Dark Web Drug Sales Show No Signs of Slowing
February 10, 2017
Business is apparently booming for Dark Web drug sales. Business Insider published an article that reports on this news: An in-depth new study shows that the online market for illegal drugs is skyrocketing. The study conducted by RAND Europe found the number of transactions on illegal drug sites has tripled since 2013, and revenues have almost doubled. Apparently, most of the shipping routes are within North America. The article tells us,
Elsewhere in the study, researchers found that wholesale transactions (which it categorised as sales worth over $1,000 [£770]) generated a quarter of total revenue for drug marketplaces. That figure was unchanged between 2013 and 2016, though. Cannabis was the most popular drug globally, making up 33% of drug marketplace transactions. But the report looked at sales to Holland specifically and found that it only made up 17% of transactions there. That’s likely because the sale of cannabis is legal in the country through licensed venues, reducing the need for people to use illegal online stores.
The year 2013 carries meaning because it was in fall 2013 that the Silk Road was shut down. This study suggests its closure did not eliminate Dark Web drug sales. As the article alludes to, as cannabis laws may or may not change in the United States, it will be interesting to see how this affects Dark web use and marketplace sales.
Megan Feil, February 10, 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
Alphabet Google Boston Dynamics
February 9, 2017
In June 2016, I thought that Alphabet Google was selling its Boston Dynamics’ robot outfit to Toyota. My source? The ever reliable USA Today. Then I learned that Toyota also wanted Google’s Schaft, another Google entity. Then nothing. Why do I care today? No reason. I just wondered what happened to the deal.
I learned that Boston Dynamics has invented a robot that can zip about on two wheels, go in the water, and jump over obstacles. Here’s a screen capture from “Leaked Video Reveals New Boston Dynamics Robot That Can Perform Amazing Stunts on Two Wheels.”
I like jumping robots, but my all time favorite is the holiday infused robot reindeer which probably terrified college students without access to a special room with dogs to pet and advisors to assist them through a mental crisis. In case you forgot, here’s a snap of the beasties:
I know that whether Alphabet Google, Toyota, or some other outfit buys Boston Dynamics, the robots will find useful things to do in law enforcement, intelligence gathering, warfighting. I suppose I should add baby sitting and working in primary school classrooms. Well, maybe not yet.
Stephen E Arnold, February 9, 2017
IBM on Cognitive Computing Safari in South Africa
February 9, 2017
The article on ZDNet titled IBM to Use AI to Tame Big Data in Its Second African Research Lab discusses the 12th global research unit IBM has opened. This one is positioned in South Africa for data analytics and cognitive computing as applied to healthcare and urban development. Dr. Solomon Assefa, IBM’s Director of Research for Africa, mentions in the article that the lab was opened in only 18 months. He goes on,
Assefa said the facility will combine industrial research with a startup incubator, working closely with Wits’ own entrepreneur accelerator in the same innovation hub, known as the Tshimologong Precinct. Tshimologong is part of a major urban renewal project by Wits and the City of Johannesburg.
Nowhere else in the world is there an innovation hub that houses a world class research lab,” Assefa said. “One thing we agreed on from the start is that we will make the lab accessible to startups and entrepreneurs in hub.
The lab is funded by a ten-year investment program of roughly $60M and maintains an open door policy with the University of the Witswatersrand (Wits), The Department of Trade and Industry, and the Department of Science and Technology. The immediate focuses of several early applications include Cape region forest fire prevention, disease monitoring, and virtual reality.
Chelsea Kerwin, 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
Semantics: Biting the Semantic Apple in the Garden of Search Subsystems
February 8, 2017
I love the Phoenix like behavior of search and content processing subsystems. Consider semantics or figuring out what something is about and assigning an index term to that aboutness. Semantics is not new, and it is not an end in itself. Semantic functions are one of the many Lego blocks which make up a functioning and hopefully semi accurate content processing and information accessing system.
