In this introduction to the basic steps of market research, the reader can find help with framing the research question, figuring out which approach to data collection to use, how best to analyze the data, and how to structure the market research findings and share them with clients.

The market research process consists of six discrete stages or steps. They are as follows:

The third step of market research - - Collect the Data or Information - entails several important decisions. One of the first things to consider at this stage is how the research participants are going to be contacted. There was a time when survey questionnaires were sent to prospective respondent via the postal system. As you might imagine, the response rate was quite low for mailed surveys, and the initiative was costly.

Telephone surveys were also once very common, but people today let their answering machines take calls or they have caller ID, which enables them to ignore calls they don't want to receive. Surprisingly, the Pew Foundation conducts an amazingly large number of surveys, many of which are part of longitudinal or long-term research studies.

Large-scale telephone studies are commonly conducted by the Pew researchers and the caliber of their research is top-notch.

Some companies have issued pre-paid phone cards to consumers who are asked to take a quick survey before they use the free time on the calling card. If they participate in the brief survey, the number of free minutes on their calling card is increased.

Some of the companies that have used this method of telephone surveying include Coca-Cola, NBC, and Amaco.

Methods of Interviewing

In-depth interviews are one of the most flexible ways to gather data from research participants. Another advantage of interviewing research participants in person is that their non-verbal language can be observed, as well as other attributes about them that might contribute to a consumer profile. Interviews can take two basic forms: Arranged interviews and intercept interviews.

Arranged interviews are time-consuming, require logistical considerations of planning and scheduling, and tend to be quite expensive to conduct. Exacting sampling procedures can be used in arranged interviews that can contribute to the usefulness of the interview data set. In addition, the face-to-face aspect of in-depth interviewing can result in exposure to interviewer bias, so training of interviewers necessarily becomes a component of an in-depth interviewing project.

Intercept interviews take place in shopping malls, on street corners, and even at the threshold of people's homes. With intercept interviews, the sampling is non-probabilistic. For obvious reasons, intercept interviews must be brief, to the point, and not ask questions that are off-putting.

Otherwise, the interviewer risks seeing the interviewee walk away. One version of an intercept interview occurs when people respond to a survey that is related to a purchase that they just made. Instructions for participating in the survey are printed on their store receipt and, generally, the reward for participating is a free item or a chance to be entered in a sweepstakes.

Online data collection is rapidly replacing other methods of accessing consumer information. Brief surveys and polls are everywhere on the Web. Forums and chat rooms may be sponsored by companies that wish to learn more from consumers who volunteer their participation. Cookies and clickstream data send information about consumer choices right to the computers of market researchers. Focus groups can be held online and in anonymous blackboard settings.

Market research has become embedded in advertising on digital platforms.

There are still many people who do not regularly have access to the Internet. Providing internet access for people who do not have connections at home or are intimidated by computing or networking can be fruitful. Often, the novelty of encountering an online market research survey or poll that looks like and acts like a game is incentive enough to convert reticent Internet users.

Characteristics of Data Collection

Data collection strategies are closely tied to the type of research that is being conducted as the traditions are quite strong and have resilient philosophical foundations. In the rapidly changing field of market research, these traditions are being eroded as technology makes new methods available. The shift to more electronic means of surveying consumers is beneficial in a number of ways. Once the infrastructure is in place, digital data collection is rapid, relatively error-free, and often fun for consumers. Where data collection is still centralized, market researchers can eliminate the headache of coding data by inputting responses into computers or touch screens. The coding is instantaneous and the data analysis is rapid.

Regardless of how data is collected, the human element is always important. It may be that the expert knowledge of market researchers shifts to different places in the market research stream. For example, the expert knowledge of a market researcher is critically important in the sophisticated realm of Bayesian Networks simulation and structured equation modeling -- two techniques that are conducted through computer modeling. Intelligently designed market research requires planning regardless of the platform. The old adage still holds true: Garbage in, garbage out.

Now you are ready to take a look at the market research process Step 4. Analyze the Data.


Kotler, P. (2003). Marketing Management (11th ed.). Upper Saddle River, NJ: Pearson Education, Inc., Prentice Hall.

Lehmann, D. R. Gupta, S., and Seckel, J. (1997). Market Research. Reading, MA: Addison-Wesley

Categorized in Market Research

The CIA is developing AI to advance data collection and analysis capabilities. These technologies are, and will continue to be, used for social media data.


