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Meatbags Prevent Google’s Self-Driving Car

July 2, 2015

Driving is a privilege not a right…for humans and Google wants it for its self-driving carsGoogle, however, is still in the test phasing for its self-driving cars and announced that they would publish results of the study on a monthly basis.  They first report recently came out and it says that Google cars were in twelve accidents when they were on real roads.  The Register takes a snarky, informative approach to self-driving cars in “Google: Our Self-Driving Cars Would Be Tip-Top If You Meatheads Didn’t Crash Into Them.”

Google has twenty-three Lexus SUVs that have driven 1,011,338 miles with the self-driving software and 796, 250 miles with a human behind the wheel.  Many of the cars have taken to the real road, but nine are still restricted to the private track.

Google blames all twelve of the accidents on human error, not the software, and it is due to either the human driver in the autonomous car or the driver in the other car.  The Google cars, being rear-ended from driving too slow, caused seven accidents.  One accident was due to the Google car braking trying to avoid a collision and two more were when non-Google cars failed to obey traffic signs.  The worst accident caused when a Google car was driving at 63 mph and was sideswiped by a car changing lanes.  No one was hurt.  The last two accidents were the fault of Google’s employees: both accidents resulted in Google cars rear-ending the cars in front of them.

Google is quick to point out the software’s positive aspects:

“The report also highlighted some of the smarter aspects of the cars’ software. Google cars can identify emergency vehicles, for example, and automatically give way in a fashion many fleshy drivers are irritatingly unwilling to do.  The other example given was Google cars dealing with cyclists who didn’t obey the rules of the road. One cyclist veered in front of the car at night, and the software was clever enough to stop immediately to avoid a crash.”

Google will have its cars drive ten thousand miles a week on the software.  A recent luxury car ad campaign was critical of the self-driving car, saying people want the luxury of driving themselves with all the benefits of said luxury car.  It will be the TV vs. radio battle again, but the one thing holding back the self-driving car will be human error.  Stupid, stupid humans.

Whitney Grace, July 2, 2015

Sponsored by, publisher of the CyberOSINT monograph

ClearStory Is On the Move

July 1, 2015

The article on Virtual-Strategy Magazine titled ClearStory Data Appoints Dr. Timothy Howes as Chief Technology Offiver; Fromer Vice President of Yahoo, CTO of HP Software, Opsware, and Netscape discusses Howe’s reputation as an innovative thinker who helped invent LDAP. His company Rockmelt Inc. was acquired by Yahoo and he also co-founded Loudcloud, which is now known as Opsware, with the founders of VC firm Andreessen Horowitz, who are current backers of ClearStory Data. Needless to say, obtaining his services is quite a coup for ClearStory. Howe discusses his excitement to join the team in the article,

“There’s a major technology shift happening in the data market right now as businesses want to see and explore more data faster. ClearStory is at the forefront of delivering the next-generation data analysis platform that brings Spark-powered, fast-cycle analysis to the front lines of business in a beautiful, innovative user experience that companies are in dire need of today,” said Howes. “The ClearStory architectural choices made early on, coupled with the focus on an elegant, collaborative user model is impressive.”

The article also mentions that Ali Tore, formerly of Model N, has been named the new Chief Product Officer. Soumitro Tagore of the startup Clari will become the VP of Engineering and Development Operations. ClearStory Data is intent on the acceleration of the movement of data for businesses. Their Intelligent Data Harmonization platform allows data from different sources to be quickly and insightfully explored.

Chelsea Kerwin, July 1, 2014

Sponsored by, publisher of the CyberOSINT monograph

Microsoft Puts the Cloud First with SharePoint Server 2016

June 30, 2015

Discussion of the cloud seems to push users into two camps: for and against. While hybrid is probably truly the way of the future, folks are still currently either of the “love it” or “hate it” variety. Redmond Magazine has provided good ongoing coverage of the upcoming SharePoint Server 2016 release, and their article, “Microsoft Taking a ‘Cloud First’ Approach with SharePoint 2016,” gives more details about what can be expected.

The article says:

“SharePoint Server 2016 will be a very cloud-inspired product when commercially released next year . . . Microsoft’s cloud services have been looming in the background of prior SharePoint Server releases . . . Office 365 cloud services have played a role since SharePoint Server 2013, and they will do so going forward with SharePoint Server 2016.”

One of the main promotional points of the new release is a promised “unified experience” for SharePoint users. While cloud skeptics still have reason to be cautious, the promised improvements may win them over. To stay up-to-date with the latest news regarding SharePoint, stayed tuned in to and the dedicated SharePoint feed. Stephen E. Arnold is a longtime leader in search and his expertise comes in handy when trying to stay current without spending a lot of time doing independent research.

Emily Rae Aldridge, June 30, 2015

Sponsored by, publisher of the CyberOSINT monograph


Webinar from BrightFunnel Ties Marketing to Revenue

June 30, 2015

The webinar on BrightFunnel Blog titled Campaign Attribution: Start Measuring True Marketing Impact (How-To Video) adds value to marketing efforts. BrightFunnel defines itself as platform for marketing analytics that works to join marketing more closely to revenue. The webinar is focused on the attribution application. The video poses three major questions that the application can answer about how pipeline and revenue are affected by marketing channels and specific campaigns, as well as how to gain better insight on the customer. The article overviews the webinar,

“Marketers care. We care a lot about what happens to all those leads we generate for sales. It can be hard to get a complete view of marketing impact when you’re limited to trusting that the right contacts, if any, are being added to opportunities! In this recording from our recent webinar, see how BrightFunnel solves key attribution problems by providing seamless visibility into multi-touch campaign attribution so you can accurately measure the impact you have on pipeline and revenue.”

