The app also highlights gaps in the GTHA's transportation network, from cycling to transit.

By Chelsea La Vecchia

This story was originally published on Torontoist. 

My commute is any cyclist’s dream—I ride 100 metres on a side street, and then it’s a straight shot down Sherbourne—one of Toronto’s only proper cycle tracks—to the beautiful and cyclist-friendly Martin Goodman Trail. From buffered bike lane to protected cycle track, it’s better than what most commuters have to put up with in Toronto these days.

So when I recently had mechanical difficulty that put my bike out of commission, I thought I was in trouble. Big trouble. TTC trouble.

I decided to get a Bike Share Toronto membership, despite knowing my little green Opus would only be in the shop for a few days. It seemed like a good emergency measure so I could be sure I wouldn’t have to hop on an overcrowded, under-air-conditioned subway.

And then I fell in love with an app.

Read more: How Transit App Saved Me From a Terrible Commute

Related on the dandyBLOG:

Bike Share announces expansion: East side draws the short stick 

Bike Share expansion coming thanks to Metrolinx and Toronto Parking Authority partnership

A More Bike-Friendly TTC Means a Better Way for All Riders

Mid-summer newsletter is here!

If new rumours are accurate, we’ll get our first glimpse at the iPhone 7 on September 7th.

Almost always correct leakster Mark Gurman, previously of 9to5 Mac, but now a journalist with Bloomberg, says that the iPhone 7 will be revealed at an upcoming September 7th Apple keynote.

Corroborating earlier rumours, Gurman says that the iPhone 7 is set to drop the device’s headphone jack, a controversial move, but will also include a new haptic feedback home button. Also, the phone will overall look nearly identical to the iPhone 6S, with Apple saving a more extensive revamp for its next iteration of the iPhone.

A larger Plus model of the iPhone 7 will reportedly be be released as well.

Related reading: iPhone 7 rumoured to feature pressure-sensitive home button

Control Order House Installation View, Edmund Clark. All images courtesy of the artist and the Imperial War Museum of London

The so-called "War on Terror" doesn’t make news headlines like it used to, but the military campaign rages on. As it persists, increasingly unsettling fragments emerge from the ashes of catch-all ‘counterterrorism,’ and British photographer and artist Edmund Clark is ready and waiting to pick up the pieces. Edmund Clark: War of Terror, his ongoing solo exhibition at the Imperial War Museum of London, is a collection of multimedia projects engaging with disparate aspects related to the War on Terror and other elements of pervasive state control.

Redacted image of a complex of buildings where a pilot identified as having flown rendition flights lives; from the series Negative Publicity, Edumnd Clark & Crofton Black

In Negative Publicity, Clark has visualized the research of counterterrorism investigator Crofton Black. Locations related to rendition flights, which involve the secret abductions of ‘dangerous individuals,’ are revealed, ranging from hotels used by the rendition teams to the now-abandoned interrogation rooms used for the abductees. The images are almost always devoid of people and at times have been heavily censored, an eerie combination of ghostly suppression.

Home; from the series Guantanamo: If the Light Goes Out, Edmund Clark

Guantanamo: If the Light Goes Out illustrates the experience of Guantanamo detainees in three distinct chapters: Guantanamo itself, the camps in which the prisoners are detained, and the homes of released detainees attempting to reintegrate themselves into society after their traumatic experiences.

Letter from Sarah, a college student; from the series Letters to Omar, Edmund Clark

Letters to Omar, another project on view, also deals with Guantanamo, but hones in on Omar Deghayes, a UK resident who was detained for five years before his release in 2007. Letters sent to him while at Guantanamo are on view, but these are in fact scans of copies of the originals; results of the heavily bureaucratic censorship applied onto the correspondence to disallow Deghayes from viewing the original copies.

Bedroom; from the series Control Order House, Edumnd Clark

An anonymous terror suspect is the subject of Control Order House. The hundreds of images included in this section are of the house where the suspect was forced to live in during the investigation, as part of the British government's “Home Office enforced control order.” While he is absent from the images and his identity is hidden, it is revealed that the individual was detained without trial, solely on the basis of unrevealed ‘secret evidence.’

Edmund Clark: War of Terror Installation View, Edmund Clark

Clark’s interest in the war stems off of three primary motivations. The first is originated from “Guantanamo Bay becoming a geo-political event. It was the contrast between the imagery of ‘the worst of the worst’ in orange jumpsuits, and the first British detainees who came back to the UK and were never tried for anything and went back to live in their houses as innocent people. My work started by exploring that contrast,” Clark tells The Creators Project.

“Secondly, the realization that the propaganda, which is a common part of war, was not able to reach a new level through the combination of 24/7 global media, the Internet, digital technology, and social media in particular. So I have been interested in the war of terror and war of images-as-spectacle, and how that has been used by all sides. Thirdly, I have been interested in new forms of conflict which seem to characterize this war, and in particular trying to explore visual strategies and forms for seeing unseen or unaccountable experiences and the processes of conflict.”

Abu Salim prison, Libya; from the series Negative Publicity: Artefacts of Extraordinary Rendition, Edmund Clark & Crofton Black

Clark believes that these bodies of work, as well as his other projects investigating the War on Terror are not meant to shape events at large, but instead serve as point of reflection for the future: “I think my work may have more influence in years to come when people look back and reflect on these events and the questions my work raises. Contemporaneously, I think all I can possibly hope is to make work which engages people enough for them to reflect, revisit, and reconfigure how and what they think about these events and the processes behind them,” Clark adds.

Edmund Clark: War of Terror will be on view at the Imperial War Museum of London until August 28th, 2017. View more of Clark’s works here. 

Related:

Laura Poitras' First Solo Show Makes the Surveillance State Visible

Surveillance Art Takes Action in a Post-Snowden World

Sublime Oil Paintings Unveil the Anxieties of War

Imagine a colleague learnt a technique that would save her 12 minutes per day (or one hour per week).

That adds up to 48 hours per year for a period of 3 years (average employee retention rates). If she costs the organisation $70 per hour, that one tip is worth $10k+.

Now imagine she shares that tip with the rest of the team and it spreads to 10 other staff. That one tip is now worth $100k+.

These are the kind of sums what makes building a community of practice within organisations so appealing. It’s the kind of maths that makes training or reading a book so important. Single tips multiplied by years, costs, and staff members become huge cost savings.

And the crazy thing is most teams spend almost no time even looking for these sorts of tips.

Staff members might spend their own time reading blogs and books looking to serendipitously pick up an idea or two they might one day use. We have plenty of hackathons to build new products but no knowledge-a-thons to build new knowledge.

Imagine the tremendous value that would accrue to those that deliberately and proactively sought out exactly the ideas that would have the biggest impact.

Make a list of where people spend most of their time. Now proactively look for tips that would save time or improve performance in each of these. Make it part of the team’s goals at the organisation to improve the way they work by 5% each quarter. Give them the space to do it too.

Now document each tip and set a weekly 15 minute webinar hosted by a rotating colleague each week to share what they have learnt to save time or improve outcomes. It might be new tool, a great idea, or an entire new approach.

Make it a challenge if you like. Solicit ratings each week. Keep a score table of how useful each tip has been.

Make being better and more efficient an ongoing mission for your team.

It seems that 3.5 is the new 2.7. Kind of serendipitous that this is happening just when I’m starting to do new projects using uvloop and asyncio (I even updated a set of Docker containers to include Python 3.5).

Maybe it’s time to see if it’s finally feasible to run this site on 3.5 as well — without undue haste, of course…

Thinking of buying a used bike on Craigslist, Kijiji, eBay, LesPAC, or any other Online Market Place? Here’s a guide to help you find a good quality, bargain-priced used bike. This guide will show you what research you should do, what to watch out for, and which brands can be trusted when you set out to buy a used bike.

The post How to Buy Used Bikes on Craigslist (and Other Online Marketplaces) appeared first on Average Joe Cyclist.

Ich bin seit 2008 bei Facebook und habe heute, neben meinem persönlichen Profil auch vier Facebook Pages in der Betreuung:

• mobile zeitgeist
• APPS MARKETING
• ZUKUNFT DES EINKAUFENS
• THE DIGNIFIED SELF

Natürlich fanden sich auf meinem Smartphone (OnePlus One) neben der „normalen“ Facebook-App auch noch der Seitenmanager und der Messenger.

Seit einiger Zeit ging mir die Facebook-App wegen ihres extrem hohen Akkuverbrauchs zunehmend auf die Nerven. Doch da ich vor einigen Monaten schon einmal die auf Tinfoil basierende Browser-Alternative Metal ausprobiert hatte und sie nicht stabil bei mir lief, hatte ich kaum Ambitionen, etwas zu ändern. Die übliche Trägheit, gewohnte Abläufe zu ändern, kam hinzu.

Neuer Versuch

Was genau mich dazu bewogen hat, nun doch einen neuen Versuch u.a. mit Metal zu wagen? Eine weitere Zugfahrt, bei der ich kaum abgefahren war und mein Ladebalken schon erschreckend klein geworden war. Das musste sich ändern.

Also habe ich in den vergangenen Wochen sowohl Metal als auch Swipe ausprobiert. Beides sind Wrapper, die im Grunde „nur“ die Bedienung der mobilen Webseiten von Facebook vereinfachen und verbessern. Genau dies tun sie allerdings beide wirklich sehr gut.

