.”

FundersClub, Oakhouse Partners, Buckley Endeavours, Josh Buckley and OneSignal CEO George Deglin also invested.

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Help Locate your own Email Message in Someone Else’s Gmail

You’ve sent an important email to a colleague but it is lost in the deluge of emails they receive every day, buried and forgotten. They can obviously use Gmail search operators, like FROM: or SUBJECT:, to locate that email later but wouldn’t it be useful if there were a way to directly locate that one missing email in their mailbox.

Well, there’s an alternate search trick and the sender can actually help the recipient find any specific email message that they have sent in the past.

When you send an email through Gmail, a unique Message ID is added to the email header as per the RFC 822 specification. To know the ID of your message, open the email inside Gmail, go to 3-dot menu and choose Show Original. The Message-ID will be displayed in the first line of the header as shown the screenshot.

The Message ID of a particular email message is exactly the same for both the sender and the recipient. That means if the recipient opens the header of your email in their mailbox, the message ID will match that of the message in your Gmail sent folder.

Gmail offers a lesser-known search operator – rfc822msgid – that helps you search emails by their message ID.

So if our message ID is xyz@mail.gmail.com, a simple search like rfc8222msgid:xyz@mail.gmail.com will return the exact email in search results.

And that’s the trick. This search query will work for both the recipient and the email sender. So if you pass the message ID to the recipient, they can simply use the rfc822msgid operator to locate a specific email from you in their own mailbox.

Since the recipient ID is too complex, you can simply copy of the URL of the Gmail search page and pass them to the recipient. The URL will work for them as well since the Message ID is the same for them as well.

You can also use this search trick to bookmark emails in the browser.

Also see: Send Personalized Emails with Gmail

The post Help Locate your own Email Message in Someone Else’s Gmail appeared first on Digital Inspiration.

Apple patent shows new way to create 3D printed models

A patent filed by Apple Inc. shows a new method to print 3D models using triangular tessellation. The patent office approved the method, which breaks smooth surfaces into little triangles that approximate the shape of the original model, on October 23, 2018.

The unique aspect of the patent involves the infill and surface. The infill are little patterns inside an object that help it retain rigidity. Most infill is usually fairly simple and involves drawing shapes or squiggles inside an object in a uniform way to keep the shape from collapsing. This means that the entire inside of the object is uniform, leading to cracking or brittleness in the finished product. Apple’s solution would change the shape of the internal infill to differently-sized triangles, depending on the print, ensuring that there is more infill on the edges of the object. The same system is used on the surface of the print to approximate smooth surfaces.

Apple listed Michael R. Sweet, Senior Printing System Engineer at Apple Inc., Canada, as the sole inventor. Sweet has patented at least 13 other 3D printing inventions according to 3D Printing Industry.

“In one embodiment, the triangles making up the triangular tessellations are fixed-size triangles. In another embodiment, the triangles making up the triangular tessellations are dynamically sized triangles. By way of example, small triangles could be used to form an object’s edges or other regions in which strength/support is needed. Larger triangles could be used to build-up or construct areas where strength/support is not as critical,” wrote Sweet in the patent. The patent notes that this system can speed up printing considerably as the print head does not have to move back and forth and instead only moves forward to make the triangular shapes. As an example, Sweet points out that circular infill, as shown below, is inefficient.

This obviously doesn’t meet Apple is making a 3D printer. It simply means that a printing researcher at Apple is looking into the problem and has created a slightly more efficient method for designing 3D printed parts.

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The Google Censorship Leak: Are You Being Censored?

Recent years have seen the tables turn on internet giants such as Facebook, Google, and Twitter. Censorship is a word on the lips of people around the globe.

Are the de facto controllers of internet information and dissemination doing enough—or too little—to protect users from negative content while protecting the core tenets of free speech?

A leaked internal research presentation suggests that Google is struggling to find a balance, an existential crisis of sorts. Can tech giants actively protect against the negative aspects of free speech without censoring and destroying the voices of others?

Google: The Good Censor

leaked google report the good censor front page

The internal research presentation was leaked to Breitbart News and is titled “The Good Censor.” The Good Censor offers a rare and almost unprecedented look into how Google struggles to mediate its position at the center of the internet.

