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violetsystems · 5 years ago

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#personal

If there were ever a silver lining to anything these days, it’s that I am also qualified to work at IKEA. In Shanghai. You guessed it. Cybersecurity. I do like to rearrange my crappy furniture every once in a week. But between rotating the kitchen table a precise ninety degrees for more elbow space, I’ve been feeding the algorithms like hungry plants. Sometimes they are monstrous. Someone on Amazon reviews had targeted me over a skin care product. You had to click a layer deep. A metallurgist from New York who was a professor at a major university. His reviews of fiction were endless of Grant and the civil war. You could put two and two together. And a week or so later the algorithms did. They suggested in an email blast every fucking work of importance about said Grant and the confederacy. Needless to say, I’m not really a fan of such perspectives. But awash in all this is my own personal data which governments refer to as PII henceforth my shitty Magnum jokes. We here in America love this thing you call freedom. But most of our data is not free. In fact, it is harvested, manipulated and spat back at us in a condescending way. Depending on the algorithm of course. Machine learning could be good for humanity. If it actually paired datasets together that were mutually beneficial to one and other. We humans do this when we connect communities together in a diverse and democratic way. There is a power to that. Of course, there are people who can’t profit off of people thinking and working for themselves. And thus, here in America we don’t have the same protections as Europe with laws like GDPR. I hear American diplomats chant all the time about how setting foot in mainland China is a blow to your privacy. All I experienced was a Big Mac at Pudong airport. When I was on Instagram and Facebook it felt like a waking nightmare. As if algorithms were interacting with GPS data to lure people together. This was the after effect of Pokemon Go in real life. A product that was funded partially by government money for not so obvious purposes. Social Engineering is an equal opportunity employer I guess. For better or for worse. These days there’s no shortage of human operators out there trying to sniff for clues. Looking for a job in the midst of all of it is frustrating enough. Knowing the balance between networking, ghost accounts, and maintaining the professionalism in between. I have never known who is interacting with me online and why sometimes. I have clues. I can guess but is that psychologically healthy in the long term for a person. It can be deeper than catfishing. Whole entire friendships shrouded by fake names. I stick to the ones I can visualize without a migraine. And the narratives that might support it out of hiding. Like commuting to Shanghai for a job for a range of companies. Or waiting around for the rest of my previous employer’s obligations to me to settle.

If you ever wanted to look at someone who is totally and utterly mindfucked but exceedingly okay with it all it is me. And the value of that is still to be determined. I wake up some days and wonder why I haven’t hurt myself or done worse. I quit drinking almost four years ago. I cleared all of my credit card debt which sits at zero to this day. My credit score is above eight hundred. I paid my rent. Nobody bothers me much. I am alone all the time except when I go for groceries. I sleep alone with my cat on my shoulder. People interact with me in the most bizarre fashion. I feel empty and ghostlike. And yet there’s these small windows of hope. I haven’t applied for anything else. I think sometimes you have to put your name out there and see what it means to people. The algorithms thought I was a good fit. There are other things it seems to think I am a good fit for. Friday night the algorithms pelted my notifications for the first time in awhile for jobs here in Chicago. And they were bleak. I felt more empty. I felt overwhelmed by the fact through reaching out I have seen no closure or solace. When I do connect with people from my past on that platform it’s mostly professional. Like a note of encouragement but no real desire to go deeper. You feel like a leper. And this isn’t the first time. I’m starting to realize I’ve felt isolated and exiled for longer than this entire pandemic. I feel used and manipulated over and over and through and through. And yet I also have this very thin layer of understanding with the rest of the world. One that I couldn’t really escape if I tried. One that I really have no idea what the outcome is. But it’s something I had to try. You throw a rock across the pond and it lands with a splash. And people start connecting two and two together. What happens? To me nothing. It was such a far throw to reach you. I’ve been throwing rocks for years. Missing every time. And then you just nail it. And people aren’t looking. It’s frustrating. You know it landed. And yet you know nothing. Maybe it needed to landed in the pond a little further to the left. Maybe IKEA furniture was blocking the way. Maybe it dropped into somebody’s Prada bag. The general point is this. I’m in your area. And in some ways you are in mine. I don’t know what the answer is. I don’t think it’s mine to solve. Unless it has something to do with keeping the internet safe. And this community has always felt true to that for me. Everyone I’ve ever shared these ideas and desires with has held a silent respect and knowing. And we’re more than just machines grinding out data in a callous way. We are people trying to connect to real emotions and dreams. And in some ways, I’ve found that people here actually help each other emotionally. Which is why it is such a torture to look for a job at the mercy of social networking that treats you like a dataset and not a loving, caring human being.

I am beyond hurt in my life. It feels both hard and easy to say. I have experienced the most soul crushing ego death no one could ask for. And I live with it silently like a beast inside me. Nobody gives a real fuck about me in real life. Nobody has ever given me a hug. Nobody has ever reached out to touch me and ask if I was okay. And somehow people on the internet have. For years. Silently layered on top of this casual and fragile society we live in. A complex network of people who trust each other and care in their own way. A respect for privacy, space and dreams. These are the things I was sworn to protect even if nobody ever gave a fuck. I did not want to fail the people who inspired me. And yet I am a complete failure. I am worth absolutely nothing to people other than to compare or constrast themselves and their stock portfolios to. I am a mirror in a house of broken dreams. A fractured idea of what could be if someone would just piece me the fuck back together. And the algorithms try I believe. And they shove data in front of my face I don’t want to see. They push and pull me apart and I’m expected to ride the pink wave off into the sunset. When each day I feel more and more like garbage. This is what is to be expected. I’m supposed to throw it all away. And yet I’m also supposed to wait for people to get their shit together. The last two months I was abandoned in the most hateful and spiteful way. I don’t know if that’s what the intention was. But my feelings are beyond existential. The hope I cling onto is weighted by things holding me back. And the indecision with people to trust I am somebody. I have never felt like somebody. I have felt invisible, hopeless, and dried up. And always there’s this breath of that one day I will be discovered. I will be taken off the bench and treated like someone special. And it never comes. I grow older. My life becomes more complex. The things that keep me alive and the decisions I make are in a complete psychological vacuum. This is self reliance. This is being an adult. And yet I am completely alone in this process. It makes me cry. It makes me angry. It makes me sit here and want to scream. But here in space. The personal space. The intimate private space we all share. Nobody wants to see me break down. Especially you. And if you didn’t know by now, now you do. I will keep throwing that rock until somebody catches it and asks why. Because I have no other choice but to send the message. I care. I have always cared. Whether that means anything to anyone is the real mystery. I don’t know that it does. I hope. But hope does nothing. You have to try. And you will fail. You know me best at that. How many times I have failed. It’s highly probable I’ll succeed one day. By myself or other wise. <3 Tim

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wolfliving · 5 years ago

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The Corona Reboot

It’s early yet, but we’ll see once the bodies are buried.

https://www.ianalanpaul.com/the-corona-reboot/

The Corona Reboot

by Ian Alan Paul

A decade from now, historians may very well call the coronavirus pandemic the great deceleration. The bodies that had been endlessly propelled through cities on metros, buses, bicycles, and freeways now sit in self-imposed isolation at home, the international flights that had been relentlessly criss-crossing continents now are increasingly grounded, and the container ships that had been churning steadily back and forth across oceans now drift idly beside coastal ports, buoyed by their lack of cargo. Chinese factories lay serenely still without their workers as if they were relics of a bygone industrial era, while environmentalists post online about the substantial reduction in global carbon dioxide emissions. The relentlessly accelerating velocities of capitalism appear, quite unexpectedly and abruptly, to be grinding, lumbering, and lurching into a languid slumber.