Leichte Schmerzen

Fast alles ist ebenso bequem, schnell und einfach zu nutzen. Aber eben nur fast alles. Auf einige Funktionen muss man bei beiden verzichten.

1. 360 Grad Fotos
2. Live Videos
3. Pinchen und zoomen
4. Push-Benachrichtigungen (das Fehlen macht das Leben erheblich ruhiger!)
5. Teilen von Beiträgen auf eigenen Seiten
6. Messenger-Nachrichten auf eigenen Pages werden zwar angezeigt, man gelangt auch kurz auf eine Seite, um den Messenger herunter zu laden, beide Wrapper springen dann aber sofort wieder auf die Übersichtsseite

Für mich mit den oben erwähnten vier Seiten, die thematisch alle einigermaßen dicht beieinander liegen und ich sehr gern cross-poste, ist der Punkt 5 das größte Manko der Wrapper. Diese fehlende Funktion macht mir wirklich das Leben schwer.

Ich muss also den Beitrag aus meiner persönlichen Timeline speichern und später am PC erneut herausfischen und dann auf den Seiten teilen. Extrem nervig. Swipe hat zumindest schon für seine Pro-Version angekündigt, dass sie dieses Feature auf dem Radar haben und alsbald ergänzen wollen.

Swipe ist meine Wahl

Metal bietet im Vergleich zu Swipe noch die Möglichkeit, einen Twitter-Account mit aufzunehmen und zu administrieren. Aber für meine verschiedenen Twitter-Accounts nutze ich ohnehin Hootsuite (sowohl am Desktop als auch mobil), so dass dies für mich unerheblich ist.

Da sich Metal und Swipe ansonsten nicht sehr unterscheiden, ist bei mir Swipe im Einsatz. Ich bin damit nicht 100%ig glücklich, bleibe aber dabei. Denn mein Akku, der hält und hält und hält. Winfuture kam Anfang dieses Jahres mit Metal auf eine Ersparnis von 20 Prozent.

Beide Wrapper bekommen von den Nutzern gute Bewertungen: Metal 4,3 von 5 Sternen (37.600 Downloads), Swipe 4,5 Sterne (21.000 Downloads).

Guter Datenschutz

Bei der Wahl eines Wrappers sollte man auch beachten, dass man vor der Datenkrake Facebook weitgehend sicher ist. Dies war für mich auch wichtig, aber nicht der vorrangige Grund für den Einsatz eines Wrappers.

Es gibt natürlich auch noch andere Möglichkeiten, die Facebook-App zu umgehen, z.B. Hermit.

Hier Basisversionen downloaden: Metal | Swipe

Beide Wrapper haben Pro Versionen mit leicht erweiterten Funktionen: Metal 1,50€ | Swipe 3,09€

Setzt Ihr noch auf die gefräßige Facebook-App? Oder nutzt Ihr die mobilen Webseiten ohne Wrapper? Etwas anderes? Wie zufrieden seid Ihr damit?

Teilt Eure Erfahrungen mit den LeserInnen von mobile zeitgeist. Hier in den Kommentaren oder auch auf unseren Social Media Kanälen.

Within everyday social life, those who fall outside normative boundaries are subject to social censure through rejection, exclusion, vitriol, and violence. One group — white, male, cis, able-bodied, neurotypical, thin — is assumed to be normal and can operate in a way that feels relatively effortless while the rest have to adapt and account for their difference. The non-normative may then be marginalized or erased to preserve the illusion of those norms’ universality.

This false universality, and the indifference it can breed, is the crux of privilege: The privileged group needn’t worry themselves with the nuts and bolts of social navigation, because the system has evolved to accommodate them. That is, they have used their sociopolitical dominance to replicate their advantage as part of the natural order. Privilege can be explicit (e.g., “Whites Only!”), but more often, it blends in with the mundanity of social organization (e.g., sidewalks without wheelchair-accessible curb cuts).

One of the dominant lines in tech critique today — that phones and social media diminish face-to-face interaction and thus erode “real” human connection — trades in privileged and normative logic. The critique of screens as alienating is less about screens than about what constitutes the essence of human nature, and who counts as fully human with respect to that fixed, homogenous, and highly particularized version of humanity. To assess the validity and ramifications of this critique, it’s important to have a clear picture of the universal human with which critics begin — and an account of all those whom the model tacitly discounts.

It is not difficult to find examples of prominent academics making the case that screens proliferate to humanity’s detriment, stunting our ability to connect and participate in “real” sociality. In 2014, clinical psychologist Sue Johnson argued in Wired that “real connection with others is being crowded out by virtual kinship.” Sherry Turkle claimed in 2015 that “you need to suppress your empathy ‘gene’ in order to participate fully in the mobile revolution.” And in 2016, sociologist Zygmunt Bauman argued in El País that “it’s so easy to add or remove friends on the internet that people fail to learn the real social skills, which you need when you go to the street, when you go to your workplace, where you find lots of people who you need to enter into sensible interaction with.”

Never mind that a dip into the research reveals these critics’ claims to be empirically unfounded — kinship is maintained (not “crowded out”) by digital connectivity, digital media are tools that effectively strengthen (not “suppress”) empathy, and today’s “workplace” is more accurately defined by project affiliation than shared office space. And of course, never mind that screen-mediated and face-to-face communication are not zero-sum — data show that digitally mediated communication augments rather than replaces face-to-face interaction.

These critics are instead driven by an ideological presupposition about screens separating people both from each other and from an essential part of themselves. As genuine as this concern may be, it is nonetheless predicated on a belief that our essence is the same and that screens affect us in basically the same way, no matter who we are. They assume a universal human nature, embodied by a normative technology user — one for whom face-to-face interaction is both possible and optimal, and whose local networks are consistently supportive and healthy. That is, the tech critics’ model human has full mental and physical health, a typical neurological profile, is “able” bodied, and self-identifies in socially supported ways. This model certainly does not describe all people, nor does it describe any person at all times. When critics lament the rise of screens and the supposed downfall of social connection, what they ignore is human diversity.

While it is true that communication media shape how people engage with one another and with the social world, a medium is not valuable or detrimental in its own right but more or less helpful and appropriate depending on circumstances. These tech critics begin with the concern that humanity suffers from the loss of an ideal communicative form — face-to-face interaction — and fail to ask the sociological question: Ideal for whom, and under what conditions? By doing so, the dominant tech critique overlooks entirely those people for whom face-to-face communication creates obstacles to interaction and for whom digital media is socially beneficial.

In a study of adults with early-onset Alzheimer’s, sociologist Jason Rodriquez showed how an online forum was instrumental in helping participants maintain social connection and preserve a sense of self. Participants lauded the benefits of a community, but they also found reprieve in the cadence of interaction afforded by the platform. Rodriquez’s participants reported that asynchronous communication made social engagement more accessible by circumventing the speed of face-to-face interaction. “I’m having a little trouble having normal conversations, but with typing I have all day to collect and express my thoughts,” one participant explained.

Alzheimer’s patients are far from alone in finding screen-mediated communication empowering where face-to-face was prohibitive. People with physical disabilities, people with neuro-atypicalities, people who are ill, and people with contested identities all may invigorate their social lives through digital media. And as Zeynep Tufekci pointed out in the Atlantic in 2012, “people who don’t dominate conversations…who appear shy, are less outgoing, who feel nervous talking to new people” and those who “are different from the people around them” may also benefit. Thus, in its striking specificity, the tech critics’ model is not only exclusionary, but also ableist, normative, and morally saturated.

Human bodies are far from uniform. Sight, sound, and mobility vary widely across populations, and across the course of any individual’s life. For many, physiology makes face-to-face interaction inaccessible or less accessible than digitally mediated forms of communication. For a person who is hearing impaired, communicating through text- and image-based platforms removes a significant barrier. For a person with nonstandard body control, screen mediation makes conversations and communities available. For those with vision impairments, gestural cues are not more authentic but superfluous, serving no communicative function. The normative model that insists on face-to-face engagement thus erases the disabled body.

So too, the normative tech critique discounts the atypical mind. A person with indicators of ADHD may find it intolerable to engage in one-on-one conversation with continuous eye contact. A person with traumatic brain injury may struggle to focus on multiple stimuli simultaneously, as in a crowded coffee shop or buzzing restaurant. A person on the autism spectrum may be better able to engage on a text-based platform in which word choice takes primacy over facial expressions.

In order to take face-to-face communication as more real, one must take for granted ableist assumptions of physically able bodies and neurotypical minds, of those who walk briskly, see, hear, and speak clearly, effectively read facial cues, and engage in ways that put most others at ease. If someone wheels, crutches, signs, stutters, interprets speech in literal terms, thrives in repetition and patterns, concentrates too long, shifts attention too quickly, feels uncomfortable with physical touch, or relies on touch to navigate the physical landscape, venturing into social interaction can pose exceptional challenges — not because of physical or cognitive deficiency but because infrastructures have been narrowly designed for a particular kind of person.

