Finding Meaning in Snapchat Images, One Billion at a Time

February 27, 2017

The article on InfoQ titled Amazon Introduces Rekognition for Image Analysis explores the managed service aimed at the explosive image market. According to research cited in the article, over 1 billion photos are taken every single day on Snapchat alone, compared to the 80 billion total taken in the year 2000. Rekognition’s deep learning power is focused on identifying meaning in visual content. The article states,

The capabilities that Rekognition provides include Object and Scene detection, Facial Analysis, Face Comparison and Facial Recognition. While Amazon Rekognition is a new public service, it has a proven track record. Jeff Barr, chief evangelist at AWS, explains: Powered by deep learning and built by our Computer Vision team over the course of many years, this fully-managed service already analyzes billions of images daily. It has been trained on thousands of objects and scenes. Rekognition was designed from the get-go to run at scale.

The facial analysis features include markers for image quality, facial landmarks like facial hair and open eyes, and sentiment expressed (smiling = happy.) The face comparison feature includes a similarity score that estimates the likelihood of two pictures being of the same person. Perhaps the most useful feature is object and scene detection, which Amazon believes will help users find specific moments by searching for certain objects. The use cases also span vacation rental markets and travel sites, which can now tag images with key terms for improved classifications.

Chelsea Kerwin, February 27, 2017

Upgraded Social Media Monitoring

February 20, 2017

Analytics are catching up to content. In a recent ZDNet article, Digimind partners with Ditto to add image recognition to social media monitoring, we are reminded images reign supreme on social media. Between Pinterest, Snapchat and Instagram, messages are often conveyed through images as opposed to text. Capitalizing on this, and intelligence software company Digimind has announced a partnership with Ditto Labs to introduce image-recognition technology into their social media monitoring software called Digimind Social. We learned,

The Ditto integration lets brands identify the use of their logos across Twitter no matter the item or context. The detected images are then collected and processed on Digimind Social in the same way textual references, articles, or social media postings are analysed. Logos that are small, obscured, upside down, or in cluttered image montages are recognised. Object and scene recognition means that brands can position their products exactly where there customers are using them. Sentiment is measured by the amount of people in the image and counts how many of them are smiling. It even identifies objects such as bags, cars, car logos, or shoes.

It was only a matter of time before these types of features emerged in social media monitoring. For years now, images have been shown to increase engagement even on platforms that began focused more on text. Will we see more watermarked logos on images? More creative ways to visually identify brands? Both are likely and we will be watching to see what transpires.

Megan Feil, February 20, 2017

 

Why Do We Care More About Smaller Concerns? How Quantitative Numbing Impacts Emotional Response

February 14, 2017

The affecting article on Visual Business Intelligence titled When More is Less: Quantitative Numbing explains the phenomenon that many of us have probably witnessed on the news, in our friends and family, and even personally experienced in ourselves. A local news story about the death of an individual might provoke a stronger emotional response than news of a mass tragedy involving hundreds or thousands of deaths. Scott Slovic and Paul Slovic explore this in their book Numbers and Nerves. According to the article, this response is “built into our brains.” Another example explains the Donald Trump effect,

Because he exhibits so many examples of bad behavior, those behaviors are having relatively little impact on us. The sheer number of incidents creates a numbing effect. Any one of Trump’s greedy, racist, sexist, vulgar, discriminatory, anti-intellectual, and dishonest acts, if considered alone, would concern us more than the huge number of examples that now confront us. The larger the number, the lesser the impact…This tendency… is automatic, immediate, and unconscious.

The article suggests that the only reason to overcome this tendency is to engage with large quantities in a slower, more thoughtful way. An Abel Hertzberg quote helps convey this approach when considering the large-scale tragedy of the Holocaust: “There were not six million Jews murdered: there was one murder, six million times.” The difference between that consideration of individual murders vs. the total number is stark, and it needs to enter into the way we process daily events that are happening all over the world if we want to hold on to any semblance of compassion and humanity.

Chelsea Kerwin, February 14, 2017

Data Mining Firm Cambridge Analytica Set to Capture Trump White House Communications Contract and Trump Organization Sales Contract

February 13, 2017

The article titled Data Firm in Talks for Role in White House Messaging — And Trump Business on The Guardian discusses the future role of Cambridge Analytica in both White House communication and the Trump Organization as well. Cambridge Analytica is a data company based out of London that boasts crucial marketing and psychological data on roughly 230 million Americans. The article points out,

Cambridge’s data could be helpful in both “driving sales and driving policy goals”, said the digital source, adding: “Cambridge is positioned to be the preferred vendor for all of that.”… The potential windfall for the company comes after the Mercers and Cambridge played key roles in Trump’s victory. Cambridge Analytica was tapped as a leading campaign data vendor as the Mercers… The Mercers reportedly pushed for the addition of a few top campaign aides, including Bannon and Kellyanne Conway, who became campaign manager.