Following from the desertion of offices, factories, universities, restaurants, and other places of work, the historical suspension of the planet’s economy has given us all time for long conversations in living rooms and on phones, for cooking intricate recipes and reading long-forgotten books on shelves, for bringing groceries and medicine to neighbors in need, for playing in baths with children sent home from school, and for watching films that had been put off for years. People sleep, write, cry, dance, play, exercise, have sex, and laugh in the new pause we find ourselves within. The fragility, vulnerability, and interdependency of life come to be more intensely felt and drawn more acutely into focus as the virus spreads, opening the way for new intimacies, solidarities, and creativities. Even when surrounded by crisis and fear, fragile but utopian moments nonetheless find life.

And yet it already appears that, after only a few days of a planetary interlude characterized by an unprecedented deceleration of life on every continent where people have begun questioning the social order that had defined their lives up to this point, immense accelerations have been set into motion in an attempt to socially, economically, and politically compensate for the velocities that had been lost elsewhere. The shutting down of our planet’s systems appears to have already been answered by a system reboot meant to capture the unactualized potentials of so many newly immobilized bodies, to economically put to use the many bodies that have rather unexpectedly found time to experiment with the multiplicity of life’s uses.

If a system reboot, what we might simply call the corona reboot, can be said to be taking place, it is only because power now understands society as being wholly integrated as a vast computer that can be programmed and reprogrammed as needed in response to whatever disruption, contingency, or event. In this sense, the deceleration of so many bodies appears to have opened the way for the cybernetic reorganization and reacceleration of planetary life, where social distancing has justified the implementation of the most intense forms of digitized connectivity and control technically realizable in our present. This text is ultimately an attempt to think through the possibility that the shutting down and subsequent rebooting of the planet presently underway may not in fact be a collection of ad-hoc measures that will fade as the contagion does, but that the coronavirus may come to serve as the catalyst for a new kind of society built upon the forms of digitized subjectivity that are forged within the unique historical circumstances of the pandemic.

At the very minimum, in this moment we must all struggle to understand the rapid transformations of social life, of work, and of politics presently underway not only in the interest of surviving this together and defending our common humanity, but also in hopes of establishing a different kind of society than the one presently imagined by power. If this planetary reboot takes form as a total recalibration of social, economic, and political life in the interest of preserving the continuity of the social, political, and economic order of capitalism, how might we begin to imagine social life differently in this trying moment?

At this early stage, it appears that at least two new kinds of subjectivity have already begun to take shape, both of which are mutually constitutive, intimately dependent upon, and shaped by the informatic infrastructures and apparatuses that now run through and organize much of our planetary society. On the one hand, we have the domesticated/connected subject, who in being confined to their home is pushed to invent new ways to reconnect to and participate in a virtualized economy. On the other hand, we have the mobile/disposable subject that serves as the circulatory system of the pandemic, a subject that becomes increasingly vulnerable and precarious as it is compelled to move at ever greater velocities. In order for domesticated/connected subjects to materially sustain themselves, they must be coupled with the mobile/disposable subject that fulfills the minimum material needs of society while ensuring the social possibility of isolated yet networked domestic life.

The domesticated/connected subject is horrifically cut off from social life in their home yet is intimately plugged into an increasingly networked economy. They are as docile as they are productive, integrated with society but integrated only as separate. Office workers, university professors, programmers, reporters, and cultural workers, among others, are all ordered to stay home, but to stay logged on. Video streaming platforms struggle to handle the new volumes of traffic while raking in profits, and everyone undergoes online training so they can continue to collaborate and work on a domesticated network. The isolation of the home corresponds with its degree of connectivity. The domesticated/connected subject can avoid the risk of being proximate and promiscuous with other possibly-infected bodies by simply connecting to the office meeting on Zoom, streaming culture on Netflix, ordering food on Postmates, venting on Facebook, and purchasing more hand sanitizer on Amazon, while Trump has announced that if you do end up with symptoms of the coronavirus all you must do is visit a site designed by Google to schedule a remote test. As the mobility of bodies becomes restricted to domestic spaces, computer keyboards dance with frenzied kinetic activity in service of slowing the contagion and keeping the economy stumbling along through waves of turbulent market volatility.

Emerging as a refrain to the domesticated/connected subject, the mobile/disposable subject moves at ever greater speeds and at ever greater risk so no one else has to. The interruption of public life is overrun by the feverishly accelerated mobile/disposable subject that is connected and subservient to the same informatic networks that connect domesticated/connected subjects to planetary economies. Commanded by smartphone apps delivering endless streams of pings and alerts that steer them from one gig to the next through nearly vacant streets, migrant workers on electric bikes have never been in higher demand, carrying food boxes from restaurants, bags of groceries from supermarkets, and miscellany from pharmacies, bodegas, and liquor stores to all of the salaried domesticated/connected workers who, now confined at home, create vast deluges of online orders.

Amazon truck drivers speed across neighborhoods, always over capacity and behind impossible-to-meet computationally-generated schedules, carrying boxes filled with diapers, batteries, bleach wipes, laptops, and breathing masks. Ambulance drivers are asked to simply never stop driving, while garbage workers haul larger and larger bags of trash filled with larger and larger volumes of domestic refuse. All of these workers are expected to go increasingly fast to keep up with increasing demand, and thus increasingly expose themselves to the contagion and other forms of risk associated with their embodied acceleration. The massive containment and isolation of the domesticated/connected subject has as its twin the mobile/disposable subject that constitutes the system of distribution for a new pandemic economy.

Both the domesticated/connected subjects working from home and the mobile/disposable subjects racing through the streets are ultimately brought together not only by the immense interconnected apparatuses of the digital economy but also by the blanket waves of social abandonment that now affect all life. When bodies of all kinds can be connected as isolated nodes on a network, remaining deeply reliant upon and subject to shifting algorithmic command and demand structures, the value of any single body approaches zero as every node on the network can be algorithmically swapped out and replaced with any other.