A variety of communicative forms can expand the definition of conversation and welcome a neurodiverse population — historically excluded from aspects of social life — into the web of social engagement. Yet normative bias in tech criticism not only ignores this opportunity but actively reinforces the devalued meanings associated with medical labels of cognitive difference. They claim that the internet makes us “autistic,” “schizophrenic,” and “ADHD” — labels deployed as signifiers of deficit, of something gone awry. We are thus purportedly suffering from technologically induced neuropathologies, curable only by unplugging and connecting with ourselves and each other in the “real” world. In contrast, screens can be the very way that we, as a society, stop pathologizing difference and instead broaden how and with whom we communicate. Screens offer a chance to question the value of “typical” thinking and, in turn, discover the richness of the human mind in all its varied forms.

It is notable that tech critics are not wary of those adaptive technologies that help people with disabilities more seamlessly negotiate the built environments and social arrangements constructed specifically for people with “able” bodies and typical ways of thinking and learning. Because of their ableist assumptions, tech critics do not apply their critique to adaptive technologies that help people speak, walk, see, and hear. They make no comment on the cochlear implant that transmits sound to deaf ears; they are uncritical of text-and-image-to-speech software that turns visual signals into auditory ones for people who are blind; they leave unaddressed the computer programs designed to teach people with autism how to accurately interpret facial cues. Indeed, these are all technologies that help people who are “different” adapt to circumstances for which they are ill equipped. These technologies treat disability as a problem to be cured rather than diversity to be acknowledged and accommodated. The burden of adaptation and inclusion is borne by those with disabilities — who are tasked with finding, paying for, and using the technologies in ways that are unobtrusive — rather than carried by society as a whole. Such adaptive technologies not only serve disabled populations but also serve the status quo. Their application does not threaten existing models of human nature nor insist upon social and structural adjustments for the sake of inclusivity. Instead, they allow stigma and exclusion to remain intact, as those who are stigmatized and excluded retrofit their bodies and train their minds for optimal function in an unaccommodating social system.

The ableism embedded in the normative tech critique is clear and reflects patterns of exclusion that pervade public social life. Yet those whose bodies and minds fall under the category of “disabled” are not the only ones forgotten by the critics. Rather, through the ebbs and flows of health, illness, and the inevitabilities of aging, the tech critics’ normative model inevitably excludes us all.

It is obvious how those with serious conditions that warrant prolonged hospitalization would benefit from phones and ubiquitous connectivity: Digital media not only provide access to an outside world but also can provide community through which those managing ill health can commiserate, gather information, exchange resources, get well, and find comfort in a shared condition. But even something as ordinary as the common cold reveals the limits of face-to-face communication. Not only does the person with clogged sinuses and a congested chest not want to be around people; others don’t wish to be in their presence. Screen mediation becomes a sick person’s access to social engagement, a means of human connection from beneath the blankets and tissues of isolated misery.

So too, digital media can give respite from the isolation of a contested identity. Screen mediation can be an equally important or even life-saving tool for those who feel (or know) that they cannot openly express their sexual preference, gender identity, religious beliefs, or political propensities because of unaccepting local social networks. For those with contested identities, screens provide a means of commiseration, collaboration, and eventually, collective action, with the potential for social change.

Increasingly, people are “coming out” via Facebook, announcing their sexual identity in a way they may give them more control. The affordances of large and overlapping networks, coupled with the time to craft a thoughtful message, facilitate what Nathan Jurgenson and I call “context collusion”: using social network sites to reach a vast audience and efficiently present the self in one’s own terms. Teens like Ryan Eichenauer, who went viral after posting a video status update declaring his romantic interest in men, deploy the screen to connect with family and friends in a truthful way while laying claim to identities for themselves.

Bauman complains that people use social media to “cut cultural comfort zones,” creating networks that reflect them back to themselves, instead of exposing the self to the full breadth of humanity. Rather than enter into debate and discomfort, he argues, people construct community with those who will not challenge their sense of self, and society is weaker for this. But broad exposure is a luxury enjoyed by those who identify in socially approved ways. For the rest, those for whom normal daily life is uncomfortable or dangerous, a cultural comfort zone may be an urgent need, not a narcissistic or egocentric proclivity.

To accept the argument that screens threaten our very humanness requires that one accepts the premise of an intractable human nature, one built upon a framework of normativity and privilege. Like all claims to human nature, tech critics misunderstand the dynamic human condition, and instead operate with a static picture of what is “good” and “right” for social and personal life. Such a model is at best misguided, and in practice, deeply exclusionary. In fact, no one will be able to satisfy the full range of norms implicit in the “screens prevent real conversation” critique throughout the entire span of their life. If only those who can always talk face-to-face are qualified to have real conversations, they may find there’s no one left to talk to.

Gregor Aisch and Larry Buchanan for the New York Times visualized Olympic medal dominance with a streamgraph for each event. Time is on the horizontal axis, and each stack represents a country. The greater the height is at any point, the more medals the country won that year. Nice labels, too.

Tags: New York Times, Olympics, streamgraph

Elisabeth Pain, Science, Aug 12, 2016

This is not a how-to article as the title suggests but rather a collection of dozens of short comments describing how various people - ranging from students to professors to editors - read scientific papers. There's a lot in common across the different accounts. They typically start with the title and abstract, jump to the conclusion, and look at the figures. From there the methodology varies a lot. I read scientific papers every day as a part of my job. My method is similar. I will focus more on methdology because it helps me weed out the trivial (eg., studies where n=6). I skim the literature view (which is almost always a list of cites in prose form, and rarely an actual summation). I focus on the discussion. The conclusion is less interesting than you might think; researchers often 'bury the lede' - the most important point may be something they observe in passing rather than in the statement of outcomes.

In good news for travellers without roaming plans or those who don’t have much data to spare, Google Maps is rolling out a substantial update that allows users to enable a Wi-Fi only offline mode.

Once the feature is activated, Maps will operate as usual on Wi-Fi, then immediately switch into offline mode when it leaves connectivity range, working only where the user has saved offline maps.

Additionally, the update brings with it the ability to save offline maps to a microSD card, if the user’s handset supports external memory.

The feature can be switched on through a toggle in the app’s settings. At this point, Google notes that “a small amount of data might still be used, but it will be significantly less while on Wi-Fi only.”

Once that’s done, the app will prompt users to choose their location preference when it comes to saving offline maps — internal or external memory — and will show how much spaces is free in both storage options.

The update is rolling out now to users everywhere.

Related: Google Maps launches real-time transit updates for the TTC

Tracon: Square’s reverse proxy

Tracon is our reverse HTTP proxy powered by Netty. Several years ago, as we started to move to a microservice architecture, we realized that we needed a reverse proxy to coordinate the migration of APIs from our legacy monolith to our rapidly expanding set of microservices.

We chose to build Tracon on top of Netty in order to get efficient performance coupled with the ability to make safe and sophisticated customizations. We are also able to leverage a lot of shared Java code with the rest of our stack in order to provide rock-solid service discovery, configuration and lifecycle management, and much more!

Tracon was written using Netty 3 and has been in production for three years. Over its lifetime, the codebase has grown to 20,000 lines of code and tests. Thanks in large part to the Netty library, the core of this proxy application has proven so reliable that we’ve expanded its use into other applications. The same library powers our internal authenticating corporate proxy. Tracon’s integration with our internal dynamic service discovery system will soon power all service-to-service communication at Square. In addition to routing logic, we can capture a myriad of statistics about the traffic flowing into our datacenters.

Why upgrade to Netty 4 now?

Netty 4 was released three years ago. Compared to Netty 3, the threading and memory models have been completely revamped for improved performance. Perhaps more importantly, it also provides first class support for HTTP/2. Although we’ve been interested in migrating to this library for quite a while, we’ve delayed upgrading because it is a major upgrade that introduces some significant breaking changes.

Now that Netty 4 has been around for a while and Netty 3 has reached the end of its life, we felt that the time was ripe for an overhaul of this mission-critical piece of infrastructure. We want to allow our mobile clients to use HTTP/2 and are retooling our RPC infrastructure to use gRPC which will require our infrastructure to proxy HTTP/2. We knew this would be a multi-month effort and there would be bumps along the way. Now that the upgrade is complete, we wanted to share some of the issues we encountered and how we solved them.

Issues encountered

Single-threaded channels: this should be simple!

Unlike Netty 3, in Netty 4, outbound events happen on the same single thread as inbound events. This allowed us to simplify some of our outbound handlers by removing code that ensured thread safety. However, we also ran into an unexpected race condition because of this change.

Many of our tests run with an echo server, and we assert that the client receives exactly what it sent. In one of our tests involving chunked messages, we found that we would occasionally receive all but one chunk back. The missing chunk was never at the beginning of the message, but it varied from the middle to the end.

In Netty 3, all interactions with a pipeline were thread-safe. However, in Netty 4, all pipeline events must occur on the event loop. As a result, events that originate outside of the event loop are scheduled asynchronously by Netty.

In Tracon, we proxy traffic from an inbound server channel to a separate outbound channel. Since we pool our outbound connections, the outbound channels aren’t tied to the inbound event loop. Events from each event loop caused this proxy to try to write concurrently. This code was safe in Netty 3 since each write call would complete before returning. In Netty 4, we had to more carefully control what event loop could call write to prevent out of order writes.

When upgrading an application from Netty 3, carefully audit any code for events that might fire from outside the event loop: these events will now be scheduled asynchronously.

When is a channel really connected?