I read “With Better Scaling, Semantic Technology Knocks on Enterprise’s Door.” The headline encapsulates decades of frustration for the champions of semantic solutions. The early bird vendors fouled the nest for later arrivals. As a result, nifty semantic technology makes a sales call and finds that those who bother to attend the presentation are [a] skeptical, [b] indifferent, [c] clueless, [d] unwilling to spend money for another career killer. Pick your answer.
For decades, yes, decades, enterprise search and content processing vendors have said whatever was necessary to close a deal. The operative concept was that the vendor could whip up a solution and everything would come up roses. Well, fly that idea by those who licensed Convera for video search, Fast Search for an intelligent system, or any of the other train wrecks that lie along the information railroad tracks.
This write up happily ignores the past and bets that “better” technology will make semantic functions accurate, easy, low cost, and just plain wonderful. Yep, the Garden of Semantics exists as long as the licensee has the knowledge, money, time, and personnel to deliver the farm fresh produce.
I noted this passage:
… semantics standards came out 15 or more years ago, but scalability has been an inhibitor. Now, the graph technology has taken off. Most of what people have been looking at it for is [online transactional processing]. Our focus has been on [online analytical processing] — using graph technology for analytics. What held graph technology back from doing analytics was the scaling problem. There was promise and hype over those years, but, at every turn, the scale just wasn’t there. You could see amazing things in miniature, but enterprises couldn’t see them at scale. In effect, we have taken our query technology and applied MPP technology to it. Now, we are seeing tremendous scales of data.
Yep, how much does it cost to shove Big Data through a computationally intensive semantic system? Ask a company licensing one of the industrial strength systems like Gotham or NetReveal.
Make sure you have a checkbook with a SPARQL enhanced cover and a matching pen with which to write checks appropriate to semantic processing of large flows of content. Some outfits can do this work and do it well. In my experience, most outfits cannot afford to tackle the job.
That’s why semantic chatter is interesting but often disappointing to those who chomp the semantic apple from the hot house of great search stuff. Don’t forget to gobble some cognitive chilies too.
Stephen E Arnold, February 8, 2017
More Semantic Search Cheerleading: My Ears Hurt
February 8, 2017
I read “Semantic Search. The Present and Future of Search Engine Optimization .” Let’s be clear. The point of this write up has zero to do with precision and recall. The goal strikes me as generating traffic. Period. Wrapping the blunt truth in semantic tinsel does not change the fact that providing on point information is not on the radar.
I noted this statement and circled it in wild and crazy pink:
SEO in the current times involves user intent to provide apt results which can help you to improve your online presence. Improvement is possible by emphasizing on various key psychological principles to attract readers; rank well and eventually expand business.
When I look for information, my intent is pretty clear to me. I have learned over the last 50 years that software is not able to assist me. May I give you an example from yesterday, gentle reader. I wanted information about Autonomy Kenjin, which became available in the late 1990s. It disappeared. Online was useless and the search systems I used either pointed me to board games, rock music, or Japanese culture. My intent is pretty clear to me. Intent to today’s search systems suck when it comes to my queries.
The write up points out that semantics will help out with “customer personality guiding SEO.” Maybe for Lady Gaga queries. For specialized, highly variable search histories, not a chance. Systems struggle to recognize the intent of highly idiosyncratic queries. Systems do best with big statistical globs. College students like pizza. This user belongs to a cluster of users labeled college students. Therefore, anyone in this cluster gets… pizza ads. Great stuff. Double cheese with two slices of baloney. Then there are keywords. Create a cluster, related terms to it. Bingo. Job done. Close enough for today’s good enough approach to indexing.
The real gems of the write up consist of admonitions to write about a relevant topic. Relevant to whom, gentle reader. The author, the reader, the advertiser? Include concepts. No problem. A concept to you might be a lousy word to describe something to me; for example, games and kenjin. And, of course, use keywords. Right, double talk and babble.
Semantic SEO. Great stuff. Cancel that baloney pizza order. I don’t feel well.