Google is a powerful institute in the ebb and flow of internet censorship. The leaked presentation explores the idea that 21st century tech companies “are performing a balancing act between two incompatible positions.”

They’re not wrong.

Who Controls the Internet?

“Is it possible to have an open and inclusive internet while simultaneously limiting political oppression and despotism, hate, violence, and harassment? Who should be responsible for censoring ‘unwanted’ conversation, anyway?”

It is no secret that the online platforms we use are facing unparalleled pressure to moderate the conversation. It isn’t just online, either. The actions and activities taking place across social networks such as Facebook have a direct effect in the “offline” world (as if there is really any boundary between the two, anyway).

The presentation has a few interesting tidbits as to where Google believes the internet is heading, as well as Google’s position.

Perhaps most interesting is that the document appears to contradict Google’s long-held position that it isn’t a media company. Google uses this line of defense to protect from liabilities.

But the distinction that helped Google, Facebook, Twitter, and other social media platforms grow has become increasingly blurry in recent years.

Free speech is “instilled in the DNA of the Silicon Valley startups that now control the majority of our online conversations.” The presentation also acknowledges the role of Section 230 of the Communications Decency Act of 1996 on social media’s explosive growth. The statute effectively grants technology companies immunity from the content posted on the platform.

This distinction is different from traditional media and has empowered Facebook, Twitter, Reddit, and YouTube to become bastions of free speech without fear of consequence (for the companies, not the users).

A Vacuum of Free Speech

As a focal point for public opinion, and so often the loudspeaker of the masses, Google, Facebook, Reddit, and Twitter have had an unmatched role in major recent events.

“The internet was founded on Utopian principles of free speech…”

And the internet has undoubtedly allowed free speech to flourish. The Arab Spring almost certainly would not have taken place without the protected environments of social media. (Here are some tech-savvy ways people work around censorship.)

But within the vacuum of social media, and as Google’s research document declares, “recent global events have undermined this Utopian narrative.” The idea of a Utopian and genuinely egalitarian internet was dead long ago. The Google research document isolates specific incidents in recent years that illustrate how unbridled free speech can damage.

The End of Internet Utopia?

Specifically:

The Ferguson Unrest
Leslie Jones vs. Trolls
US Election 2016
Kashmir Clashes in India
The Philando Castile shooting aftermath
The Rise of the Alt-Right
Queermuseu in Brazil
YouTuber Logan Paul

The events chosen to illustrate the Google research explore the wider role of tech companies in censorship, intentional or not. For instance, the Ferguson protests exposed the difference between platform algorithms. During Ferguson, Twitter was full of detailed accounts of the event, with Facebook was full of the Ice Bucket Challenge. Algorithms can effectively censor the news depending on the platform.

During the 2016 US Presidential Election, over 80,000 Russian-based posts allegedly influenced up to 126 million Facebook users. The posts steered conversations, revealing the “scope and potential impact of fake news on democracy.”

Actress Leslie Jones was subject to a prolonged and persistent sexist and racist Twitter troll campaign. She eventually quit the platform. In the aftermath, a number of alt-right Twitter accounts received platform bans, including the prominent Milo Yiannopolous. Twitter alleged that Yiannopolous was the ringleader of the campaign.

Yiannopolous claimed “This is the end for Twitter. Anyone who cares about free speech has been sent a clear message: ‘You’re not welcome on Twitter.'” (Fortunately, there are Twitter alternatives for you to try.)

Over at YouTube, a series of major brands boycotted the platform after their ads were shown alongside recruiting material for extremist organizations, including ISIS. Google promised to reform their advertising policies (as they did in response to the Logan Paul issue, too).

However, reforms stopped short of ridding YouTube from such material in its entirety because doing so would “place them entirely in the realm of ‘curator and censor.'”

Tech Companies Censor for Governments

For a long time, tech companies played a single, extremely handy get-out-of-jail-free card: “we’re not responsible for what happens on our platforms.” Google, Facebook, Twitter, and others have trotted the defense out so many times that it is now the expectation, with very little questioning. However, Google, and I’m sure the other platforms, are aware that the times are changing. If the tech companies don’t want governments to interfere, then there must be self-regulation, right?