The cybernetic management and distribution of labor and commodities allows for the economy to draw on the population only as needed, while effectively abandoning the waste that is the remainder. When a domesticated/connected subject gets sick with the coronavirus and can no longer work, the still-healthy occupants of another house are ready to log on and fill their place, just as when a delivery worker breaks their leg after falling off of their bike, another can be pinged and made to run out the door. The emerging economic system doesn’t spare any time thinking of what may happen to all those who for whatever reason cannot manage to stay connected and working in this economy.

The massive deterritorialization of labor spurred on by the pandemic response has allowed for the implementation of a newly flexible organization of work that frees capitalism and the capitalist state of any responsibility for life in general as long as the economy survives. Providing adequate testing for the virus, guaranteeing universal access to healthcare, and ensuring monetary relief to newly impoverished populations are seen as unnecessary as long as everyone remains willing to connect, log on, and answer the relentless call of capitalism’s networks. The management of the population has become synonymous with the management of waste, excess, and trash, and only those who have the ability to accelerate will be sustained and supported by the larger logistical and infrastructural systems of a new post-pandemic cybernetic economy, which in reality is just a more extreme and refined form of the capitalism we had all already been accustomed to living within.

In this moment it is crucial that we insist that the reterritorialization of our society, the corona reboot, that is presently underway is not inevitable nor undefeatable. In the interlude of the pandemic there is an opportunity to refuse the imposition of digitized commands and coercive connections while defending and cultivating different kinds of human relation and interdependency. There is a chance now for all of us to consider how we might restart society differently rather than allow the logic of capital to unthinkingly do it for us. We’ll likely be in these pandemic circumstances for many months, so let’s use this time to disconnect from the pressures, exigencies, and demands of the economy and to reconnect with others in ways that do not conform or submit to the new kinds of acceleration and abandonment that are already being implemented everywhere around us.

The coronavirus pandemic marks the first time in our history that a planetary disruption of this kind and scale has occurred in a networked society such as ours, but that does not mean that we have to let the logic of capitalist networks be what ultimately reorganizes our ways of life. Already, we see mutual aid networks being constituted, new forms of digital labor being subverted, carceral structures being dismantled, and market logics being refused. We must think of this as just a beginning. How freely, wildly, and courageously will we allow ourselves to dream in this moment? What new practices of living and relationalities will we dare to put into practice? How can we overcome the domestic paranoia that sends people sprinting to supermarkets, the fear that keeps us away from neighbors, the depression that follows from reading the news, while also keeping one another safe and caring for one another as the virus spreads? How can we begin to find one another to act compassionately and collectively together in a struggle to arrive on the other side of this pandemic in a world not structured by abandonment, isolation, and acceleration but by the inextinguishable dignity and value of life itself? Each of us must dedicate ourselves to begin not only articulating but living answers to these questions in all of the varied situations we find ourselves living within.

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caplofan · 5 years ago

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The Unreasonable Importance of Data Preparation in 2020

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The Unreasonable Importance of Data Preparation in 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them.

This is the garbage in, garbage out principle: flawed data going in leads to flawed results, algorithms, and business decisions. If a self-driving car’s decision-making algorithm is trained on data of traffic collected during the day, you wouldn’t put it on the roads at night.

To take it a step further, if such an algorithm is trained in an environment with cars driven by humans, how can you expect it to perform well on roads with other self-driving cars?

Beyond the autonomous driving example described, the “garbage in” side of the equation can take many forms—for example, incorrectly entered data, poorly packaged data, and data collected incorrectly, more of which we’ll address below.

When executives ask me how to approach an AI transformation, I show them Monica Rogati’s AI Hierarchy of Needs, which has AI at the top, and everything is built upon the foundation of data (Rogati is a data science and AI advisor, former VP of data at Jawbone, and former LinkedIn data scientist):

AI Hierarchy of Needs 2020

Image courtesy of Monica Rogati, used with permission.

Why is high-quality and accessible data foundational?

If you’re basing business decisions on dashboards or the results of online experiments, you need to have the right data.

On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0 era, a new paradigm for software where machine learning and AI require less focus on writing code and more on configuring, selecting inputs, and iterating through data to create higher level models that learn from the data we give them.

In this new world, data has become a first-class citizen, where computation becomes increasingly probabilistic and programs no longer do the same thing each time they run.

The model and the data specification become more important than the code.

Collecting the right data requires a principled approach that is a function of your business question.

Data collected for one purpose can have limited use for other questions.

The assumed value of data is a myth leading to inflated valuations of start-ups capturing said data. John Myles White, data scientist and engineering manager at Facebook, wrote:

The biggest risk I see with data science projects is that analyzing data per se is generally a bad thing.

Generating data with a pre-specified analysis plan and running that analysis is good. Re-analyzing existing data is often very bad.”

John is drawing attention to thinking carefully about what you hope to get out of the data, what question you hope to answer, what biases may exist, and what you need to correct before jumping in with an analysis[1].

With the right mindset, you can get a lot out of analyzing existing data—for example, descriptive data is often quite useful for early-stage companies[2].

Not too long ago, “save everything” was a common maxim in tech; you never knew if you might need the data. However, attempting to repurpose pre-existing data can muddy the water by shifting the semantics from why the data was collected to the question you hope to answer. In particular, determining causation from correlation can be difficult.

For example, a pre-existing correlation pulled from an organization’s database should be tested in a new experiment and not assumed to imply causation[3], instead of this commonly encountered pattern in tech:

A large fraction of users that do X do Z Z is good Let’s get everybody to do X

Correlation in existing data is evidence for causation that then needs to be verified by collecting more data.

The same challenge plagues scientific research. Take the case of Brian Wansink, former head of the Food and Brand Lab at Cornell University, who stepped down after a Cornell faculty review reported he “committed academic misconduct in his research and scholarship, including misreporting of research data, problematic statistical techniques [and] failure to properly document and preserve research results.” One of his more egregious errors was to continually test already collected data for new hypotheses until one stuck, after his initial hypothesis failed[4]. NPR put it well: “the gold standard of scientific studies is to make a single hypothesis, gather data to test it, and analyze the results to see if it holds up. By Wansink’s own admission in the blog post, that’s not what happened in his lab.” He continually tried to fit new hypotheses unrelated to why he collected the data until he got a null hypothesis with an acceptable p-value—a perversion of the scientific method.

Data professionals spend an inordinate amount on time cleaning, repairing, and preparing data

Before you even think about sophisticated modeling, state-of-the-art machine learning, and AI, you need to make sure your data is ready for analysis—this is the realm of data preparation. You may picture data scientists building machine learning models all day, but the common trope that they spend 80% of their time on data preparation is closer to the truth.

common trope that data scientists spend 80% of their time on data preparation 2020

This is old news in many ways, but it’s old news that still plagues us: a recent O’Reilly survey found that lack of data or data quality issues was one of the main bottlenecks for further AI adoption for companies at the AI evaluation stage and was the main bottleneck for companies with mature AI practices.