Stephen E Arnold, February 8, 2017
Gradescope Cuts Grading Time in Half, Makes Teachers Lives 50% More Bearable
February 8, 2017
The article titled Professors of the World, Rejoice: Gradescope Brings AI to Grading on Nvidia might more correctly be titled: TAs of the World, Rejoice! In my experience, those hapless, hardworking, underpaid individuals are the ones doing most of the grunt work on college campuses. Any grad student who has faced a stack of essays or tests when their “real work” is calling knows the pain and redundancy of grading. Gradescope is an exciting innovation that cuts the time spent grading in half. The article explains,
The AI isn’t used to directly grade the papers; rather, it turns grading into an automated, highly repeatable exercise by learning to identify and group answers, and thus treat them as batches. Using an interface similar to a photo manager, instructors ensure that the automatically suggested answer groups are correct, and then score each answer with a rubric. In this way, input from users lets the AI continually improve its future predictions.
The trickiest part of this technology was handwriting recognition, and the Berkeley team used a “recurrent neural network trained using the Tesla K40 and GEForce GTX 980 Ti GPUs.” Interestingly, the app was initially created at least partly to prevent cheating. Students have been known to alter their answers after the fact and argue a failure of grading, so a digital record of the paper is extremely useful. This might sound like the end of teachers, but in reality it is the beginning of a giant, global teacher party!
Chelsea Kerwin, February 8, 2017
The Game-Changing Power of Visualization
February 8, 2017
Data visualization may be hitting at just the right time. Data Floq shared an article highlighting the latest, Data Visualisation Can Change How We Think About The World. As the article mentions, we are primed for it biologically: the human eye and brain processes 10 to 12 separate images per second, comfortably. Considering the output, visualization provides the ability to rapidly incorporate new data sets, remove metadata and increase performance. Data visualization is not without challenge. The article explains,
Perhaps the biggest challenge for data visualisation is understanding how to abstract and represent abstraction without compromising one of the two in the process. This challenge is deep rooted in the inherent simplicity of descriptive visual tools, which significantly clashes with the inherent complexity that defines predictive analytics. For the moment, this is a major issue in communicating data; The Chartered Management Institute found that 86% of 2,000 financiers surveyed late 2013, were still struggling to turn volumes of data into valuable insights. There is a need, for people to understand what led to the visualisation, each stage of the process that led to its design. But, as we increasingly adopt more and more data this is becoming increasingly difficult.
Is data visualization changing how we think about the world, or is the existence of big data the culprit? We would argue data visualization is simply a tool to present data; it is a product rather than an impetus for a paradigm shift. This piece is right, however in bringing attention to the conflict between detail and accessibility of information. We can’t help but think the meaning is likely in the balancing of both.
Megan Feil, February 8, 2017
HonkinNews for 7 February 2017 Now Available
February 7, 2017
This week’s program highlights Google’s pre school and K-3 robot innovation from Boston Dynamics. In June 2016 we thought Toyota was purchasing the robot reindeer company. We think Boston Dynamics may still be part of the Alphabet letter set. Also, curious about search vendor pivots. Learn about two shuffles (Composite Software and CopperEye) which underscore why plain old search is a tough market. You will learn about the Alexa Conference and the winner of the Alexathon. Alexa seems to be a semi hot product. When will we move “beyond Alexa”? Social media analysis has strategic value? What vendor seems to have provided “inputs” to the Trump campaign and the Brexit now crowd? HonkinNews reveals the hot outfit making social media data output slick moves. We provide a run down of some semantic “news” which found its way to Harrod’s Creek. SEO, writing tips, and a semantic scorecard illustrate the enthusiasm some have for semantics. We’re not that enthusiastic, however. Google is reducing its losses from its big bets like the Loon balloon. How much? We reveal the savings, and it is a surprising number. And those fun and friendly robots. Yes, the robots. You can view the video at this link. Google Video provides a complete run down of the HonkinNews programs too. Just search for HonkinNews.
Kenny Toth, February 7, 2017
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