The United States Central Intelligence Agency (CIA) requires large quantities of data, collected from a variety of sources, in order to complete investigations. Since its creation in 1947, intel has typically been gathered by hand. The advent of computers has improved the process, but even more modern methods can still be painstakingly slow. Ultimately, these methods only retrieve minuscule amounts of data when compared what artificial intelligence (AI) can gather.

According to information revealed by Dawn Meyerriecks, the deputy director for technology development with the CIA, the agency currently has 137 different AI projects underway. A large portion of these ventures are collaborative efforts between researchers at the agency and developers in Silicon Valley. But emerging and developing capabilities in AI aren’t just allowing the CIA more access to data and a greater ability to sift through it. These AI programs have taken to social media, combing through countless public records (i.e. what you post online). In fact, a massive percentage of the data collected and used by the agency comes from social media. 

As you might know or have guessed, the CIA is no stranger to collecting data from social media, but with AI things are a little bit different, “What is new is the volume and velocity of collecting social media data,” said Joseph Gartin, head of the CIA’s Kent School. And, according to Chris Hurst, the chief operating officer of Stabilitas, at the Intelligence Summit, “Human behavior is data and AI is a data model.”


According to Robert Cardillo, director of the National Geospatial-Intelligence Agency, in a June speech, “If we were to attempt to manually exploit the commercial satellite imagery we expect to have over the next 20 years, we would need eight million imagery analysts.” He went on to state that the agency aims to use AI to automate about 75% of the current workload for analysts. And, if they use self-improving AIs as they hope to, this process will only become more efficient.

While countries like Russia are still far behind the U.S. in terms of AI development, especially as it pertains to intelligence, there seems to be a global push — if not a race — forward.  Knowledge is power, and creating technology capable of extracting, sorting, and analyzing data faster than any human or other AI system could is certainly sounds like a fast track to the top.  As Vladimir Putin recently stated on the subject of AI, “Whoever becomes the leader in this sphere will become the ruler of the world.”

Source: This article was published futurism.com By Chelsea Gohd

Categorized in Internet Technology
  • Fireball steals sensitive user data and manipulates regular surfing data
  • CERT-In has issued its latest advisory to Internet users
  • It said the virus can be detected by majority of anti-virus solution

Cyber-security sleuths have alerted Internet users against the destructive activity of a browser-attacking virus- 'Fireball'- that steals sensitive user data and manipulates regular surfing activity.

The malware has been spreading across the globe and possesses over two dozen aliases and spreads by bundling and "without the user's consent".

"It has been reported that a malware named as 'Fireball' targeting browsers is spreading worldwide.

"It has the ability to collect user information, manipulate web-traffic to generate ad-revenue, malware dropping and executing malicious code on the infected machines," the Computer Emergency Response Team of India (CERT-In) said in its latest advisory to Internet users.

The CERT-In is the nodal agency to combat hacking, phishing and to fortify security-related defences of the Indian Internet domain.

The agency said the malware or the virus can be "detected by majority of the anti-virus solutions" and it has advised Internet users to install updated anti-virus solutions to protect their computers from this infection.

It said the virus, 'Fireball', "currently installs plug-ins and additional configurations to boost its advertisements but it could be used as distributor for any additional malware in future."

"It is reported that the malware 'Fireball' is used by one of the largest marketing agency to manipulate the victims' browsers and changes their default search engines and home pages into fake search engines.

"It also re-directs the queries to either yahoo.com or Google.com. The fake search engines also collects the users' private information," the advisory said.

'Fireball', it said, is capable of acting as a browser-hijacker, manipulating web traffic to generate ad-revenue, capable of downloading further malware, capable of executing any malicious code on the victim machine and collects user information and steals credentials from the victim machine.

The CERT-In has also suggested some counter-measures: "Do not click on banners or pop-up or ads notifications, do not visit untrusted websites and do not download or open attachment in emails received from untrusted sources or unexpectedly received from trusted users."

It said a user, in order to exercise caution after logging-in the system, should check for default setting of web browsers, such as homepage, search engine, browser extensions and plug-ins installed, and if something is found unknown, then it should be deleted.

Source: This article was published gadgets.ndtv

Categorized in Internet Privacy

INDIANAPOLIS -- Analyzing millions of internet searches tied to major societal events offers a new way to understand public reaction to those events, according to new research from the Richard M. Fairbanks School of Public Health at Indiana University-Purdue University Indianapolis.

In what's believed to be the first study to examine the issue, the IUPUI researchers focused on the public's reaction to the Sandy Hook Elementary School shootings in 2012 in Newtown, Connecticut, to test their approach.