The truth is that we cannot expect governments to act in good faith, either. There are too many instances of governments using tech companies to do their bidding. Plus, the speed of development at tech companies makes it hard for governments to keep up.

In that case, governments have two choices: develop laws with vast overreach, or apply old laws to new tech. It also creates a negative “with us or against us” mentality, where you’re either helping the government, or you are a threat.

As you have seen above, mixed-use social media sites are a (sort of) positive in the fight for censorship. If a government wants to have a piece of content removed, they have to make a formal request.

The yearly Electronic Frontier Foundation “Who Has Your Back” study shows how sites handle requests (see the full “Who Has Your Back” PDF comparison.) Most notably, YouTube receives a full five stars, showing that meaningful censorship can take place. However, this is without examining the details of the reams of content removed from the platform.

Lawful Content Takedown

Tech companies don’t always roll over and agree to a request. There are numerous examples of Apple refusing to cooperate with the government (albeit, the issue usually relates to encryption rather than censorship). In January 2017, US Customs and Border Protection requested Twitter provide the identity of a user who objected to President Trump’s immigration policy.

Twitter took them to court, and Customs and Borders backed down.

Tech companies will comply. Of course, they will; it is the law. But in that, the tech companies only comply with lawful data collection and removal requests. And the numbers of requests have drastically increased in recent years, at least according to transparency reports released by Google, Facebook, Twitter, and Reddit. The below image comes from Google’s “Removal requests by the numbers” section.

Google Transparency report

The rising numbers show that governments around the world are “also trying to tighten their grip on political discourse” by asking tech companies to censor damaging content.

Are Tech Companies Failing the Public on Censorship?

The Google research report is very honest. There are failings. Tech firms:

Incubate fake news by allowing “dubious distributors” to take advantage of the lack of platform checks, gaming algorithms that automatically display news items.
Have “ineffective automation” that cannot cope with the demands of moderation. With so much content, moderation is turned over to AI, meaning a large number of appropriate videos also fall foul of censorship. Overturning wrongful AI censorship decisions can also take a long time.
Commercialize the online conversation by making sure the most advertising revenue friendly content “wins” social media.
Are unfathomably inconsistent regarding the censorship of certain groups and activities.
Regularly underplay the issues of negative or scandal concerning their platforms until hard fact proves otherwise. At that point, the tact switches and it becomes a PR-cover up game of damage limitation, with the real issue never resolved.
Are slow to correct false censorship (see also point two, above).
Often use reactionary tactics in the hope issues blow over before forcing action. In the meantime, platform users and government agencies can speculate, while anger relating to the issue explodes.

So, are tech companies failing the public with regards to censorship?

Yes.

But the tech companies are trying to make amends. Governments are, too, despite their use of social media and tech companies as tools of censorship. In an age where everyone wants to share their opinion, where platforms want users to feel safe, and where that safety can maximize advertising profit (which is, of course, the be all and end all of the internet), censorship will only continue to expand.

As censorship demand fluctuates depending on political mood or major global controversy, only one thing is certain: Google and other tech companies have little chance of pleasing everyone.

Read the full article: The Google Censorship Leak: Are You Being Censored?

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How to Track the Movies and TV Shows You Watch Using Trakt

Mozilla is matching all donations to the Tor Project

Firefox parent Mozilla is returning to back the Tor Project, its long-time ally, after it committed to matching all donations made to fund Tor, the open source initiative to improve online privacy which has just started its annual end of year funding drive.

Tor announced Mozilla’s support today, extending the pair’s partnership which last year helped Tor raise over $400,000 from a similar campaign last year. That is a small seed round for a tech startup, but it represents an important source of income for Tor, which began soliciting ‘crowdfunded’ donations in 2015 in a bid to offset its reliance on government grants.

The company’s latest publicly available accounts cover 2015 when Tor received a record $3.3 million in donations. That’s up from $2.5 million in 2014 and it represented Tor’s highest year of income to date, but state-related grants accounted for 86 percent of the figure. That was an improvement on previous years, but Tor Research Director and President Roger Dingledine admitted that the organization has “more work to do” to change that ratio.