In Netty 3, the SslHandler “redefines” a channelConnected event to be gated on the completion of the TLS handshake instead of the TCP handshake on the socket. In Netty 4, the handler does not block the channelConnected event and instead fires a finer-grained user event: SslHandshakeCompletionEvent. Note that Netty 4 replaces channelConnected with channelActive.

For most applications, this would be an innocuous change, but Tracon uses mutually authenticated TLS to verify the identity of the services it is speaking to. When we first upgraded, we found that we lacked the expected SSLSession in the mutual authenticationchannelActive handler. The fix is simple: listen for the handshake completion event instead of assuming the TLS setup is complete on channelActive

@Override public void userEventTriggered(ChannelHandlerContext ctx, Object evt) throws
 if (evt.equals(SslHandshakeCompletionEvent.SUCCESS)) {
     Principal peerPrincipal = engine.getSession().getPeerPrincipal();
     // Validate the principal
     // ...
 }
 super.userEventTriggered(ctx, evt);

}

Recycled Buffers Leaking NIO Memory

In addition to our normal JVM monitoring, we added monitoring of the size and amount of NIO allocations by exporting the JMX bean java.nio:type=BufferPool,name=direct since we want to be able to understand and alert on the direct memory usage by the new pooled allocator.

In one cluster, we were able to observe an NIO memory leak using this data. Netty provides a leak detection framework to help catch errors in managing the buffer reference counts. We didn’t get any leak detection errors because this leak was not actually a reference count bug!

Netty 4 introduces a thread-local Recycler that serves as a general purpose object pool. By default, the recycler is eligible to retain up to 262k objects. ByteBufs are pooled by default if they are less than 64kb: that translates to a maximum of 17GB of NIO memory per buffer recycler.

Under normal conditions, it’s rare to allocate enough NIO buffers to matter. However, without adequate back-pressure, a single slow reader can balloon memory usage. Even after the buffered data for the slow reader is written, the recycler does not expire old objects: the NIO memory belonging to that thread will never be freed for use by another thread. We found the recyclers completely exhausted our NIO memory space.

We’ve notified the Netty project of these issues, and there are several upcoming fixes to provide saner defaults and limit the growth of objects:

• Allow to limit the maximum number of WeakOrderQueue instances per Thread
• Introduce allocation / pooling ratio in Recycler
• Port SendBufferPooled from netty 3.10 and use it if non pooled ByteBufAllocator is used.

We encourage all users of Netty to configure their recycler settings based on the available memory and number of threads and profiling of the application. The number of objects per recycler can be configured by setting -Dio.netty.recycler.maxCapacity and the maximum buffer size to pool is configured by -Dio.netty.threadLocalDirectBufferSize. It’s safe to completely disable the recycler by setting the -Dio.netty.recycler.maxCapacity to 0, and for our applications, we have not observed any performance advantage in using the recycler.

We made another small but very important change in response to this issue: we modified our global UncaughtExceptionHandler to terminate the process if it encounters an error since we can’t reasonably recover once we hit an OutOfMemoryError. This will help mitigate the effects of any potential leaks in the future.

class LoggingExceptionHandler implements Thread.UncaughtExceptionHandler {

 private static final Logger logger = Logger.getLogger(LoggingExceptionHandler.class);

 /** Registers this as the default handler. */
 static void registerAsDefault() {
   Thread.setDefaultUncaughtExceptionHandler(new LoggingExceptionHandler());
 }

 @Override public void uncaughtException(Thread t, Throwable e) {
   if (e instanceof Exception) {
     logger.error("Uncaught exception killed thread named '" + t.getName() + "'.", e);
   } else {
     logger.fatal("Uncaught error killed thread named '" + t.getName() + "'." + " Exiting now.", e);
     System.exit(1);
   }
 }
}

Limiting the recycler fixed the leak, but this also revealed how much memory a single slow reader could consume. This isn’t new to Netty 4, but we were able to easily add backpressure using the channelWritabilityChanged event. We simply add this handler whenever we bind two channels together and remove it when the channels are unlinked.

/**

* Observe the writability of the given inbound pipeline and set the {@link ChannelOption#AUTO_READ}
* of the other channel to match. This allows our proxy to signal to the other side of a proxy
* connection that a channel has a slow consumer and therefore should stop reading from the
* other side of the proxy until that consumer is ready.
*/

public class WritabilityHandler extends ChannelInboundHandlerAdapter {

 private final Channel otherChannel;

 public WritabilityHandler(Channel otherChannel) {
   this.otherChannel = otherChannel;
 }

 @Override public void channelWritabilityChanged(ChannelHandlerContext ctx) throws Exception {
   boolean writable = ctx.channel().isWritable();
   otherChannel.config().setOption(ChannelOption.AUTO_READ, writable);
   super.channelWritabilityChanged(ctx);
 }
}

The writability of a channel will go to not writable after the send buffer fills up to the high water mark, and it won’t be marked as writable again until it falls below the low water mark. By default, the high water mark is 64kb and the low water mark is 32kb. Depending on your traffic patterns, you may need to tune these values.

If a promise breaks, and there’s no listener, did you just build /dev/null as a service?

While debugging some test failures, we realized that some writes were failing silently. Outbound operations notify their futures of any failures, but if each write failure has shared failure handling, you can instead wire up a handler to cover all writes. We added a simple handler to log any failed writes:

@Singleton
@Sharable
public class PromiseFailureHandler extends ChannelOutboundHandlerAdapter {

 private final Logger logger = Logger.getLogger(PromiseFailureHandler.class);

 @Override public void write(ChannelHandlerContext ctx, Object msg, ChannelPromise promise)
     throws Exception {
   promise.addListener(future -> {
     if (!future.isSuccess()) {
       logger.info("Write on channel %s failed", promise.cause(), ctx.channel());
     }
   });

   super.write(ctx, msg, promise);
 }
}

HTTPCodec changes

Netty 4 has an improved HTTP codec with a better API for managing chunked message content. We were able to remove some of our custom chunk handling code, but we also found a few surprises along the way!

In Netty 4, every HTTP message is converted into a chunked message. This holds true even for zero-length messages. While it’s technically valid to have a 0 length chunked message, it’s definitely a bit silly! We installed object aggregators to convert these messages to non-chunked encoding. Netty only provides an aggregator for inbound pipelines: we added a custom aggregator for our outbound pipelines and will be looking to contribute this upstream for other Netty users.

There are a few nuances with the new codec model. Of note, LastHttpContent is also a HttpContent. This sounds obvious, but if you aren’t careful you can end up handling a message twice! Additionally, a FullHttpResponse is also an HttpResponse, an HttpContent, and a LastHttpContent. We found that we generally wanted to handle this as both an HttpResponse and a LastHttpContent, but we had to be careful to ensure that we didn’t forward the message through the pipeline twice.

Don’t do this

if (msg instanceof HttpResponse) {
  ...
}

if (msg instanceof HttpContent) {
  ...
}

if (msg instanceof LastHttpContent) {
  … // Duplicate handling! This was already handled above!
}

Another nuance we discovered in some test code: LastHttpContent may fire after the receiving side has already received the complete response if there is no body. In this case, the last content is serving as a sentinel, but the last bytes have already gone out on the wire!

Replacing the engine while the plane is in the air

In total, our change to migrate to Netty 4 touched 100+ files and 8k+ lines of code. Such a large change coupled with a new threading and memory model is bound to encounter some issues. Since 100% of our external traffic flows through this system, we needed a process to validate the safety of these changes.

Our large suite of unit and integration tests was invaluable in validating the initial implementation.

Once we established confidence in the tests, we began with a “dark deploy” where we rolled out the proxy in a disabled state. While it didn’t take any traffic, we were able to exercise a large amount of the new code by running health checks through the Netty pipeline to check the status of downstream services. We highly recommend this technique for safely rolling out any large change.

As we slowly rolled out the new code to production, we also relied on a wealth of metrics in order to compare the performance of the new code. Once we addressed all of the issues, we found that Netty 4 performance using the UnpooledByteBufAllocator is effectively identical to Netty 3. We’re looking forward to using the pooled allocator in the near future for even better performance.

Thanks

We’d like to thank everyone involved in the Netty project. We’d especially like to thank Norman Maurer / @normanmaurer for being so helpful and responsive!

References

• New and Noteworthy in Netty 4.0: http://netty.io/wiki/new-and-noteworthy-in-4.0.html

• Netty Best Practices a.k.a Faster == Better: http://normanmaurer.me/presentations/2014-facebook-eng-netty/slides.html

• Netty in Action: https://www.amazon.com/Netty-Action-Norman-Maurer/dp/1617291471/qid=1470353221

As anyone who writes or publishes can tell you, attaining a perfect proofread—ferreting out every typo, missing word, and so on—is staggeringly difficult. You can read over something six times, swear it’s perfect—and then show it to someone else who spots a typo instantly. Somehow, your brain gets lulled into blindness.

(When I write computer books, each book is read by four pairs of eyes: Mine, a technical editor’s, a copy editor’s, and a proofreader’s—and readers still find typos after publication. Grrrr!!)

If you don’t have the luxury of four beta readers—or even if you do—here’s a miraculous trick that will make “blind spot” typos pop out: Change the font.