Nir Menachemi, a professor and the department chair of health policy and management in the School of Public Health, and researchers Saurabh Rahurkar and Mandar Rahurkar analyzed 5.6 million firearm-related search queries from the Yahoo search engine that occurred two weeks before and two weeks after the shootings.

"We wanted to understand how firearm-related information-seeking, such as looking up relevant laws and learning about advocacy, and web-based behavior, such as visits to firearm retailers, changed immediately after the event," Menachemi said.

Given the amount of data involved, this approach was unimaginable in the past. The researchers went through the 5.6 million firearm-related searches several times to get to the queries used in the study.

"This data is a hidden gem to be added to the arsenal of public health," Menachemi said.

One of the key findings of the analysis was that firearm-related searches more than doubled immediately after the Sandy Hook shooting incident.

Overall, retail websites were the most visited sites, followed by searches for gun types and ammunition. Gun type and ammunition searches had a two- to threefold increase after the shooting incident.

The researchers discovered that most people were getting information from entities that advocate -- either pro-gun or pro-gun control -- rather than from more neutral entities like government or educational websites.

Understanding firearm-related search trends to gain insight into how Americans responded to the Sandy Hook incident can enhance societal debates and inform policy development related to firearms, Menachemi said.

"Now that we have this information, the question is, what can we do with it?" he said.

In the Sandy Hook study, queries can be matched with particular states or smaller geographic areas to see whether searches from politically conservative, or "red," states differ from searches from "blue" states.

"That creates an opportunity to better understand what might be influencing behavior, allowing advocates to intervene with appropriate education content or be better able to react to what information people need," Menachemi said.

Menachemi noted that there are many different areas in which this type of information may improve public health and public health education.

"When we had fears around Ebola, understanding what people worried about could have been extremely helpful to a public health response," Menachemi said. "More recently with Zika, this type of data would give valuable information about what doctors, nurses and front-line clinical staff -- and policymakers -- could do or use to improve their responses to what people are experiencing."

The study, "Using Web-Based Search Data to Study the Public's Reactions to Societal Events: The Case of the Sandy Hook Shooting," was published in JMIR Public Health and Surveillance.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Source: This article was published on eurekalert.org by INDIANA UNIVERSITY

Categorized in Search Engine

Google Cloud launched a new Internet of Things management service today called Google Cloud IoT Core that provides a way for companies to manage IoT devices and process data being generated by those devices.

A transportation or logistics firm, for example, could use this service to collect data from its vehicles and combine it with other information like weather, traffic and demand to place the right vehicles at the right place at the right time.

By making this into a service, Google is not only keeping up with AWS and Microsoft, which have similar services, it is tapping into a fast-growing market. In fact, a Google Cloud spokesperson said the genesis of this service wasn’t so much about keeping up with its competitors — although that’s clearly part of it — it was about providing a service its cloud customers were increasingly demanding.

That’s because more and more companies are dealing with tons of data coming from devices large and small, whether a car or truck or tiny sensors sitting on an MRI machine or a machine on a manufacturer’s shop floor. Just validating the devices, then collecting the data they are generating is a huge undertaking for companies.

Google Cloud IoT Core is supposed to help deal with all of that by removing a level of complexity associated with managing all of these devices and data. By packaging this as a service, Google is trying to do a lot of the heavy lifting for customers, providing them with the infrastructure and services they need to manage the data, using Google’s software services like Google Cloud Dataflow, Google BigQuery, and Google Cloud Machine Learning Engine. Customers can work with third-party partners like ARM, Intel and Sierra Wireless for their IoT hardware and Helium, Losant or Tellmeplus for building their applications.

Photo: Google Cloud

While the company bills itself as the more open alternative to competitors like AWS and Microsoft Azure, this IoT service is consistent with Google’s overall strategy to let customers use both its core cloud services and whatever other services they choose to bring to the process, whether they are from Google itself or from a third party.


The solution consists of two main pieces. First there is a device manager for registering each of the “things” from which you will be collecting data. This can be done manually through a console or programmatically to register the devices in a more automated fashion, which is more likely in scenarios involving thousands or even tens of thousands of devices.

As Google describes it, the device manager establishes the identity of a device and provides a mechanism for authenticating it as it connects to the cloud, while maintaining a configuration for each device that helps the Google Cloud service recognize it.

The second piece is a “protocol bridge,” which provides a way to communicate using standard protocols between the “things” and the Google Cloud service. It includes native support for secure connection over MQTT, an industry-standard IoT protocol, according to the company.