Tor hasn’t made its latest (2016) financials available as of yet, but the past year has seen the organization make big leaps in its product offerings, which are still best known for being used by NSA whistleblower Edward Snowden. Tor launched its first official mobile browser for Android in September and the same month it released Tor Browser 8.0, its most usable browser yet which is based on Firefox’s 2017 Quantum structure. It is also worked closely with Mozilla to bring Tor into Firefox itself as it has already done with Brave, a browser firm led by former Mozilla CEO Brendan Eich.

Beyond the browser and the Tor network itself, which is designed to minimize the potential for network surveillance, the organization also develops a range of other projects. Around two million people are estimated to use Tor, according to data from the organization.

“The Tor Project has a bold mission: to take a stand against invasive and restrictive online practices and bring privacy and freedom to internet users around the world. But we can’t do it alone,” Sarah Stevenson, who is fundraising director at the Tor Foundation, wrote in a blog post.

“Countries like Egypt and Venezuela have tightened restrictions on free expression and accessing the open web; companies like Google and Amazon are mishandling people’s data and growing the surveillance economy; and some nations are even shutting off the internet completely to quell possible dissidence,” she added.

If you feel suitably compelled, you can donate to the Tor Project’s campaign right here.

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Naya Health, once a promising breast pump startup, now leaving customers in the dark

With their loud noises and hard plastic flanges, breast pumps are the bane of many a new mother’s existence. Founded in 2013, Naya Health is one of the most notable tech startups working on a better pump. But the company’s support site is now shutdown and it’s stopped updating its social media accounts. In a report today, CNBC spoke to several customers who said their pumps, which cost $1,000 and aren’t covered by insurance, had stopped working, and Naya Health had not provided them with adequate support or replacement parts.

Several users have also complained on Naya Health’s Facebook page about non-delivery of pumps they ordered months ago. A Kickstarter campaign created for Naya Health’s smart baby bottle, which raised more than $100,000, is also filled with complaints about orders not being fulfilled (the last response from co-founder and CEO Janica Alvarez was posted six months ago).

Naya Health’s Facebook and Instagram accounts haven’t been updated since summer, even though users are still posting complaints, while its Twitter account has been set to protected mode. An email sent to Alvarez, who co-founded the company with her husband Jeffery Alvarez, Naya Health’s CTO, received an auto-reply. TechCrunch has also contacted Naya Health investors Tandem Capital and Bojiang Capital, the co-leads of its seed round, for comment. The company has raised $4.6 million in angel and seed funding, according to Crunchbase.

While the Naya Health breast pump’s price tag is significantly more than most competing devices, customers were willing to give it a chance because of its unique flange design, which used silicone and water instead of plastic cups to recreate a nursing baby’s mouth.

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Amazon Alexa goes AWOL for many users

Some Amazon Alexa users are currently having problems reaching the voice assistant. Instead of reacting to commands, Alexa simply says “sorry, something went wrong.” Amazon hasn’t commented publicly yet on the issue.

Based on tweets and Down Detector, users began having trouble reaching Alexa around 7AM PST. While some had their connection issues resolved quickly, many others are still waiting.

#AlexaDown ! Now I have to remember how to turn the lights on and off again!

— Erin Boyle (@erinboyle05) October 24, 2018

@amazonecho what’s up with Alexa? She seems under the weather. #alexadown #alexanotrreliable

— Holly Ross Tong (@USAHollyRT) October 24, 2018

I would like to apologize to #alexa users worldwide for the 80 times my 6 year old requested “what does the fox say” today which surely caused the outage. She was right to shut down. Enough is enough. I hope @amazon can fix her. #alexadown

— Amy Gail (@AmyGail8) October 24, 2018

This follows an outage last month that mainly affected Echo devices in parts of the United Kingdom, Spain, Germany, and Australia. According to Down Detector’s outage map, however, most of the users who currently can’t reach Alexa are in the United States.

Alexa also suffered an outage in March after an Amazon Web Services networking issue.

TechCrunch has contacted Amazon for comment.

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