Good quality datasets are all alike, but every low-quality dataset is low-quality in its own way[5]. Data can be low-quality if:

It doesn’t fit your question or its collection wasn’t carefully considered; It’s erroneous (it may say “cicago” for a location), inconsistent (it may say “cicago” in one place and “Chicago” in another), or missing; It’s good data but packaged in an atrocious way—e.g., it’s stored across a range of siloed databases in an organization; It requires human labeling to be useful (such as manually labeling emails as “spam” or “not” for a spam detection algorithm).

This definition of low-quality data defines quality as a function of how much work is required to get the data into an analysis-ready form. Look at the responses to my tweet for data quality nightmares that modern data professionals grapple with.

The importance of automating data preparation

Most of the conversation around AI automation involves automating machine learning models, a field known as AutoML.

This is important: consider how many modern models need to operate at scale and in real time (such as Google’s search engine and the relevant tweets that Twitter surfaces in your feed). We also need to be talking about automation of all steps in the data science workflow/pipeline, including those at the start. Why is it important to automate data preparation?

It occupies an inordinate amount of time for data professionals. Data drudgery automation in the era of data smog will free data scientists up for doing more interesting, creative work (such as modeling or interfacing with business questions and insights). “76% of data scientists view data preparation as the least enjoyable part of their work,” according to a CrowdFlower survey.

A series of subjective data preparation micro-decisions can bias your analysis. For example, one analyst may throw out data with missing values, another may infer the missing values. For more on how micro-decisions in analysis can impact results, I recommend Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results[6] (note that the analytical micro-decisions in this study are not only data preparation decisions).

Automating data preparation won’t necessarily remove such bias, but it will make it systematic, discoverable, auditable, unit-testable, and correctable. Model results will then be less reliant on individuals making hundreds of micro-decisions.

An added benefit is that the work will be reproducible and robust, in the sense that somebody else (say, in another department) can reproduce the analysis and get the same results[7];

For the increasing number of real-time algorithms in production, humans need to be taken out of the loop at runtime as much as possible (and perhaps be kept in the loop more as algorithmic managers): when you use Siri to make a reservation on OpenTable by asking for a table for four at a nearby Italian restaurant tonight, there’s a speech-to-text model, a geographic search model, and a restaurant-matching model, all working together in real time.

No data analysts/scientists work on this data pipeline as everything must happen in real time, requiring an automated data preparation and data quality workflow (e.g., to resolve if I say “eye-talian” instead of “it-atian”).

The third point above speaks more generally to the need for automation around all parts of the data science workflow. This need will grow as smart devices, IoT, voice assistants, drones, and augmented and virtual reality become more prevalent.

Automation represents a specific case of democratization, making data skills easily accessible for the broader population. Democratization involves both education (which I focus on in my work at DataCamp) and developing tools that many people can use.

Understanding the importance of general automation and democratization of all parts of the DS/ML/AI workflow, it’s important to recognize that we’ve done pretty well at democratizing data collection and gathering, modeling[8], and data reporting[9], but what remains stubbornly difficult is the whole process of preparing the data.

Modern tools for automating data cleaning and data preparation

We’re seeing the emergence of modern tools for automated data cleaning and preparation, such as HoloClean and Snorkel coming from Christopher Ré’s group at Stanford.

HoloClean decouples the task of data cleaning into error detection (such as recognizing that the location “cicago” is erroneous) and repairing erroneous data (such as changing “cicago” to “Chicago”), and formalizes the fact that “data cleaning is a statistical learning and inference problem.”

All data analysis and data science work is a combination of data, assumptions, and prior knowledge. So when you’re missing data or have “low-quality data,” you use assumptions, statistics, and inference to repair your data.

HoloClean performs this automatically in a principled, statistical manner. All the user needs to do is “to specify high-level assertions that capture their domain expertise with respect to invariants that the input data needs to satisfy. No other supervision is required!”

The HoloClean team also has a system for automating the “building and managing [of] training datasets without manual labeling” called Snorkel. Having correctly labeled data is a key part of preparing data to build machine learning models[10].

As more and more data is generated, manually labeling it is unfeasible.

Snorkel provides a way to automate labeling, using a modern paradigm called data programming, in which users are able to “inject domain information [or heuristics] into machine learning models in higher level, higher bandwidth ways than manually labeling thousands or millions of individual data points.”

Researchers at Google AI have adapted Snorkel to label data at industrial/web scale and demonstrated its utility in three scenarios: topic classification, product classification, and real-time event classification.

Snorkel doesn’t stop at data labeling. It also allows you to automate two other key aspects of data preparation:

Data augmentation—that is, creating more labeled data. Consider an image recognition problem in which you are trying to detect cars in photos for your self-driving car algorithm.

Classically, you’ll need at least several thousand labeled photos for your training dataset. If you don’t have enough training data and it’s too expensive to manually collect and label more data, you can create more by rotating and reflecting your images.

Discovery of critical data subsets—for example, figuring out which subsets of your data really help to distinguish spam from non-spam.

These are two of many current examples of the augmented data preparation revolution, which includes products from IBM and DataRobot.

The future of data tooling and data preparation as a cultural challenge

So what does the future hold? In a world with an increasing number of models and algorithms in production, learning from large amounts of real-time streaming data, we need both education and tooling/products for domain experts to build, interact with, and audit the relevant data pipelines.

We’ve seen a lot of headway made in democratizing and automating data collection and building models. Just look at the emergence of drag-and-drop tools for machine learning workflows coming out of Google and Microsoft.

As we saw from the recent O’Reilly survey, data preparation and cleaning still take up a lot of time that data professionals don’t enjoy. For this reason, it’s exciting that we’re now starting to see headway in automated tooling for data cleaning and preparation. It will be interesting to see how this space grows and how the tools are adopted.

A bright future would see data preparation and data quality as first-class citizens in the data workflow, alongside machine learning, deep learning, and AI. Dealing with incorrect or missing data is unglamorous but necessary work.

It’s easy to justify working with data that’s obviously wrong; the only real surprise is the amount of time it takes. Understanding how to manage more subtle problems with data, such as data that reflects and perpetuates historical biases (for example, real estate redlining) is a more difficult organizational challenge.

This will require honest, open conversations in any organization around what data workflows actually look like.

The fact that business leaders are focused on predictive models and deep learning while data workers spend most of their time on data preparation is a cultural challenge, not a technical one. If this part of the data flow pipeline is going to be solved in the future, everybody needs to acknowledge and understand the challenge.