Once the device is registered and the data is moved across the protocol bridge, it can flow through processing and eventually visualization or use in an application.

Source: This article was published techcrunch.com By Ron Miller

Categorized in Search Engine

Back in February, we learned from a security researcher that various iOS apps can secretly leak login data and other personal information to hackers that know how iOS works, and how to take advantage of various flaws. Three months later, it looks like many of these apps, including mobile banking applications, have not been fixed.

Sudo Security Group Will Strafach explained that no less than 76 apps were susceptible to man-in-the-middle attacks, including banking and medical apps. Hackers could fool these apps into leaking a user’s login details, without the user knowing.

You’d think app developers would go ahead and fix their apps following the notice. It turns out some of them have done so, including HipChat and Foxit. But ZDNet reports that many others haven’t taken action. 

minor update: more of these are fixed now, such as Atlassian HipChat for iOS (CVE-2017-8058) and Foxit PDF Reader for iOS (CVE-2017-8059) https://twitter.com/chronic/status/828724931773026305 … 

The majority of the apps that can leak user data will still expose login info have not been fixed, including banking apps Emirates NBD, 21st Century Insurance, Think Mutual Bank, and Space Coast Credit Union, to name just a few.

Other apps including private web browser Dolphin Web Browser, blood glucose level Diabetes in Check, and an app that allows Indiana residents to vote are still affected by the hack.

There’s no indication anyone is abusing this iOS security flaw, but that’s not a good excuse for any app developer not to fix the issues. If you still have to use any of this apps, Strafach advises to avoid Wi-Fi networks and use your cellular plan instead.

Source : This article was published in bgr.com By Chris Smith

Categorized in Others

Much of the data of the World Wide Web hides like an iceberg below the surface. The so-called 'deep web' has been estimated to be 500 times bigger than the 'surface web' seen through search engines like Google. For scientists and others, the deep web holds important computer code and its licensing agreements. Nestled further inside the deep web, one finds the 'dark web,' a place where images and video are used by traders in illicit drugs, weapons, and human trafficking. A new data-intensive supercomputer called Wrangler is helping researchers obtain meaningful answers from the hidden data of the public web.

The Wrangler supercomputer got its start in response to the question, can a computer be built to handle massive amounts of I/O (input and output)? The National Science Foundation (NSF) in 2013 got behind this effort and awarded the Texas Advanced Computing Center (TACC), Indiana University, and the University of Chicago $11.2 million to build a first-of-its-kind data-intensive supercomputer. Wrangler's 600 terabytes of lightning-fast flash storage enabled the speedy reads and writes of files needed to fly past big data bottlenecks that can slow down even the fastest computers. It was built to work in tandem with number crunchers such as TACC's Stampede, which in 2013 was the sixth fastest computer in the world.

While Wrangler was being built, a separate project came together headed by the Defense Advanced Research Projects Agency (DARPA) of the U.S. Department of Defense. Back in 1969, DARPA had built the ARPANET, which eventually grew to become the Internet, as a way to exchange files and share information. In 2014, DARPA wanted something new - a search engine for the deep web. They were motivated to uncover the deep web's hidden and illegal activity, according to Chris Mattmann, chief architect in the Instrument and Science Data Systems Section of the NASA Jet Propulsion Laboratory (JPL) at the California Institute of Technology.

"Behind forms and logins, there are bad things. Behind the dynamic portions of the web like AJAX and Javascript, people are doing nefarious things," said Mattmann. They're not indexed because the web crawlers of Google and others ignore most images, video, and audio files. "People are going on a forum site and they're posting a picture of a woman that they're trafficking. And they're asking for payment for that. People are going to a different site and they're posting illicit drugs, or weapons, guns, or things like that to sell," he said.

Mattmann added that an even more inaccessible portion of the deep web called the 'dark web' can only be reached through a special browser client and protocol called TOR, The Onion Router. "On the dark web," said Mattmann, "they're doing even more nefarious things." They traffic in guns and human organs, he explained. "They're basically doing these activities and then they're tying them back to terrorism."

In response, DARPA started a program called Memex. Its name blends 'memory' with 'index' and has roots to an influential 1945 Atlantic magazine article penned by U.S. engineer and Raytheon founder Vannevar Bush. His futuristic essay imagined making all of a person's communications - books, records, and even all spoken and written words - in fingertip reach. The DARPA Memex program sought to make the deep web accessible. "The goal of Memex was to provide search engines the information retrieval capacity to deal with those situations and to help defense and law enforcement go after the bad guys there," Mattmann said.