Robert Mercer is a major investor in Cambridge Analytica as well as Breitbart News, Steve Bannon’s alt-right news organization. Steve Bannon is also on the board of Cambridge Analytica. The entanglements mount. Prior to potentially snagging these two wildly conflicting contracts, Cambridge Analytica helped Trump win the presidency with their data modeling and psychological profiling that focuses on building intimate relationships between brands and consumers to drive action.

Chelsea Kerwin, February 13, 2017

Cambridge Analytica: Applied Big Data

February 9, 2017

Cambridge University, not Stanford or Carnegie Mellon, is one of the academic institutions responsible for some of the most interesting content processing innovations. I often point to Cambridge’s role in the second world war. The magic of Bayesian statistics was a bit of a specialty for the fuddy duddies trundling near the banks of the Cam. i2 Group, Autonomy, and a host of other next generation content processing outfits took root and grew. Silicon Valley did not notice.

I was reminded of Cambridge’s role in figuring out what insights can be weaseled from algorithmic content processing when I read “The Data That Turned the World Upside Down.” The focus in the article is on the victory of Donald Trump, the dark art of psychometrics, and an outfit called Cambridge Analytica. You can get more information about the firm at this link.

The write up focuses on the dangers of making sense of Big Data. That’s okay, but danger may be in the eye of the beholder. The most interesting part of the write up was the realization that Facebook actions could provide clues to behavior. Interesting. Because systems which make sense of Facebook and Twitter content have been around for years. Moreover, these systems have been integrated into larger analytical platforms in wide use by law enforcement and intelligence entities for a while.

I learned from the write up:

Our smartphone…is a vast psychological questionnaire that we are constantly filling out, both consciously and unconsciously.

There you go. Sudden insight.

To learn how Donald Trump and politicians for Brexit used outputs from Cambridge Analytica, check out the source article.

Keep in mind that this method is not new. Over and out. Don’t forget to twitch your mantle blue. Sorrowful, no.

Stephen E Arnold, February 9, 2017

Presenting Watson as a Service

February 9, 2017

Every now and then, interest in Watson re-emerges. Forbes published a long-read recently entitled How IBM Is Building A Business Around Watson. After gaining press during Watson’s victorious Jeopardy face-off with Ken Jennings, Watson’s first commercial applications took off. IBM sold it to Memorial Sloan Kettering Cancer Center and Wellpoint to design an advisory system for its medical staff. Other medical institutions have purchased it since then. The author asserts,

Still, the potentially is undeniable. Think about how much more effective an ordinary doctor can be with Watson as an assistant. First, even before the patient enters the room, it can analyze their personal medical history, which often runs to hundreds of pages. Then, it can compare the case history with the 700,000 academic papers published every year as well as potentially millions of other patient records. All of this is, of course, beyond the capabilities of human doctors, who typically only get a few minutes to prepare for each examination. So being able to consult with Watson will be enormously helpful.

The real value is offering Watson as a service by providing its API, so that developers in organizations can develop their own applications using its technology. Over 550 partners are utilizing this currently for everything from retail to geolocation to travel agencies. Certainly, with all the hype Watson receives, we can only expect usage to grow.

Megan Feil, February 9, 2017

 

How to Quantify Culture? Counting the Bookstores and Libraries Is a Start

February 7, 2017

The article titled The Best Cities in the World for Book Lovers on Quartz conveys the data collected by the World Cities Culture Forum. That organization works to facilitate research and promote cultural endeavors around the world. And what could be a better measure of a city’s culture than its books? The article explains how the data collection works,

Led by the London mayor’s office and organized by UK consulting company Bop, the forum asks its partner cities to self-report on cultural institutions and consumption, including where people can get books. Over the past two years, 18 cities have reported how many bookstores they have, and 20 have reported on their public libraries. Hong Kong leads the pack with 21 bookshops per 100,000 people, though last time Buenos Aires sent in its count, in 2013, it was the leader, with 25.