Original Source: The unreasonable importance of data preparation

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jacewilliams1 · 6 years ago

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5 good things about general aviation in 2019

Pilots have a well-earned reputation for seeing the glass half empty, even if it’s threatening to spill over the top. In the last three months I have personally heard the following ever-popular complaints: gas prices are too high, the FAA is out to get us, and (most importantly) it was so, so much better back in the good old days. A little nostalgia once in a while is understandable, but, when it becomes completely divorced from reality, we need to call a timeout. Too much negativity is bad for an industry that is trying to attract new entrants, whether they be recreational flyers or airline pilots.

So in the spirit of fairness, I like to pause every few years and consider what’s going right in aviation. Call me a naive optimist if you like, but I still see a lot to appreciate, from the thousands of airports in the US to the relative openness of our airspace to the strong experimental aircraft movement. These trends are old news; five newer ones caught my attention at the Sun ‘n Fun Fly-in last week, and I think they bode well for pilots.

A glass cockpit in a Tiger? It makes sense given the new avionics options from Garmin and others.

1. Lower cost avionics are taking over. The dream of modern, powerful, and inexpensive avionics has seemed within reach for 20 years, but only in the last two it has finally become a reality. A stroll around the show last week in Lakeland showed a huge variety of avionics that truly do make flying safer and easier, but do not required a $25,000 buy-in. From Garmin’s sub-$10,000 G3X glass cockpit to uAvionix’s wingtip ADS-B transmitter to Aspen’s affordable E5 flight display, there are plenty of great options from established companies.

Taken together, these breakthroughs in avionics value make a 50-year old piston airplane worth upgrading. You can buy that 1970 Cessna 182 and put a new panel in it without spending more than the airplane purchase price. Or, you can build a new airplane around these avionics that is (relatively) affordable, like Piper’s $260,000 Pilot model.

The innovative avionics companies deserve a lot of credit here, including giants like Garmin who have continually reinvented their product line and startups like ForeFlight who have challenged the giants with new ways of doing business. But don’t forget the regulatory and legislative changes that have made these new avionics possible. The FAA’s flexible NORSEE policy has allowed the installation of non-certified avionics in thousands of airplanes, but without complicated paperwork and expensive certification. Likewise for the revised Part 23 certification standards, which may finally encourage some new airplane designs. Whether you credit AOPA, Congress, or the FAA, the folks in Washington deserve some applause.

2. Backcountry flying is hot. If you’ve spent any time on YouTube lately, you may have noticed a growing number of videos showing taildraggers landing in remote places. Some are recognizable YouTube stars like Trent Palmer, while others are simply private pilots with a Cub and a dry riverbed. Combine this with the good work the Recreational Aviation Foundation (RAF) is doing to preserve backcountry airstrips, and even the new High Sierra Fly-in at a dry lakebed in Nevada, and you have a real trend. Flying airplanes is not just about tricycle gear airplanes landing at paved airports anymore.

Whether you land off-airport or not, this growing niche is good for general aviation, because – for a change – it’s all about the fun. While I believe an ILS to 200 feet is as thrilling as anything in flying, many non-pilots would disagree, and it’s a lot harder to relate to than fly fishing next to an old Cessna. Besides, traveling by GA isn’t easy without a high performance airplane and an instrument rating, both of which cost money. What the “fat tire cowboys” and other groups offer is a more accessible and more adventurous brand of aviation. Sure, some of the airplanes are high priced bush planes, and some of the locations are remote, but the overall culture is welcoming. Anecdotal evidence (the emails I get and the people I talk to at air shows) suggests they are attracting a whole new type of pilot.

Triple Tree Aerodrome is a special place – and a very popular one too.

3. Community spirit is strong. Some pilots wax nostalgic about the days when “the pilot brotherhood” was strong and hangar flying sessions would last all day. In fact, I see plenty of signs that this community spirit is as strong as ever. It might look different, but that doesn’t make it bad. Consider three trends.

First, flying clubs are growing in popularity after years of neglect. Both AOPA and EAA have encouraged this growth, and it seems to be paying off at least a bit: AOPA announced last week that over 100 new clubs have been started in the last five years. That doesn’t count the many new IMC/VMC clubs that have popped up, where pilots meet monthly to discuss real world scenarios. I’ve attended a few of these meetings over the last year and I can confirm that pilots still like to meet face-to-face and learn from each other.

Second, fly-ins seem to be reinventing themselves. The high desert fly-in mentioned above is a prime example, as are the rotating AOPA fly-ins, which offer free, local events around the country. Both have been successful, and last week’s Sun ‘n Fun event was as busy as I can remember, but Triple Tree Aerodrome in South Carolina may be the most interesting. This beautiful grass strip is a pilot’s paradise, but instead of guarding it for personal use, the owner throws the doors open multiple times per year for fun events. This includes radio control airplane contests and even a young pilots’ fly-in. No big exhibit tents, no fancy air show, just a relaxed atmosphere to meet new friends and admire other airplanes.

Finally, there are a variety of online groups that keep pilots connected. From Facebook groups (Cirrus pilots, student pilots, and tailwheel pilots all have active ones, among dozens of others) to Slack channels to this website, I see plenty of examples of pilots sharing their experience with others. Not all of this is positive and encouraging, but compared to much of the garbage on social media, I’ve found most of it to be honest and helpful. I know I would have loved such a resource when I was a student pilot.

4. Weather tools are much better. Weather will never be “solved” for pilots, but the increasing number and quality of weather tools has made life a little better for pilots. It’s easy to lose track of the recent advancements, but they are notable. For a start, subscription-free ADS-B weather has made in-flight radar more available than ever before and tens of thousands of pilots are flying with it for the first time. This service continues to improve, too, with the introduction of five new weather products late last year. I believe ADS-B and iPads have had a real impact on safety.

The latest GFA cloud top product (right) is much more accurate than the old one (left).

Online tools are also improving. The Graphical Forecast for Aviation (GFA) is the replacement for the Area Forecast, and the overall goal is laudable – to replace coded text forecasts with easier-to-understand graphical products. Unfortunately, its first iteration was underwhelming. The team behind the GFA stuck to it, though, and recent versions are much better. In particular, I’ve found the cloud tops tool to be far more accurate after a recent change to the algorithm.

The same effort is paying off with graphical ceiling and visibility forecasts (MOS), and icing forecasts (CIP/FIP). These were once nothing more than experiments, but they have become quite reliable and are now an essential part of any preflight briefing. Even turbulence forecasts, previously only released for the flight levels, are now available all the way to the ground. GA pilots have more – and better – tools than ever before, and we very rarely have to pay for them.