Karanjeet Singh is a University of Southern California graduate student who works with Chris Mattmann on Memex and other projects. "The objective is to get more and more domain-specific (specialized) information from the Internet and try to make facts from that information," said Singh said. He added that agencies such as law enforcement continue to tailor their questions to the limitations of search engines. In some ways the cart leads the horse in deep web search. "Although we have a lot of search-based queries through different search engines like Google," Singh said, "it's still a challenge to query the system in way that answers your questions directly."

Once the Memex user extracts the information they need, they can apply tools such as named entity recognizer, sentiment analysis, and topic summarization. This can help law enforcement agencies like the U.S. Federal Bureau of Investigations find links between different activities, such as illegal weapon sales and human trafficking, Singh explained.

"Let's say that we have one system directly in front of us, and there is some crime going on," Singh said. "The FBI comes in and they have some set of questions or some specific information, such as a person with such hair color, this much age. Probably the best thing would be to mention a user ID on the Internet that the person is using. So with all three pieces of information, if you feed it into the Memex system, Memex would search in the database it has collected and would yield the web pages that match that information. It would yield the statistics, like where this person has been or where it has been sited in geolocation and also in the form of graphs and others."

"What JPL is trying to do is trying to automate all of these processes into a system where you can just feed in the questions and and we get the answers," Singh said. For that he worked with an open source web crawler called Apache Nutch. It retrieves and collects web page and domain information of the . The MapReduce framework powers those crawls with a divide-and-conquer approach to big data that breaks it up into small pieces that run simultaneously. The problem is that even the fastest computers like Stampede weren't designed to handle the input and output of millions of files needed for the Memex project.

The World Wide Web is like an iceberg, with most of its data hidden below the surface. There lies the 'deep web,' estimated at 500 times bigger than the 'surface web' that most people see through search engines like Google. A innovative

The Wrangler data-intensive supercomputer avoids data overload by virtue of its 600 terabytes of speedy flash storage. What's more, Wrangler supports the Hadoop framework, which runs using MapReduce. "Wrangler, as a platform, can run very large Hadoop-based and Spark-based crawling jobs," Mattmann said. "It's a fantastic resource that we didn't have before as a mechanism to do research; to go out and test our algorithms and our new search engines and our crawlers on these sites; and to evaluate the extractions and analytics and things like that afterwards. Wrangler has been an amazing resource to help us do that, to run these large-scale crawls, to do these type of evaluations, to help develop techniques that are helping save people, stop crime, and stop terrorism around the world."

Singh and Mattmann don't just use Wrangler to help fight crime. A separate project looks for a different kind of rule breaker. The Distributed Release Audit Tool (DRAT) audits software licenses of massive code repositories, which can store hundreds of millions of lines of code and millions of files. DRAT got its start because DARPA needed to audit the massive code repository of its national-scale 100-million-dollar-funded presidential initiative called XDATA. Over 60 different kinds of software licenses exist that authorize the use of code. What got lost in the shuffle of XDATA is whether developers followed DARPA guidelines of permissive and open source licenses, according to Chris Mattmann.

Mattmann's team at NASA JPL initially took the job on with an Apache open source tool called RAT, the Release Audit Tool. Right off the bat, big problems came up working with the big data. "What we found after running RAT on this very large code repository was that after about three or four weeks, RAT still hadn't completed. We were running it on a supercomputer, a very large cloud computer. And we just couldn't get it to complete," Mattmann said. Some other problems with RAT bugged the team. It didn't give status reports. And RAT would get hung up checking binary code - the ones and zeroes that typically just hold data such as video and were not the target of the software audit.

Mattmann's team took RAT and tailored it for parallel computers with a distributed algorithm, mapping the problem into small chunks that run simultaneously over the many cores of a supercomputer. It's then reduced into a final result. The MapReduce workflow runs on top of the Apache Object Oriented Data Technology, which integrates and processes scientific archives.

The distributed version of RAT, or DRAT, was able to complete the XDATA job in two hours on a Mac laptop that previously hung up a 24-core, 48 GB RAM supercomputer at NASA for weeks. DRAT was ready for even bigger challenges.

"A number of other projects came to us wanting to do this," Mattmann said. The EarthCube project of the National Science Foundation had a very large climate modeling repository and sought out Mattmann's team. "They asked us if all these scientists are putting licenses on their code, or whether they're open source, or if they're using the right components. And so we did a very big, large auditing for them," Mattmann said.