New York sits comfortably in sixth place, but London, surprisingly, is near the bottom of the ranking with roughly 360 bookstores. Another measure the WCCF uses is libraries per capita. Edinburgh of all places surges to the top without any competition. New York is the only US city to even make the cut with an embarrassing 2.5 libraries per 100K people. By contrast, Edinburgh has 60.5 per 100K people. What this analysis misses out on is the size and beauty of some of the bookstores and libraries of global cities. To bask in these images, visit Bookshelf Porn or this Mental Floss ranking of the top 7 gorgeous bookstores.

Chelsea Kerwin, February 7, 2017

Visualizing a Web of Sites

February 6, 2017

While the World Wide Web is clearly a web, it has not traditionally been presented visually as such. Digital Trends published an article centered around a new visualization of Wikipedia, Race through the Wikiverse for your next internet search. This web-based interactive 3D visualization of the open source encyclopedia is at Wikiverse.io. It was created by Owen Cornec, a Harvard data visualization engineer. It pulls about 250,000 articles from Wikipedia and makes connections between articles based on overlapping content. The write-up tells us,

Of course it would be unreasonable to expect all of Wikipedia’s articles to be on Wikiverse, but Cornec made sure to include top categories, super-domains, and the top 25 articles of the week.

Upon a visit to the site, users are greeted with three options, each of course having different CPU and load-time implications for your computer: “Light,” with 50,000 articles, 1 percent of Wikipedia, “Medium,” 100,000 articles, 2 percent of Wikipedia, and “Complete,” 250,000 articles, 5 percent of Wikipedia.

Will this pave the way for web-visualized search? Or, as the article suggests, become an even more exciting playing field for The Wikipedia Game? Regardless, this advance makes it clear the importance of semantic search. Oh, right — perhaps this would be a better link to locate semantic search (it made the 1 percent “Light” cut).

Megan Feil, February 6, 2017

Counter Measures to Money Laundering

January 30, 2017

Apparently, money laundering has become a very complicated endeavor, with tools like Bitcoin “washers” available via the Dark Web. Other methods include trading money for gaming or other virtual currencies and “carding.”  ZDNet discusses law enforcement’s efforts to keep up in, “How Machine Learning Can Stop Terrorists from Money Laundering.”

It will not surprise our readers to learn authorities are turning to machine learning to cope with new money laundering methods. Reporter Charlie Osborne cites the CEO of cybersecurity firm ThetaRay, Mark Gazit, when she writes:

By taking advantage of Big Data, machine learning systems can process and analyze vast streams of information in a fraction of the time it would take human operators. When you have millions of financial transactions taking place every day, ML provides a means for automated pattern detection and potentially a higher chance of discovering suspicious activity and blocking it quickly. Gazit believes that through 2017 and beyond, we will begin to rely more on information and analytics technologies which utilize machine learning to monitor transactions and report crime in real time, which is increasingly important if criminals are going to earn less from fraud, and terrorism groups may also feel the pinch as ML cracks down on money laundering.

Of course, criminals will not stop improving their money-laundering game, and authorities will continue to develop tools to thwart them. Just one facet of the cybersecurity arms race.

Cynthia Murrell, January 30, 2017

Bing Gets Nostalgic

January 25, 2017

In my entire life, I have never seen so many people who were happy to welcome in a New Year.  2016 will be remembered for violence, political uproar, and other stuff that people wish to forget.  Despite the negative associations with 2016, other stuff did happen and looking back might offer a bit of nostalgia for the news and search trends of the past year.  On MSFT runs down a list of what happened on Bing in 2016,“Check Out The Top Search Trends On Bing This Past Year.”

Rather than focusing on a list of just top searches, Bing’s top 2016 searches are divided into categories: video games, Olympians, viral moments, tech trends, and feel good stories.  More top searches are located over at Bing page.  However, on the top viral trends it is nice to see that cat videos have gone down in popularity:

Ryder Cup heckler

Villanova’s piccolo girl

Powerball

Aston Martin winner

Who’s the mom?

Evgenia Medvedeva

Harambe the gorilla

#DaysoftheWeek

Cats of the Internet

Pokemon Go

On a personal level, I am surprised that Harambe the gorilla outranked Pokemon Go.  Some of these trends I do not even remember making the Internet circuit and I was on YouTube and Reddit for all of 2016.  I have been around enough years to recognize that things come and go and 2016 might have come off as a bad year for many, in reality, it was another year.  It also did not forecast doomsday.  That was back in 2000, folks.  Get with the times!

Whitney Grace, January 25, 2017

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