That’s right. A different typeface in your word processor gives the text a different layout, with different line wraps, making it look fresh. The writing no longer looks like yours, making it easier to spot errors.

For the same reason, choosing an unfamiliar font is a great idea when you’re trying to edit or shorten your paper. You’re less attached to your writing, less used to its look, and more able to see something new as you read it.

Repurposed from June 2015

For more great tech tips, follow Yahoo Tech on Facebook right here!

See more of Pogue’s Basics on Yahoo Tech!

The popular group funding app Tilt has announced a new money transfer feature.

The app originally launched in 2012 and has since become the go-to place for groups to fund something they collectively care about — whether it be a charity, a birthday gift or even a group holiday.

Now, with the Request and Send feature, users can send secure, automatic payments on iOS and Android. A statement sent to MobileSyrup describes this feature as being perfect for splitting dinner bills or sharing other small costs.

“At Tilt we see mobile payments changing the way groups and communities organize and create experiences together,” said James Beshara, Tilt CEO and co-founder in a statement. “It should be easier to send and exchange money through your phone and in a couple of years I anticipate we won’t remember doing it any other way.”

The app is extremely popular with students and millennials, having experiences 41 percent month over month growth on college campuses since launching. Originally founded by James Beshara and Khaled Hussein, the app is now available in nine countries globally.

Users will be able to send or request money from friends in their own country. The feature is available internationally as long as users have a debit or credit card. Furthermore, users can request money from an entire group.

This feature will be free, as is the app itself, and will be available in the United States, the United Kingdom and Canada.

Related reading: Vending machines across Canada now accept Apple Pay

Dan Colman, Open Culture, Aug 12, 2016

Compare what we say about information today with what Virginia Woolf says about words in this the only surviving recording of her voice: "(words) hate being useful; they hate making money; they hate being lectured about in public. In short, they hate anything that stamps them with one meaning or confines them to one attitude, for it is in their nature to change." What a world we live in, where we can hear the living words of great people now long since passed on. I am inclined to agree with Woolf here; I have never thought of writing as a 'craft'. But I don't think of it as an art either. It is something else.

Onni have completed their artists live/work project on Great Northern Way called Canvas. Last summer they submitted a four building development application for a site close by, part of the University Campus rezoning.

The initial proposal was for four buildings – two 13 and 15 storey live-work buildings with retail at grade and a total of 220 units, a 15 storey hotel with 199 rooms and a 7 storey office building.  The Urban Design Panel didn’t support the design (right), so now there’s a revised design (the model shown above). The design rationale offered by the architects, IBI, proposes to use colours from a Rubik’s cube and references digital art like Douglas Coupland’s digital orca (at the Convention Centre).

Images courtesy of JD Sound

Several companies have tried to make the DJ experience highly portable and affordable, and to varying degrees have they been succesful—products like the Pyle Pro bluetooth DJ mixer and the Reloop MIXTOUR DJ controller attest to this. But the company JD Sound, maker of Monster audio equipment, did a major rethink on portable mixing with its GoDJ, released back in 2013.

Recently, however, JD Sound has been crowdfunding on Indiegogo to develop its next generation DJ tool, the GoDJ Plus. Basically, it takes the design of its predecessor and adds more hardware real estate and controls. Amongst other features, the GoDJ Plus has built-in speakers, internal memory, launch pads and a more robust battery.

Aaron Koh, Head of Sales for GoDJ and GoDJ Plus, tells The Creators Project that, while they had indeed succeeded in developing the original GoDJ as a pocket-sized DJ mixer, the GoDJ Plus is being designed based on customers’ feedback.

“Our company has a technology related to audio DSP [digital signal processor] and embedded SW [software] development,” Koh says. “Based on these software technologies we started to develop portable DJ equipment, [but] at that time there was no hardware technology development for audio devices and DJ equipment.”

“[With GoDJ] there was a lot of trial and error,” he adds, particularly since they were developing a product that would enter a market dominated by established players like Pioneer and Native Instruments. “But we got the hardware development capacity for GoDJ Plus while producing GoDJ.”

The main attraction to GoDJ Plus is certainly its portability. About the size of a small Apple MacBook Air, it can easily slip into a backpack for transport. Now, if someone were to be DJing a low-key party, they could bring it without a laptop because of its internal memory. But GoDJ Plus also has a USB port in a user wants to connect a smartphone or other mobile device storing music files.

Though designed with powerful built-in speakers, GoDJ Plus has a 3.5mm stereo line-out to connect to external speakers via RCA cables. It’s a setup that isn’t going to cut the sonic muster for established DJs, but amateurs could definitely make use of the line out for their external speakers.  

Reinforcing the idea that the GoDJ Plus is a performance tool, Monster has given the device a bunch of effects to tweak songs. In addition to equalization (EQ), pitch bend and BPM Analyzer functions, users can also create loops and simulate vinyl scratching.  

What else sets GoDJ Plus apart from other portable DJ gear is its sample pads. These 16 performance-ready triggers feature soft-touch rubber that can play up to 136 effects, somewhat like the old school Akai MPC samplers, and get illuminated in various LED colors. There are also touchscreen pads that have similar functions.

Koh says that Monster sees GoDJ Plus’s primary users being amateurs looking for general DJ equipment. They also envision professionals making use of the GoDJ plus as another piece of equipment for portability. Koh says the mixer will be ready to go in December of 2016.

Click here for more info on the GoDJ Plus.

Related:

Chop, Mix, And Stir Beats As If You're Cooking With Beatoven

A Bird Skull Turntable Playing Bird Songs Is Horrifying

This Turntable Is Made of 2,405 Legos

This is part two of an essay on René Girard’s influence on Peter Thiel. Part one ran last week and you can read it here. 

In my previous post, I examined social theorist René Girard’s influence on tech investor Peter Thiel. Previous observers have picked up on Thiel’s remark that Girard’s mimetic theory helped him identify the promise of social media, but they have left out a crucial dimension of Girard’s thought: mimetic violence, also a central preoccupation for Thiel. In what follows, I will make the case that Thiel invested in and promoted Facebook not simply because Girard’s theories led him to foresee the future profitability of the company, but because he saw social media as a mechanism for the containment and channeling of mimetic violence in the face of an ineffectual state. Facebook, then, was not simply a prescient and well-rewarded investment for Thiel, but a political act closely connected to other well-known actions, from founding the national security-oriented startup Palantir Technologies to suing Gawker and supporting Trump.

According to Girard’s mimetic theory, humans choose objects of desire through contagious imitation: we desire things because others desire them, and we model our desires on others’ desires. As a result, desires converge on the same objects, and selves become rivals and doubles, struggling for the same sense of full being, which each subject suspects the other of possessing. The resulting conflicts cascade across societies because the mimetic structure of behavior also means that violence replicates itself rapidly. The entire community becomes mired in reciprocal aggression. The ancient solution to such a “mimetic crisis,” according to Girard, was sacrifice, which channeled collective violence into the murder of scapegoats, thus purging it, temporarily, from the community. While these cathartic acts of mob violence initially occurred spontaneously, as Girard argues in his book Violence and the Sacred, they later became codified in ritual, which reenacts collective violence in a controlled manner, and in myth, which recounts it in veiled forms. Religion, the sacred, and the state, for Girard, emerged out of this violent purgation of violence from the community. However, he argues, the modern era is characterized by a discrediting of the scapegoat mechanism, and therefore of sacrificial ritual, which creates a perennial problem of how to contain violence.

For Girard, to wield power is to control the mechanisms by which the mimetic violence that threatens the social order is contained, channeled, and expelled. Girard’s politics, as mentioned above, are ambiguous: he criticizes conservatism for wishing to preserve the sacrificial logic of ancient theocracies, and liberalism for believing that by dissolving religion it can eradicate the potential for violence. However, Girard’s religious commitment to a somewhat heterodox Christianity is clear, and controversial: he regards the non-violence of the Jesus of the gospel texts as a powerful exception to the violence that has been in the DNA of all human cultures, and an antidote to mimetic conflict. It is unclear to what degree Girard regards this conviction as reconcilable with an acceptance of modern secular governance, founded as it is by the state monopoly on violence. Peter Thiel, for his part, has stated that he is a Christian, but his large contributions to hawkish politicians suggest he does not share Girard’s pacifist interpretation of the Bible. His sympathetic account, in “The Straussian Moment,” of the ideas of Carl Schmitt offers further evidence of his ambivalence about Girard’s pacifism. For Schmitt, a society cannot achieve any meaningful cohesion without an “enemy” to define itself against. Schmitt and Girard both see violence as fundamental to the social order, but they draw opposite conclusions from that finding: Schmitt wants to resuscitate the scapegoat in order to maintain the state’s cohesion, while Girard wants (somehow) to put a final end to scapegoating and sacrifice. In his 2004 essay, Thiel seems torn between Girard’s pacifism and Schmitt’s bellicosity.