"That's where Wrangler comes in," Karanjeet Singh said. "We have all the tools and equipment on Wrangler, thanks to the TACC team. What we did was we just configured our DRAT tool on Wrangler and ran distributedly with the compute nodes in Wrangler. We scanned whole Apache SVN repositories, which includes all of the Apache open source projects."

The project Mattmann's team is working on early 2017 is to run DRAT on the Wrangler supercomputer over historically all of the code that Apache has developed since its existence - including over 200 projects with over two million revisions in a code repository on the order of hundreds of millions to billions of files.

"This is something that's only done incrementally and never done at that sort of scale before. We were able to do it on Wrangler in about two weeks. We were really excited about that," Mattmann said.

Apache Tika formed one of the key components to the success of DRAT. It discerns Multipurpose Internet Mail Extensions (MIME) file types and extracts its metadata, the data about the data. "We call Apache Tika the 'babel fish,' like 'The Hitchhiker's Guide to the Galaxy,'" Mattmann said. "Put the babel fish to your ear to understand any language. The goal with Tika is to provide any type of file, any file found on the Internet or otherwise to it and it will understand it for you at the other end...A lot of those investments and research approaches in Tika have been accelerated through these projects from DARPA, NASA, and the NSF that my group is funded by," Mattmann said.

When data's deep, dark places need to be illuminated

File type breakdown of XDATA. Credit: Chris Mattmann

"A lot of the metadata that we're extracting is based on these machine-learning, clustering, and named-entity recognition approaches. Who's in this image? Or who's it talking about in these files? The people, the places, the organizations, the dates, the times. Because those are all very important things. Tika was one of the core technologies used - it was one of only two - to uncover the Panama Papers global controversy of hiding money in offshore global corporations," Mattmann said.

Chris Mattmann, the first NASA staffer to join the board of the Apache Foundation, helped create Apache Tika, along with the scalable text search engine Apache Lucerne and the search platform Apache Solr. "Those two core technologies are what they used to go through all the leaked (Panama Papers) data and make the connections between everybody - the companies, and people, and whatever," Mattmann said.

Mattmann gets these core technologies to scale up on supercomputers by 'wrapping' them up on the Apache Spark framework software. Spark is basically an in-memory version of the Apache Hadoop capability MapReduce, intelligently sharing memory across the compute cluster. "Spark can improve the speed of Hadoop type of jobs by a factor of 100 to 1,000, depending on the underlying type of hardware," Mattmann said.

"Wrangler is a new generation system, which supports good technologies like Hadoop. And you can definitely run Spark on top of it as well, which really solves the new technological problems that we are facing," Singh said.

Making sense out of  guides much of the worldwide efforts behind 'machine learning,' a slightly oxymoronic term according to computer scientist Thomas Sterling of Indiana University. "It's a somewhat incorrect phrase because the machine doesn't actually understand anything that it learns. But it does help people see patterns and trends within data that would otherwise escape us. And it allows us to manage the massive amount and extraordinary growth of information we're having to deal with," Sterling said in a 2014 interview with TACC.

One application of machine learning that interested NASA JPL's Chris Mattmann is TensorFlow, developed by Google. It offers  commodity-based access to very large-scale machine learning. TensorFlow's Inception version three model trains the software to classify images. From a picture the model can basically tell a stop sign from a cat, for instance. Incorporated into Memex, Mattmann said Tensorflow takes its web crawls of images and video and looks for descriptors that can aid in "catching a bad guy or saving somebody, identifying an illegal weapon, identifying something like counterfeit electronics, and things like this."

"Wrangler is moving into providing TensorFlow as a capability," Mattmann said. "One of the traditional things that stopped a regular Joe from really taking advantage of large-scale machine learning is that a lot of these toolkits like Tensorflow are optimized for a particular type of hardware, GPUs or graphics processing units." This specialized hardware isn't typically found in most computers.

"Wrangler, providing GPU-types of hardware on top of its petabyte of flash storage and all of the other advantages in the types of machines it provides, is fantastic. It lets us do this at very large scale, over lots of data and run these machine learning classifiers and these tool kits and models that exist," Mattmann said.

What's more, Tensorflow is compute intensive and runs very slowly on most systems, which becomes a big problem when analyzing millions of images looking for needles in the haystack. "Wrangler does the job," Singh said. Singh and others of Mattmann's team are currently using Tensorflow on Wrangler. "We don't have any results yet, but we know that - the tool that we have built through Tensorflow is definitely producing some results. But we are yet to test with the millions of images that we have crawled and how good it produces the results," Singh said.