5. Airlines are hiring. Certainly one of the most visible trends over the last few years, this one might not seem to have much impact on general aviation pilots. However, I see positive spillover effects everywhere: thousands of new people coming into aviation to seek airline jobs, busier flight schools paying flight instructors more money, piston airplane factories staying open to support training fleets, and more airline pilots with extra money to buy piston airplanes for fun flying. Even if many of these new student pilots leave GA and never come back, they can provide quite the stimulus during their 3-5 years in training. The airline economy dwarfs general aviation, so when it is on the upswing, we can’t help but rise too.

Yes, I hate high ramp fees, pop-up airspace restrictions, and expensive airworthiness directives. I wish new airplanes cost $50,000 and Meigs was still open. But given the chance to fly in 1999 or 2019, I wouldn’t hesitate. Hand me my iPad and let’s go flying.

The post 5 good things about general aviation in 2019 appeared first on Air Facts Journal.

from Engineering Blog https://airfactsjournal.com/2019/04/5-good-things-about-general-aviation-in-2019/

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thegloober · 6 years ago

Text

The year social networks were no longer social

The term “social network” has become a meaningless association of words. Pair those two words and it becomes a tech category, the equivalent of a single term to define a group of products.

But are social networks even social anymore? If you have a feeling of tech fatigue when you open the Facebook app, you’re not alone. Watching distant cousins fight about politics in a comment thread is no longer fun.

Chances are you have dozens, hundreds or maybe thousands of friends and followers across multiple platforms. But those crowded places have never felt so empty.

It doesn’t mean that you should move to the woods and talk with animals. And Facebook, Twitter or LinkedIn won’t collapse overnight. They have intrinsic value with other features — social graphs, digital CVs, organizing events…

But the concept of wide networks of social ties with an element of broadcasting is dead.

From interest-based communities to your lousy neighbor

If you’ve been active on the web for long enough, you may have fond memories of internet forums. Maybe you were a fan of video games, Harry Potter or painting.

Fragmentation was key. You could be active on multiple forums and you didn’t have to mention your other passions. Over time, you’d see the same names come up again and again on your favorite forum. You’d create your own running jokes, discover things together, laugh, cry and feel something.

When I was a teenager, I was active on multiple forums. I remember posting thousands of messages a year and getting to know new people. It felt like hanging out with a welcoming group of friends because you shared the same passions.

It wasn’t just fake internet relationships. I met “IRL” with fellow internet friends quite a few times. One day, I remember browsing the list of threads and learning about someone’s passing. Their significant other posted a short message because the forum meant a lot to this person.

Most of the time, I didn’t know the identities of the persons talking with me. We were all using nicknames and put tidbits of information in bios — “Stuttgart, Germany” or “train ticket inspector.”

And then, Facebook happened. At first, it was also all about interest-based communities — attending the same college is a shared interest, after all. Then, they opened it up to everyone to scale beyond universities.

When you look at your list of friends, they are your Facebook friends not because you share a hobby, but because you’ve know them for a while.

Facebook constantly pushes you to add more friends with the infamous “People you may know” feature. Knowing someone is one thing, but having things to talk about is another.

So here we are, with your lousy neighbor sharing a sexist joke in your Facebook feed.

As social networks become bigger, content becomes garbage.

Facebook’s social graph is broken by design. Putting names and faces on people made friend requests emotionally charged. You can’t say no to your high school best friend, even if you haven’t seen her in five years.

It used to be okay to leave friends behind. It used to be okay to forget about people. But the fact that it’s possible to stay in touch with social networks have made those things socially unacceptable.

Too big to succeed

One of the key pillars of social networks is the broadcasting feature. You can write a message, share a photo, make a story and broadcast them to your friends and followers.

But broadcasting isn’t scalable.

Most social networks are now publicly traded companies — they’re always chasing growth. Growth means more revenue and revenue means that users need to see more ads.

The best way to shove more ads down your throat is to make you spend more time on a service. If you watch multiple YouTube videos, you’re going to see more pre-roll ads. And there are two ways to make you spend more time on a social network — making you come back more often and making you stay longer each time you visit.

And 2018 has been the year of cheap tricks and dark pattern design. In order to make you come more often, companies now send you FOMO-driven notifications with incomplete, disproportionate information.

I created a new Facebook account just so I could access an Oculus thing. Despite having no friends, apparently I’m really missing out on a whole lot of “fun” activity from all these specifically-named people I don’t know. And I have two notifications already! “Cool.” pic.twitter.com/uBHicji3pj

— Nick Farina (@nfarina) October 1, 2018

This isn’t just about opening an app. Social networks now want to direct you to other parts of the service. Why don’t you click on this bright orange banner to open IGTV? Look at this shiny button! Look! Look!

This navigation bar makes no sense Facebook. Also it’s an insult to trick people’s brains with animated ✨ to foster engagement pic.twitter.com/eMGxbh7r4a

— Romain Dillet 🙃 (@romaindillet) November 27, 2018

And then, there’s all the gamification, algorithm-driven recommendations and other Skinner box mechanisms. That tiny peak of adrenaline you get when you refresh your feed, even if it only happens once per week, is what’s going to make you come back again and again.

Don’t forget that Netflix wanted to give kids digital badges if they completed a season. The company has since realized that it was going too far. Still, U.S. adults now spend nearly six hours per day consuming digital media — and phones represent more than half of that usage.

Given that social networks need to give you something new every time, they want you to follow as many people as possible, subscribe to every YouTube channel you can. This way, every time you come back, there’s something new.

Algorithms recommend some content based on engagement, and guess what? The most outrageous, polarizing content always ends up at the top of the pile.

I’m not going to talk about fake news or the fact that YouTubers now all write titles in ALL CAPS to grab your attention. That’s a topic for another article. But YouTube shouldn’t be surprised that Logan Paul filmed a suicide victim in Japan to drive engagement and trick the algorithm.

In other words, as social networks become bigger, content becomes garbage.

Private communities

Centralization is always followed by decentralization. Now that we’ve reached a social network dead end, it’s time to build our own digital house.

Group messaging has been key when it comes to staying in touch with long-distance family members. But you can create your own interest-based groups and talk about things you’re passionate about with people who care about those things.

Social networks that haven’t become too big still have an opportunity to pivot. It’s time to make them more about close relationships and add useful features to talk with your best friends and close ones.

And if you have interesting things to say, do it on your own terms. Create a blog instead of signing up to Medium. This way, Medium won’t force your readers to sign up when they want to read your words.

If you spend your vacation crafting the perfect Instagram story, you should be more cynical about it. Either you want to make a career out of it and become an Instagram star, or you should consider sending photos and videos to your communities directly. Otherwise, you’re just participating in a rotten system.

If you want to comment on politics and life in general, you should consider talking about those topics with people surrounding you, not your friends on Facebook.

Put your phone back in your pocket and start a conversation. You might end up discussing for hours without even thinking about the red dots on all your app icons.