The tensions between Girard’s and Thiel’s worldviews run deeper, as a brief overview of Thiel’s politics reveals. As a libertarian, he has donated to both Ron and Rand Paul, and he has also supported Tea Party stalwarts including Ted Cruz. George Packer, in a 2011 profile of Thiel, reports that his chief influence in his youth was Ayn Rand, and that in political arguments in college, Thiel fondly quoted Margaret Thatcher’s claim that “there is no such thing as society.” As George Packer notes in his New Yorker profile of Thiel, few claims could be more alien to his mentor, Girard, who insists on the primacy of the collective over the individual and dedicated several books to debunking modern myths of individualism. Indeed, Thiel’s libertarian vision of the heroic entrepreneur standing apart from society closely resembles what Girard derided in his work as “the romantic lie”: the fantasy of the autonomous, self-directed individual that emerged out of European Romanticism. Girard went so far as to suggest replacing the term “individual” with the neologism “interdividual,” which better conveys the way that identity is always constructed in relation to others.

In a seemingly Ayn-Randian vein, Thiel likes to call tech entrepreneurs “founders,” and in lectures and seminars has compared startups to monarchies. He envisions “founders” in mythical terms, citing Romulus, Remus, Oedipus, and Cain, figures discussed at length in Girard’s analyses of myth. Thiel’s pro-monarchist statements have been parsed in the media (and linked to his support for the would-be autocrat Trump), but without noting that for a self-proclaimed devotee of René Girard to advocate for monarchy carries striking ambiguities. According to Girard’s counterintuitive analysis, monarchical power is the obverse side of scapegoating. Monarchy, he hypothesizes, has its origins in the role of the sacrificed scapegoat as the unifier and redeemer of the community; it developed when scapegoats managed to delay their own ritual murder and secured a fixed place at the center of a society. A king is a living scapegoat who has been deified, and can become a scapegoat again, as Girard illustrates in his reading of the myth of Oedipus (Oedipus begins as an outsider, goes on to become king, and is ultimately punished for the community’s ills, channeling collective violence toward himself, and returned to his outsider status).

If Thiel, as he reveals in a 2012 seminar, views the “founder” as both potentially a “God” and a “victim,” then he regards the broad societal influence wielded by the tech élite as a source of risk: a king can always become a scapegoat. On these grounds, it seems reasonable to conclude that Thiel’s animus against Gawker, which he has repeatedly accused of “bullying” him and other Silicon Valley power players, is closely connected to his core concern with scapegoating, derived from his longstanding engagement with Girard’s ideas. Thiel’s preoccupation with the risks faced by the “founder” also has a close connection to his hostility toward democratic politics, which he regards as placing power in the hands of a mob that will victimize those it chooses to play the role of scapegoat. Or as he states: “the 99% vs. the 1% is the modern articulation of [the] classic scapegoating mechanism: it is all minus one versus the one.”

No serious reader of Girard can regard a simple return to monarchical rule – which Thiel has sometimes seemed to favor – as plausible: the ritual underpinnings that were necessary to maintain its credibility, Girard insists, have been irreversibly demystified. Perhaps on the basis of this recognition, and even while hedging his bets through his involvement in Republican politics, Thiel has focused instead on the new possibilities offered by network technologies for the exercise of power. A Thiel text published on the website of the libertarian Cato Institute is suggestive in this context: “In the 2000s, companies like Facebook create . . . new ways to form communities not bounded by historical nation-states. By starting a new Internet business, an entrepreneur may create a new world. The hope of the Internet is that these new worlds will impact and force change on the existing social and political order.” Although Thiel does not say so here, from a Girardian point of view, a “founder” of a community does so by bringing mimetic violence under institutional control – precisely what the application of mimetic theory to Facebook would suggest that it does.

As we saw previously, Thiel was ruminating on Strauss, Schmitt, and Girard in the summer of 2004, but also on the future of social media platforms, which he found himself in a position to help shape. It is worth adding that around the same time, Thiel was involved in the founding of Palantir Technologies, a data analysis company whose main clients are the US Intelligence Community and Department of Defense – a company explicitly founded, according to Thiel, to forestall acts of destabilizing violence like 9/11. One may speculate that Thiel understood Facebook to serve a parallel function. According to his own account, he identified the new platform as a powerful conduit of mimetic desire. In Girard’s account, the original conduits of mimetic desire were religions, which channeled socially destructive, “profane” violence into sanctioned forms of socially consolidating violence. If the sacrificial and juridical superstructures designed to contain violence had reached their limits, Thiel seemed to understand social media as a new, technological means to achieving comparable ends.

If we take Girard’s mimetic theory seriously, the consequences for the way we think about social media are potentially profound. For one, it would lead us to conclude that social media platforms, by channeling mimetic desire, also serve as conduits of the violence that goes along with it. That, in turn, would suggest that abuse, harassment, and bullying – the various forms of scapegoating that have become depressing constants of online behavior – are features, not bugs: the platforms’ basic social architecture, by concentrating mimetic behavior, also stokes the tendencies toward envy, rivalry, and hatred of the Other that feed online violence. From Thiel’s perspective, we may speculate, this means that those who operate those platforms are in the position to harness and manipulate the most powerful and potentially destabilizing forces in human social life – and most remarkably, to derive profits from them. For someone overtly concerned about the threat posed by such forces to those in positions of power, a crucial advantage would seem to lie in the possibility of deflecting violence away from the prominent figures who are the most obvious potential targets of popular ressentiment, and into internecine conflict with other users.

Girard’s mimetic theory can help illuminate what social media does, and why it has become so central to our lives so quickly – yet it can lead to insights at odds with those drawn by Thiel. From Thiel’s perspective, it would seem, mimetic theory provides him and those of his class with an account of how and to what ends power can be exercised through technology. Thiel has made this clear enough: mimetic violence threatens the powerful; it needs to be contained for their – his – protection; as quasi-monarchs, “founders” run the risk of becoming scapegoats; the solution is to use technologies to control violence – this is explicit in the case of Palantir, implicit in the case of Facebook. But there is another way of reading social media through Girard. By revealing that the management of desire confers power, mimetic theory can help us make sense of how platforms administer our desires, and to whose benefit. For Girard, modernity is the prolonged demystification of the basis of power in violence. Unveiling the ways that power operates through social media can continue that process.

Geoff Shullenberger teaches in the Expository Writing Program at New York University, and sometimes tweets at @daily_barbarian.

Headline Pic Via: Source

Ads are intrusive, frustrating and sometimes, even invasive, but what many people fail to realize, is in most cases, they also provide funding for many of the free apps and services people utilize on a daily basis.

In a recent blog post, Facebook says it now has the ability to “begin showing ads on Facebook desktop for people who currently use ad blocking software.” The social media platform, however, unfortunately doesn’t detail exactly how it plans to do this, though it says it has not paid ad blocking companies to be whitelisted, a somewhat shady approach some of the service’s rivals have adopted.

Facebook also says it has plans to release a new ad preferences tool designed to make it easier to see how users are being targeted with advertisements. You’ll be able to specify certain interests and opt out of the ones Facebook has incorrectly associated with your profile. More importantly, it will also be possible to view what advertisers have your profile details on their customer list.

When scrolling through Facebook’s News Feed users are also able to give either a thumbs up or a thumbs down, indicating how relevant an ad is.

“These improvements are designed to give people even more control over how their data informs the ads they see,” says Andrew Bosworth, vice-president for ads and business platform at Facebook, in the blog post.

While this shift could frustrate some users, given Facebook makes the majority of its revenue from ads, this is a smart business move by the social network. It will be interesting, however, to see how many users it loses as a result of this change.

Google Now is undoubtedly intuitive when it comes to tracking user interests, but what it currently lacks is an easy way for users to request information on specific subjects. That may be rectified in the near future, according to leaked screenshots that show a feature that does just that called ‘Explore Interests.’

The screenshots, published by Android Police, show a Google Now card that prompts users to get updates on their interests. Inside that feature, users can choose from categories like TV, sports and people. Within those categories are more niche categories and specific cards. Cards are also displayed along the top by popularity in the user’s area — shown as an example in the screenshot is the ‘People’ section, with Donald Trump, Hilary Clinton and Bernie Sanders.

Currently, Google Now shows users news based on data collected from a user’s history, like search history and location. Adjustments can be made using on/off toggles in settings, or tapping on the catered info to mark disinterest in that news or source.

Unfortunately for those interested in the feature, a Google representative told TechCrunch that Explore Interests is currently an experiment the company is testing, so rollout may not take place for a while, if ever — though today’s internet buzz will likely confirm to the company just how much interest there is in such an option.

Image credit: Android Police 

Related: Google trolls 16GB iPhone users with new Photos ad

Chris Noessel has written a splendid thing over on Medium about finding and looking after speakers, if you're a conference organiser.

I have one little extra thought to add.

1. Chris says this about getting gifts for speakers:

"Small tokens of appreciation are not needed, but always endearing. They don’t need to be expensive, but something local like art, food, or non-gimmicky technology is best. It should be something they can use, but also something they might pass on to their family/sweetheart as a gift for having to be away. With that in mind, avoid just putting a logo on schwag, as that just feels like advertising, rather than a token of thanks."

All true. One other thing I'd encourage you to think about - your speaker may be about to get on a plane, they might be trying to avoid checking anything in. Don't get them, for instance, a massive bottle of champagne or a huge metal fruit bowl.

I don’t normally post about politics (I’m not particularly savvy about polling, which is where data science has had the largest impact on politics). But this weekend I saw a hypothesis about Donald Trump’s twitter account that simply begged to be investigated with data:

Every non-hyperbolic tweet is from iPhone (his staff).