"I'm appreciative," said Chris Mattmann, "of being a member of the advisory board of the staff at TACC and to Niall Gaffney, Dan Stanzione, Weijia Xu and all the people who are working at TACC to make Wrangler accessible and useful; and also for their listening to the people who are doing science and research on it, like my group. It wouldn't be possible without them. It's a national treasure. It should keep moving forward."

Source : https://phys.org/news/2017-02-deep-dark-illuminated.html

Categorized in Deep Web

Microsoft's Windows 10 has been criticized a lot in three key areas during its 18 month existence.

The first was the year long aggressive free upgrade campaign to get users moving from Windows 7/8.1 to Windows 10.  In fact, Chris Capossela Microsoft's Executive VP and Chief Marketing Officer, recently admitted the company just pushed too hard to get users to upgrade for free during that program. Of course, this is now a mute point because the free offer has now expired.

Secondly, its reliability and the fast pace release of updates under the premise of Windows as a Service (WaaS) has been a constant point of contention for many users and bad updates have resulted in some system level issues for some users however, just as many Windows 10 users have told me they have systems that perform reliably despite this new updating process.

The third and final issue is one that has likely generated the most written words over the last 18 months and that is privacy and Windows 10. Microsoft collects telemetry from Windows 10 and other user information for many reasons and that is all detailed in their commitment to privacy statement and policies. The biggest issue many had from a consumer perspective is that telemetry collection could not be turned off completely unlike higher SKUs of Windows 10 like Professional, Education and Enterprise which can turn that feature off using Group Policies.

I have looked at the Privacy Settings in Windows 10 on a few different occasions and they are extensive and very granular. That allows the end user to exercise a tremendous amount of control over what information is shared with Microsoft and apps on their Windows 10 systems.

Well this week Microsoft has taken another step in reinforcing their commitment to privacy by unveiling a new centralized portal under each users Microsoft Account page that provides the ability to delete any information Microsoft has collected from their usage of Microsoft products and services.

This new privacy controls page allows users to review and/or delete information in the following areas:

  • Browsing history
  • Search history
  • Location history
  • Cortana's Notebook
  • Health activity

Now, there has always been other locations that this information could be dealt with but by bringing it all under the Microsoft Account it is now in one place for quick and easy access.

In addition to providing controls to delete this data, Microsoft is also using this portal to explain to end users the value added nature of Microsoft knowing the data collected in each area.

Browsing history

If browsing history in Cortana is turned on, your Microsoft Edge browsing history is sent to Microsoft so that Microsoft features and services may use this data to provide you with timely and intelligent answers, proactive personalized suggestions, or to complete tasks for you.

Search history

Like other search engines, Bing uses your search history to give you better results, including personalization and autosuggest. Cortana also uses that data to give you timely, intelligent answers, personalized suggestions, and complete other tasks for you.

Location history

To give you directions to the places you want to go, and show you data relevant to where you are, we use locations that you provide or that we've detected using technologies like GPS.

Cortana's Notebook

To help you avoid traffic, remember anniversaries, text the right “Jennifer” in your contact list, and in general do more, Cortana needs to know what you’re interested in, what’s on your calendar, and who you might want to do things with. The Notebook is where Cortana keeps track of your interests. When you don’t want to reach for a keyboard, Cortana can use your speech and handwriting patterns to help translate what you say or write into documents and text messages.

Health activity

Microsoft Health, HealthVault, and devices like Microsoft Band can help you collect, understand, and manage your health data. Your data can include activity and fitness data like heart rate and daily steps taken. It can also include any health records you store in HealthVault and HealthVault gives you the ability to share health records with caregivers.

In addition to providing direct access to these areas of information, the new Privacy Portal in your Microsoft Account also has a collection of direct links to other parts of the Microsoft ecosystem for managing privacy and data.

Those include:

  • Windows Privacy Settings
  • Xbox Privacy and Online Safety
  • Skype Privacy Settings
  • Apps and Services
  • Office
  • Advertising Preferences
  • Marketing Preferences

One last area that Microsoft is making some changes when it comes to privacy is the Out of Box Experience, aka OOBE, when installing the upcoming Creators Update release that is expected in April of this year. During that installation process, you will be offered the following privacy options:

  • Location
  • Speech recognition
  • Diagnostic (Full or Basic)
  • Tailored experiences with diagnostic data
  • Relevant ads

Of course, even with this new clarity and control options there will still be some who are not happy with the collection of telemetry and other information and that is simply reality.