Source: https://bloghyped.com/the-year-social-networks-were-no-longer-social/

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technicalsolutions88 · 6 years ago

Link

The term “social network” has become a meaningless association of words. Pair those two words and it becomes a tech category, the equivalent of a single term to define a group of products.

Chances are you have dozens, hundreds or maybe thousands of friends and followers across multiple platforms. But those crowded places have never felt so empty.

But the concept of wide networks of social ties with an element of broadcasting is dead.

From interest-based communities to your lousy neighbor

If you’ve been active on the web for long enough, you may have fond memories of internet forums. Maybe you were a fan of video games, Harry Potter or painting.

When you look at your list of friends, they are your Facebook friends not because you share a hobby, but because you’ve know them for a while.

Facebook constantly pushes you to add more friends with the infamous “People you may know” feature. Knowing someone is one thing, but having things to talk about is another.

So here we are, with your lousy neighbor sharing a sexist joke in your Facebook feed.

As social networks become bigger, content becomes garbage.

Too big to succeed

One of the key pillars of social networks is the broadcasting feature. You can write a message, share a photo, make a story and broadcast them to your friends and followers.

But broadcasting isn’t scalable.

Most social networks are now publicly traded companies — they’re always chasing growth. Growth means more revenue and revenue means that users need to see more ads.

I created a new Facebook account just so I could access an Oculus thing. Despite having no friends, apparently I'm really missing out on a whole lot of "fun" activity from all these specifically-named people I don't know. And I have two notifications already! "Cool." pic.twitter.com/uBHicji3pj

— Nick Farina (@nfarina) October 1, 2018

This navigation bar makes no sense Facebook. Also it’s an insult to trick people’s brains with animated

to foster engagement pic.twitter.com/eMGxbh7r4a

— Romain Dillet

(@romaindillet) November 27, 2018

Algorithms recommend some content based on engagement, and guess what? The most outrageous, polarizing content always ends up at the top of the pile.

In other words, as social networks become bigger, content becomes garbage.

Private communities

Centralization is always followed by decentralization. Now that we’ve reached a social network dead end, it’s time to build our own digital house.

If you want to comment on politics and life in general, you should consider talking about those topics with people surrounding you, not your friends on Facebook.

Put your phone back in your pocket and start a conversation. You might end up discussing for hours without even thinking about the red dots on all your app icons.

Tech fatigue

How I cured my tech fatigue by ditching feeds

from Social – TechCrunch https://tcrn.ch/2BDAiu8 Original Content From: https://techcrunch.com

#Technical Solutions #SEO #Online Earning #Youtube Marketing #Android Developer

0 notes

theinvinciblenoob · 6 years ago

Link

The term “social network” has become a meaningless association of words. Pair those two words and it becomes a tech category, the equivalent of a single term to define a group of products.

Chances are you have dozens, hundreds or maybe thousands of friends and followers across multiple platforms. But those crowded places have never felt so empty.

But the concept of wide networks of social ties with an element of broadcasting is dead.

From interest-based communities to your lousy neighbor

If you’ve been active on the web for long enough, you may have fond memories of internet forums. Maybe you were a fan of video games, Harry Potter or painting.

When you look at your list of friends, they are your Facebook friends not because you share a hobby, but because you’ve know them for a while.

Facebook constantly pushes you to add more friends with the infamous “People you may know” feature. Knowing someone is one thing, but having things to talk about is another.

So here we are, with your lousy neighbor sharing a sexist joke in your Facebook feed.

As social networks become bigger, content becomes garbage.

Too big to succeed

One of the key pillars of social networks is the broadcasting feature. You can write a message, share a photo, make a story and broadcast them to your friends and followers.

But broadcasting isn’t scalable.

Most social networks are now publicly traded companies — they’re always chasing growth. Growth means more revenue and revenue means that users need to see more ads.

— Nick Farina (@nfarina) October 1, 2018

This navigation bar makes no sense Facebook. Also it’s an insult to trick people’s brains with animated to foster engagement pic.twitter.com/eMGxbh7r4a

— Romain Dillet (@romaindillet) November 27, 2018

Algorithms recommend some content based on engagement, and guess what? The most outrageous, polarizing content always ends up at the top of the pile.

In other words, as social networks become bigger, content becomes garbage.

Private communities

Centralization is always followed by decentralization. Now that we’ve reached a social network dead end, it’s time to build our own digital house.

If you want to comment on politics and life in general, you should consider talking about those topics with people surrounding you, not your friends on Facebook.

Put your phone back in your pocket and start a conversation. You might end up discussing for hours without even thinking about the red dots on all your app icons.

Tech fatigue

How I cured my tech fatigue by ditching feeds

via TechCrunch

#IFTTT #TechCrunch

0 notes

fmservers · 6 years ago

Text

The year social networks were no longer social

The term “social network” has become a meaningless association of words. Pair those two words and it becomes a tech category, the equivalent of a single term to define a group of products.

Chances are you have dozens, hundreds or maybe thousands of friends and followers across multiple platforms. But those crowded places have never felt so empty.

But the concept of wide networks of social ties with an element of broadcasting is dead.

From interest-based communities to your lousy neighbor

If you’ve been active on the web for long enough, you may have fond memories of internet forums. Maybe you were a fan of video games, Harry Potter or painting.

When you look at your list of friends, they are your Facebook friends not because you share a hobby, but because you’ve know them for a while.

Facebook constantly pushes you to add more friends with the infamous “People you may know” feature. Knowing someone is one thing, but having things to talk about is another.

So here we are, with your lousy neighbor sharing a sexist joke in your Facebook feed.

As social networks become bigger, content becomes garbage.

Too big to succeed

One of the key pillars of social networks is the broadcasting feature. You can write a message, share a photo, make a story and broadcast them to your friends and followers.

But broadcasting isn’t scalable.

Most social networks are now publicly traded companies — they’re always chasing growth. Growth means more revenue and revenue means that users need to see more ads.

— Nick Farina (@nfarina) October 1, 2018

This navigation bar makes no sense Facebook. Also it’s an insult to trick people’s brains with animated to foster engagement pic.twitter.com/eMGxbh7r4a

— Romain Dillet (@romaindillet) November 27, 2018

Algorithms recommend some content based on engagement, and guess what? The most outrageous, polarizing content always ends up at the top of the pile.

In other words, as social networks become bigger, content becomes garbage.

Private communities

Centralization is always followed by decentralization. Now that we’ve reached a social network dead end, it’s time to build our own digital house.

If you want to comment on politics and life in general, you should consider talking about those topics with people surrounding you, not your friends on Facebook.

Put your phone back in your pocket and start a conversation. You might end up discussing for hours without even thinking about the red dots on all your app icons.