Every hyperbolic tweet is from Android (from him). pic.twitter.com/GWr6D8h5ed

— Todd Vaziri (@tvaziri) August 6, 2016

When Trump wishes the Olympic team good luck, he’s tweeting from his iPhone. When he’s insulting a rival, he’s usually tweeting from an Android. Is this an artifact showing which tweets are Trump’s own and which are by some handler?

Others have explored Trump’s timeline and noticed this tends to hold up- and Trump himself does indeed tweet from a Samsung Galaxy. But how could we examine it quantitatively? I’ve been writing about text mining and sentiment analysis recently, particularly during my development of the tidytext R package with Julia Silge, and this is a great opportunity to apply it again.

My analysis, shown below, concludes that the Android and iPhone tweets are clearly from different people, posting during different times of day and using hashtags, links, and retweets in distinct ways. What’s more, we can see that the Android tweets are angrier and more negative, while the iPhone tweets tend to be benign announcements and pictures. Overall I’d agree with @tvaziri’s analysis: this lets us tell the difference between the campaign’s tweets (iPhone) and Trump’s own (Android).

The dataset

First we’ll retrieve the content of Donald Trump’s timeline using the userTimeline function in the twitteR package:¹

library(dplyr)
library(purrr)
library(twitteR)

# You'd need to set global options with an authenticated app
setup_twitter_oauth(getOption("twitter_consumer_key"),
                    getOption("twitter_consumer_secret"),
                    getOption("twitter_access_token"),
                    getOption("twitter_access_token_secret"))

# We can request only 3200 tweets at a time; it will return fewer
# depending on the API
trump_tweets <- userTimeline("realDonaldTrump", n = 3200)
trump_tweets_df <- tbl_df(map_df(trump_tweets, as.data.frame))

# if you want to follow along without setting up Twitter authentication,
# just use my dataset:
load(url("http://varianceexplained.org/files/trump_tweets_df.rda"))

We clean this data a bit, extracting the source application. (We’re looking only at the iPhone and Android tweets- a much smaller number are from the web client or iPad).

library(tidyr)

tweets <- trump_tweets_df %>%
  select(id, statusSource, text, created) %>%
  extract(statusSource, "source", "Twitter for (.*?)<") %>%
  filter(source %in% c("iPhone", "Android"))

Overall, this includes 628 tweets from iPhone, and 762 tweets from Android.

One consideration is what time of day the tweets occur, which we’d expect to be a “signature” of their user. Here we can certainly spot a difference:

library(lubridate)
library(scales)

tweets %>%
  count(source, hour = hour(with_tz(created, "EST"))) %>%
  mutate(percent = n / sum(n)) %>%
  ggplot(aes(hour, percent, color = source)) +
  geom_line() +
  scale_y_continuous(labels = percent_format()) +
  labs(x = "Hour of day (EST)",
       y = "% of tweets",
       color = "")

Trump on the Android does a lot more tweeting in the morning, while the campaign posts from the iPhone more in the afternoon and early evening.

Another place we can spot a difference is in Trump’s anachronistic behavior of “manually retweeting” people by copy-pasting their tweets, then surrounding them with quotation marks:

"@trumplican2016: @realDonaldTrump @DavidWohl stay the course mr trump your message is resonating with the PEOPLE"

— Donald J. Trump (@realDonaldTrump) July 28, 2016

Almost all of these quoted tweets are posted from the Android:

In the remaining by-word analyses in this text, I’ll filter these quoted tweets out (since they contain text from followers that may not be representative of Trump’s own tweets).

Somewhere else we can see a difference involves sharing links or pictures in tweets.

tweet_picture_counts <- tweets %>%
  filter(!str_detect(text, '^"')) %>%
  count(source,
        picture = ifelse(str_detect(text, "t.co"),
                         "Picture/link", "No picture/link"))

ggplot(tweet_picture_counts, aes(source, n, fill = picture)) +
  geom_bar(stat = "identity", position = "dodge") +
  labs(x = "", y = "Number of tweets", fill = "")

It turns out tweets from the iPhone were 38 times as likely to contain either a picture or a link. This also makes sense with our narrative: the iPhone (presumably run by the campaign) tends to write “announcement” tweets about events, like this:

Thank you Windham, New Hampshire! #TrumpPence16 #MAGA pic.twitter.com/ZL4Q01Q49s

— Donald J. Trump (@realDonaldTrump) August 7, 2016

While Android (Trump himself) tends to write picture-less tweets like:

The media is going crazy. They totally distort so many things on purpose. Crimea, nuclear, "the baby" and so much more. Very dishonest!

— Donald J. Trump (@realDonaldTrump) August 7, 2016

Comparison of words

Now that we’re sure there’s a difference between these two accounts, what can we say about the difference in the content? We’ll use the tidytext package that Julia Silge and I developed.

We start by dividing into individual words using the unnest_tokens function (see this vignette for more), and removing some common “stopwords”²:

library(tidytext)

reg <- "([^A-Za-z\\d#@']|'(?![A-Za-z\\d#@]))"
tweet_words <- tweets %>%
  filter(!str_detect(text, '^"')) %>%
  mutate(text = str_replace_all(text, "https://t.co/[A-Za-z\\d]+|&amp;", "")) %>%
  unnest_tokens(word, text, token = "regex", pattern = reg) %>%
  filter(!word %in% stop_words$word,
         str_detect(word, "[a-z]"))

tweet_words

## # A tibble: 8,753 x 4
##                    id source             created                   word
##                 <chr>  <chr>              <time>                  <chr>
## 1  676494179216805888 iPhone 2015-12-14 20:09:15                 record
## 2  676494179216805888 iPhone 2015-12-14 20:09:15                 health
## 3  676494179216805888 iPhone 2015-12-14 20:09:15 #makeamericagreatagain
## 4  676494179216805888 iPhone 2015-12-14 20:09:15             #trump2016
## 5  676509769562251264 iPhone 2015-12-14 21:11:12               accolade
## 6  676509769562251264 iPhone 2015-12-14 21:11:12             @trumpgolf
## 7  676509769562251264 iPhone 2015-12-14 21:11:12                 highly
## 8  676509769562251264 iPhone 2015-12-14 21:11:12              respected
## 9  676509769562251264 iPhone 2015-12-14 21:11:12                   golf
## 10 676509769562251264 iPhone 2015-12-14 21:11:12                odyssey
## # ... with 8,743 more rows

What were the most common words in Trump’s tweets overall?

These should look familiar for anyone who has seen the feed. Now let’s consider which words are most common from the Android relative to the iPhone, and vice versa. We’ll use the simple measure of log odds ratio, calculated for each word as:³

android_iphone_ratios <- tweet_words %>%
  count(word, source) %>%
  filter(sum(n) >= 5) %>%
  spread(source, n, fill = 0) %>%
  ungroup() %>%
  mutate_each(funs((. + 1) / sum(. + 1)), -word) %>%
  mutate(logratio = log2(Android / iPhone)) %>%
  arrange(desc(logratio))

Which are the words most likely to be from Android and most likely from iPhone?

A few observations:

• Most hashtags come from the iPhone. Indeed, almost no tweets from Trump’s Android contained hashtags, with some rare exceptions like this one. (This is true only because we filtered out the quoted “retweets”, as Trump does sometimes quote tweets like this that contain hashtags).

• Words like “join” and “tomorrow”, and times like “7pm”, also came only from the iPhone. The iPhone is clearly responsible for event announcements like this one (“Join me in Houston, Texas tomorrow night at 7pm!”)

• A lot of “emotionally charged” words, like “badly”, “crazy”, “weak”, and “dumb”, were overwhelmingly more common on Android. This supports the original hypothesis that this is the “angrier” or more hyperbolic account.

Sentiment analysis: Trump’s tweets are much more negative than his campaign’s

Since we’ve observed a difference in sentiment between the Android and iPhone tweets, let’s try quantifying it. We’ll work with the NRC Word-Emotion Association lexicon, available from the tidytext package, which associates words with 10 sentiments: positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, and trust.

nrc <- sentiments %>%
  filter(lexicon == "nrc") %>%
  dplyr::select(word, sentiment)

nrc

## # A tibble: 13,901 x 2
##           word sentiment
##          <chr>     <chr>
## 1       abacus     trust
## 2      abandon      fear
## 3      abandon  negative
## 4      abandon   sadness
## 5    abandoned     anger
## 6    abandoned      fear
## 7    abandoned  negative
## 8    abandoned   sadness
## 9  abandonment     anger
## 10 abandonment      fear
## # ... with 13,891 more rows

To measure the sentiment of the Android and iPhone tweets, we can count the number of words in each category:

sources <- tweet_words %>%
  group_by(source) %>%
  mutate(total_words = n()) %>%
  ungroup() %>%
  distinct(id, source, total_words)

by_source_sentiment <- tweet_words %>%
  inner_join(nrc, by = "word") %>%
  count(sentiment, id) %>%
  ungroup() %>%
  complete(sentiment, id, fill = list(n = 0)) %>%
  inner_join(sources) %>%
  group_by(source, sentiment, total_words) %>%
  summarize(words = sum(n)) %>%
  ungroup()

head(by_source_sentiment)