However, Microsoft does provide an extensive collection of controls that help you manage that information. When you combine that with the explanations on why that information is useful and enhances the user experience in Windows 10 and other parts of the Microsoft user environment/services it really should help the user decide what they leave turned on or off when it relates to privacy.

But, wait...there's probably more so be sure to follow me on Twitter and Google+.

Author : Richard Hay

Source : http://winsupersite.com/microsoft/microsofts-new-privacy-dashboard-helps-users-control-their-personal-data#slide-3-field_images-81611

Categorized in Internet Privacy

Malware attacks on smartphones' operating systems have increased with the rise of the number of mobile phone users in India

With the rise in the number of mobile internet users in India, malware attacks on smartphones’ operating systems have increased and mobile applications through which people hack into phones to access personal data show the same trend, a study has found.

The report “Going Cashless and Digital: Top Cyber Threats and Targets for 2017” released on Thursday by BD Software, country partner of Bitdefender — cyber security solutions provider — highlights major trends in the cyber threat landscape in India in 2017.

“Marked with high-profile breaches and the feel of excitement and uncertainty over the country’s move towards digitising all spheres of life and economy, the outgoing 2016 sets high expectations of more advanced, more complicated and possibly more devastating security breaches in the coming year,” said Ajay Khubchandani, IT Security Expert, BD Software, in a statement.

According to the report, cashless transactions through ATMs, Point of Sale terminals, online banking websites and others are also potential targets of the cyber criminals.

The report noted that personal data is likely to draw the attention of cybercriminals in the coming year.

“As India is becoming more and more digital, the personal data of all sorts, from biometrics and family records to bank accounts and social media accounts is in danger,” the report added.

Researchers predicted that connected devices or Internet of Things (IoT) is another target for cyber attacks.

In governments, government agencies and state-affiliated organisations , the scale of data breaches is going to increase further with cross-border tensions continuing in many regions of the world, the report warned.

Author: IANS
Source: http://indianexpress.com/article/technology/tech-news-technology/personal-data-to-draw-attention-of-hackers-in-2017-report-4451436

Categorized in News & Politics

We asked Google's Gary Illyes what SEOs and webmasters should think about as this year closes.

Every year we like to get a Googler who is close with the ranking and search quality team to give us future thinking points to relay to the search marketing community. In part two of our interview with Gary Illyes of Google, we asked him that question.

After a little bit of coercion, Illyes told us three things:

(1) Machine learning

(2) AMP

(3) Structured data

He said:

Well I guess you can guess that we are going to focus more and more on machine learning. Pretty much everywhere in search. But it will not take over the core algorithm. So that’s one thing.The other thing is that there is a very strong push for AMP everywhere. And you can expect more launches around that.Structured data, again this is getting picked up more and more by the leads. So that would be another thing.

Interesting how Illyes said that the core algorithm will not be taken over by machine learning — that is an interesting point there. AMP, is obvious and structured data is as well.

Here is the transcript:

Barry Schwartz: Gary, one of my favorite parts of Matt Cutts, I guess, presentations at SMX advanced towards the year and some other conferences. Was that one of the slides always gave, I guess, webmasters and SEOs what’s coming, like what the Google search quality team is looking into for the upcoming year. And we’re kind of at the end of the year now and I was wondering if you have any of those to share.

Gary Illyes: Common, it’s early October. I understand that they started like pushing the pumpkin spice thing but it’s really not the end of the year.

Danny Sullivan: I mean you guys take all of December off and work your way from the end of the year. And might I add like December 4th you’ll be like here’s the end. It’s not like in January you go to Google Trends goes, here’s what happened year. there pushed out in Decembers. Well one thing, surely you’ve got one thing one. One forward looking statement that you can give for us to make stock purchases.

Gary Illyes: Actually you are in luck because I have a presentation or keynote for Pubcon and I will have a slide for what’s coming.

Danny Sullivan: Well let’s have that slide. Because this isn’t going to air until after…

Barry Schwartz: Can you share anything, one thing,

Danny Sullivan: One thing, this isn’t, like this isn’t live.

Gary Illyes: Oh sure.

Well I guess you can guess that we are going to focus more and more on machine learning. Pretty much everywhere in search. But it will not take over the core algorithm. So that’s one thing. The other thing is that there is a very strong push for AMP everywhere. And you can expect more launches around that. Structure data, again this is getting picked up more and more by the leads. So that would be another thing.

Author : Barry Schwartz

Source : http://searchengineland.com/google-whats-important-2017-machine-learning-amp-structured-data-261150

Categorized in Search Engine
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