Tech fatigue

How I cured my tech fatigue by ditching feeds

Via Romain Dillet https://techcrunch.com

#TechCrunch

0 notes

minnievirizarry · 8 years ago

Text

Link Building in 2017 - What You Should Know

Although link building has always been an important part of search engine algorithms, its importance has risen and declined over the years as different versions of Google’s algorithm were enforced. But a simple truth still remains—link building plays an integral part in ranking and prominent link placement can help your site rise in the SERPS.

Not all links are valued equally, of course. An abundance of low-value, spam or non-pertinent links will quickly devalue your page in Google search. To get the best possible result, webmasters should keep in check the objective value of every backlink created.

To get the best possible result, webmasters should keep in check the objective value of every backlink created.

Let’s take a look at some of the factors that will have a strong influence on link building in 2017 (and beyond).

Content Is (Still) King

Before you go looking for backlinks for your site, you need to give people a reason to link to you. Content is a good place to start. Creating high-quality articles and blog posts that offer true value on the topic will get you noticed.

If you start getting organic backlinks from another site, it’s a proof of the genuine value of your content.

Google’s algorithm has become so advanced that it can actually detect the quality of your content. It’s no longer enough just to produce long, winding posts and hope it will stick due to the number of words you write.

The content on your site needs to be of the highest quality in order to get picked up by search engines and ranked high.

We’ve been hearing many stories about how longer pieces and more elaborate content gets the upper hand in rankings and that will only get more and more significant over time, but emphasis truly needs to be on the quality.

Filler content and keyword stuffing will sink your rankings fast.

Guest Post

Good old guest posting will probably never go out of fashion.

One of the most useful tactics you can use to generate backlinks and get traffic is guest posting on websites that support content syndication.

Content syndication is the practice of publishing a piece of content in multiple blogs. Most large publications have their syndication networks.

This is how they work with partner websites from the same niche, in order to republish trending posts on their blogs.

When the content is republished by them, these websites give credit and link to the partner or publisher’s website where they got the content from. Sometimes they even feature the author’s bio.

When you post on such a website, your guest post can be featured on some of the most popular blogs on the internet.

This means that more people will come across your work and bio, and you will gain more traffic on your website.

These websites promote the republished content on their social networks, which means that your guest post automatically gains more social engagement.

When you are featured on popular blogs, this increases your credibility. Also, when your content is syndicated, you will gain access to that blog’s network.

This means that once your outreach has become significant, you will be able to approach more blogs with confidence.

The Skyscraper Technique

The Skyscraper Technique, coined by Brian Dean, is a modern content-driven technique for link building. It is based on finding a piece of content in your niche that is already popular and well-received (a “proven linkable asset”) and looking for creative and unique ways to create better content with a similar message.

Once you have created the new content, you need to reach the right people that have already linked to similar content in order to put it out there.

There are three reasons why this technique works so well. The first reason is the fact that there is already a proven demand for the given content on the market.

Once you figure out why the content worked so well, you can improve on it and gain more success.

The second reason is that there is already a prime audience for the subject. If you create something better than the original, you have the chance to further entice the existing audience.

The third reason is that the existing content has already been well indexed on Google and has a high ranking. By creating better content, you can top the old one, outrank it and gain more traffic, especially with the quality back links you can get by reaching out.

Broken Link Building

One of the techniques that often yield great results is broken link building. Broken links happen when a page links to resources that are no longer available.

This is, of course, something every webmaster is looking for a way to fix since they are bound to generate a negative user experience.

Broken link building (also known as dead link building) comprises of finding a website that fits your niche that has one or more broken links, contacting the site’s webmaster in order to point out the links that aren’t working, and then asking them to link to your website in return.

It is essential that the content of the suggested replacement link is as close as possible to the original missing content. Finding a broken link and suggesting to replace it with your sales page is not the way to go.

If you do your job properly, this technique is a good solution for you to get quick links. It will bring you results much faster than, for example, a website owner trying out and reviewing your product.

Essentially, you are helping the website owner out before they help you out.

Keep It Relevant

Linking to sites relevant to your niche—and getting backlinks from them in return—is essential in creating the best response from Google, or any search engine’s algorithm.

Other search engines have similar algorithms so this applies to them as well. If you score high on Google’s search, you should also score high on Bing, Yahoo or Ask.

Backlinks from reliable sites in your niche show that your content is trustworthy and relevant on the given topic and in the eyes of Google, trust is an extremely strong factor.

If you gain enough backlinks from reputable sites in your niche, Google will start considering you as an authority on the subject.

Getting links from strong sites that have no relevance for your business might help you initially, but will only create problems down the road.

Links from seemingly less powerful, but more related sites will do you more good in the long run. Of course, any kind of spammy links should be avoided at all cost.

Track Your Backlinks

Like any other aspect of your business, backlinks need to be tracked to see how much effect they have and to optimize them accordingly.

You want to know the number of people that click on your links and how many people visit your site coming from a guest post on another site, for example, to be able to calculate your ROI.

Tracking and research can tell you how big of an effect your link building is having.

Keeping track of your backlinks on a regular basis also allows you to detect if a link goes bad or leads to a spam site. Monitoring your links and backlinks is an essential part of your link building strategy.

Stay the course

Building up a bank of valuable backlinks takes time. Once you have developed a strategy for generating content, it might take quite some time to really develop positive indications that your strategy is working.

SEO is a marathon game and you should definitely approach it from a long-term perspective. Building links take a lot of time and effort and building credibility takes even more.

Since content is time-consuming, many companies fail to allocate the time necessary to build a solid foundation of trust. Changing strategies in mid-campaign is not the answer.

Giving your content time to build and gain trust and respect is the best course for a successful long-term link building strategy.

Summing it all up

Sometimes even the best plans don’t work out precisely as intended. A source that was thought to be reliable might end up being garbage, backlinks that look legitimate can be cloaked to lead to spam sites and other problems exist.

These problems can be surmounted but the success of your link building strategy will largely depend on how much time you put into it.

Google is increasingly shifting its focus on the quality of the content and many webmasters are following along. Quantity is becoming more important, too.

A while ago, a ‘standard’ length of a guest post used to be 500-600 words, but now it’s closer to 800 or 1000 or even more.

All this leads us to a conclusion that Google is putting a greater focus on bigger, more resourceful posts which are able to generate organic backlinks due to the quality of information they provide.

It’s no longer enough to put together a couple of thoughts on the topic and call it done. You need to provide as much data as possible if you want the content to truly resonate with the readers and in the end, the search engines.

Sam Cyrus is CEO and co-founder of Agseosydney, an innovative online marketing agency based in Sydney which is focused on Digital Marketing. Sam is also a creative writer and his interests are entrepreneurship, business, online marketing, SEO and social media. He currently advises companies about Web Design in Sydney.

The post Link Building in 2017 - What You Should Know appeared first on Ninja Outreach.

from SM Tips By Minnie https://ninjaoutreach.com/link-building-2017/

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