## # A tibble: 6 x 4
##    source    sentiment total_words words
##     <chr>        <chr>       <int> <dbl>
## 1 Android        anger        4901   321
## 2 Android anticipation        4901   256
## 3 Android      disgust        4901   207
## 4 Android         fear        4901   268
## 5 Android          joy        4901   199
## 6 Android     negative        4901   560

(For example, we see that 321 of the 4901 words in the Android tweets were associated with “anger”). We then want to measure how much more likely the Android account is to use an emotionally-charged term relative to the iPhone account. Since this is count data, we can use a Poisson test to measure the difference:

library(broom)

sentiment_differences <- by_source_sentiment %>%
  group_by(sentiment) %>%
  do(tidy(poisson.test(.$words, .$total_words)))

sentiment_differences

## Source: local data frame [10 x 9]
## Groups: sentiment [10]
## 
##       sentiment estimate statistic      p.value parameter  conf.low
##           (chr)    (dbl)     (dbl)        (dbl)     (dbl)     (dbl)
## 1         anger 1.492863       321 2.193242e-05  274.3619 1.2353162
## 2  anticipation 1.169804       256 1.191668e-01  239.6467 0.9604950
## 3       disgust 1.677259       207 1.777434e-05  170.2164 1.3116238
## 4          fear 1.560280       268 1.886129e-05  225.6487 1.2640494
## 5           joy 1.002605       199 1.000000e+00  198.7724 0.8089357
## 6      negative 1.692841       560 7.094486e-13  459.1363 1.4586926
## 7      positive 1.058760       555 3.820571e-01  541.4449 0.9303732
## 8       sadness 1.620044       303 1.150493e-06  251.9650 1.3260252
## 9      surprise 1.167925       159 2.174483e-01  148.9393 0.9083517
## 10        trust 1.128482       369 1.471929e-01  350.5114 0.9597478
## Variables not shown: conf.high (dbl), method (fctr), alternative (fctr)

And we can visualize it with a 95% confidence interval:

Thus, Trump’s Android account uses about 40-80% more words related to disgust, sadness, fear, anger, and other “negative” sentiments than the iPhone account does. (The positive emotions weren’t different to a statistically significant extent).

We’re especially interested in which words drove this different in sentiment. Let’s consider the words with the largest changes within each category:

This confirms that lots of words annotated as negative sentiments (with a few exceptions like “crime” and “terrorist”) are more common in Trump’s Android tweets than the campaign’s iPhone tweets.

Conclusion: the ghost in the political machine

I was fascinated by the recent New Yorker article about Tony Schwartz, Trump’s ghostwriter for The Art of the Deal. Of particular interest was how Schwartz imitated Trump’s voice and philosophy:

In his journal, Schwartz describes the process of trying to make Trump’s voice palatable in the book. It was kind of “a trick,” he writes, to mimic Trump’s blunt, staccato, no-apologies delivery while making him seem almost boyishly appealing…. Looking back at the text now, Schwartz says, “I created a character far more winning than Trump actually is.”

Like any journalism, data journalism is ultimately about human interest, and there’s one human I’m interested in: who is writing these iPhone tweets?

The majority of the tweets from the iPhone are fairly benign declarations. But consider cases like these, both posted from an iPhone:

Like the worthless @NYDailyNews, looks like @politico will be going out of business. Bad reporting- no money, no cred!

— Donald J. Trump (@realDonaldTrump) February 10, 2016

Failing @NYTimes will always take a good story about me and make it bad. Every article is unfair and biased. Very sad!

— Donald J. Trump (@realDonaldTrump) May 20, 2016

These tweets certainly sound like the Trump we all know. Maybe our above analysis isn’t complete: maybe Trump has sometimes, however rarely, tweeted from an iPhone (perhaps dictating, or just using it when his own battery ran out). But what if our hypothesis is right, and these weren’t authored by the candidate- just someone trying their best to sound like him?

Or what about tweets like this (also iPhone), which defend Trump’s slogan- but doesn’t really sound like something he’d write?

Our country does not feel 'great already' to the millions of wonderful people living in poverty, violence and despair.

— Donald J. Trump (@realDonaldTrump) July 28, 2016

A lot has been written about Trump’s mental state. But I’d really rather get inside the head of this anonymous staffer, whose job is to imitate Trump’s unique cadence (“Very sad!”), or to put a positive spin on it, to millions of followers. Are they a true believer, or just a cog in a political machine, mixing whatever mainstream appeal they can into the @realDonaldTrump concoction? Like Tony Schwartz, will they one day regret their involvement?

I was with one of my CEOs this morning. As we walked through the highs and lows of his business I made a suggestion that I want to pass on.

Nothing’s ever perfect in a startup, or life for that matter. Perfection is an illusion. However, on the startup journey the bulk of value gets created once everything starts to work.

The way to get to that promised land of momentum is through thousands of little things. Decisions and improvements, big and small, that you and your team make every day.

Most startups burn money. As a result, time is not on our side. Each day and week matter as we figure out how to make our companies work.

With all that context in mind, here’s my suggestion:

As leaders, it’s easy to get caught up in all the activity that’s going on. We see all that activity and are happy that things are moving forward. But I guarantee you, no matter how much progress you’re making and how hard everyone is working, you are making compromises. You’re settling.

Maybe you have a good sales leader, but not a great one. Maybe you know you have a conversion issue, but you keep allowing that to go on without diagnosis and a plan. The list of examples is endless.

I recommend that CEOs take some time each week to reflect on the business and ask themselves ‘where am I settling for good instead of pushing for great‘?

Even in my small advisory firm I do this weekly. I don’t allow meetings after 4pm Fridays. I take that time to revisit the whole week. I look at where I have settled. I use that to learn, grow and accelerate.

If you do this each and every week, mobilize your insights and push for improvements, you will be amazed at how much your entire company will level up.

The post Driving company performance: What are you settling for? appeared first on StartupCFO : Mark MacLeod.

Samsung unveiled the Galaxy Note 7 last week and stated the phone will be available in Canada on August 19th.

The 5.7-inch Marshmallow-powered Android will be launch with most Canadians carriers, including Bell, Telus, Rogers, Wind, Eastlink, Videotron, Koodo, for $1049.99 without a term and as low as $0 on contract.

Pre-orders are currently live and most Canadian carriers are offering bonuses tied to the purchase of a Note 7, which likely played a role in the phone reportedly pushing impressive pre-order numbers.

In an interview with MobileSyrup, Samsung Canada’s chief media officer Mark Childs stated, “pre-orders are outstanding,” specifically mentioning that there is “significant demand” for the Blue Coral iteration of the Note 7 in Canada. The phone is also available in Silver Titanium and Black Onyx.

“The overwhelming response has been positive in terms of reaction to the device by everybody from a review perspective, but also from Canadians. We are already seeing a huge response in the pre-orders that went live just after Unpacked and certainly surpassing our expectations as we head into the official launch next Friday,” continued Childs.

Related reading: Galaxy Note 7 runs the Snapdragon 820 in Canada

Piston Head II installation view, 2016. All photos courtesy of the artists and VENUS

Walking into VENUS, the year-old Los Angeles outpost of NY’s Venus Over Manhattan, you’ll probably feel like you’re at an auto trade show rather than an art gallery. That’s because the 14,500 square foot warehouse space has been filled with Alfa Romeos, Mustangs, and Harley Davidson motorcycles for an ongoing exhibition titled Piston Head II. 

But these aren’t your average sports cars and tough-guy motorcycles; they are a Land Rover emblazoned with Keith Haring illustrations, a 1970 Dodge Challenger painted by Richard Prince, Sterling Ruby's dilapidated 40-foot bus equipped with light fixtures and faded graffiti, and 12 more vehicles-turned-artworks by some of the biggest names in contemporary art history.

Untitled (Land Rover), Keith Haring, 1983

Piston Head II is a new iteration of an exhibition Venus Over Manhattan put on in 2013. Hosted at Art Basel Miami, the original Piston Head included cars and motorcycles by Tom Sachs, Franz West, and Damien Hirst, among others. “Most of my group show concepts I see as movies and not simply group shows,” VENUS founder Adam Lindemann tells The Creators Project. “The concept is powerful enough that we can produce several iterations and they are like sequels—the same story but different—and I think we can also improve the show in time.”

Untitled (Sow the Wind, Reap the Whirlwind), Lawrence Weiner, 2015

The automobile is no longer the status symbol it once was. In some ways, Piston Head II and its trade show-esque qualities can be seen as a memoriam to car culture. Lindemann says, “Yes, the exhibition deals with the car as a lasting symbol of power, but also an aging hulk of overweight metal that is totally pointless. In my view, we should all get around in small two-cylinder lightweight cars—they are cheap and efficient.”

Alfa Romeo 4C Painted with Hokusai’s The Great Wave of Kanagawa, Garage Italia Customs

He adds, “We are presenting the works as if at an auto show of consumer products, while in fact these objects are works of art, devoid of function. It adds a whole other eccentric element to the concept.”

BUS, Sterling Ruby, 2010

The Odyssey, Richard Prince, 2016

Flathead, Olivier Mosset, 1954

Piston Head II will be on view at VENUS in Los Angeles until September 10, 2016.

Related:

American Car Culture Gets a Roaring Group Show

The Ecstasy of Exploding Expensive Racecars

Toyota Built a Beautiful Wooden Car Without Using Nails or Screws