BrightFunnel believes in an intuitive approach, claiming that three to four weeks has been plenty of time for their users to get set up and get to work with their product. They host a series of webinars that allows interested parties to ask direct questions and be answered live.

Chelsea Kerwin, June 30, 2014

Sponsored by, publisher of the CyberOSINT monograph


Matchlight Lights Up Stolen Data

June 26, 2015

It is a common gimmick on crime shows for the computer expert to be able to locate information, often stolen data, by using a few clever hacking tricks.  In reality it is not that easy and quick to find stolen data, but eWeek posted an article about a new intelligence platform that might be able to do the trick: “Terbium Labs Launches Matchlight Data Intelligence Platform.”  Terbium Labs’ Matchlight is able to recover stolen data as soon as it is released on the Dark Web.

How it works is simply remarkable.  Matchlight attaches digital fingerprints to a company’s files, down to the smallest byte.  Data recovered on the Dark Web can then be matched to the Terbium Labs’s database.  Matchlight is available under a SaaS model.  Another option they have for clients is a one-way fingerprinting feature that keeps a company’s data private from Terbium Labs.  They would only have access to the digital fingerprints in order to track the data.  Matchlight can also be integrated into already existing SharePoint or other document management systems.  The entire approach to Matchlight is taking a protective stance towards data, rather than a defensive.

“We see the market shifting toward a risk management approach to information security,” [Danny Rogers, CEO and co-founder of Terbium} said. “Previously, information security was focused on IT and defensive technologies. These days, the most innovative companies are no longer asking if a data breach is going to happen, but when. In fact, the most innovative companies are asking what has already happened that they might not know about. This is where Matchlight provides a unique solution.”

Across the board, data breaches are becoming common and Matchlight offers an automated way to proactively protect data.  While the digital fingerprinting helps track down stolen data, does Terbium Labs have a way to prevent it from being stolen at all?

Whitney Grace, June 26, 2015

Sponsored by, publisher of the CyberOSINT monograph

Digital Reasoning a Self-Described Cognitive Computing Company

June 26, 2015

The article titled Spy Tools Come to the Cloud on Enterprise Tech shows how Amazon’s work with analytics companies on behalf of the government have realized platforms like “GovCloud”, with increased security. The presumed reason for such platforms being the gathering of intelligence and threat analysis on the big data scale. The article explains,

“The Digital Reasoning cognitive computing tool is designed to generate “knowledge graphs of connected objects” gleaned from structured and unstructured data. These “nodes” (profiles of persons or things of interest) and “edges” (the relationships between them) are graphed, “and then being able to take this and put it into time and space,” explained Bill DiPietro, vice president of product management at Digital Reasoning. The partners noted that the elastic computing capability… is allowing customers to bring together much larger datasets.”

For former CIA staff officer DiPietro it logically follows that bigger questions can be answered by the data with tools like the AWS GovCloud and subsequent Hadoop ecosystems. He cites the ability to quickly spotlight and identify someone on a watch list out of the haystack of people as the challenge set to overcome. They call it “cluster on demand,” the process that allows them to manage and bring together data.

Chelsea Kerwin, June 26,  2015

Sponsored by, publisher of the CyberOSINT monograph

Deep Learning System Surprises Researchers

June 24, 2015

Researchers were surprised when their scene-classification AI performed some independent study, we learn from Kurzweil’s article, “MIT Deep-Learning System Autonomously Learns to Identify Objects.”

At last December’s International Conference on Learning Representations, a research team from MIT demonstrated that their scene-recognition software was 25-33 percent more accurate than its leading predecessor. They also presented a paper describing the object-identification tactic their software chose to adopt; perhaps this is what gave it the edge. The paper’s lead author, and MIT computer science/ engineering associate professor, Antonio Torralba ponders the development:

“Deep learning works very well, but it’s very hard to understand why it works — what is the internal representation that the network is building. It could be that the representations for scenes are parts of scenes that don’t make any sense, like corners or pieces of objects. But it could be that it’s objects: To know that something is a bedroom, you need to see the bed; to know that something is a conference room, you need to see a table and chairs. That’s what we found, that the network is really finding these objects.”

Researchers being researchers, the team is investigating their own software’s initiative. The article tells us:

“In ongoing work, the researchers are starting from scratch and retraining their network on the same data sets, to see if it consistently converges on the same objects, or whether it can randomly evolve in different directions that still produce good predictions. They’re also exploring whether object detection and scene detection can feed back into each other, to improve the performance of both. ‘But we want to do that in a way that doesn’t force the network to do something that it doesn’t want to do,’ Torralba says.”

Very respectful. See the article for a few more details on this ambitious AI, or check out the researchers’ open-access paper here.

Cynthia Murrell, June 24, 2015

Sponsored by, publisher of the CyberOSINT monograph


Expert Systems Acquires TEMIS

June 22, 2015

In a move to improve its product offerings, Expert System acquired TEMIS.  The two companies will combine their assets to create a leading semantic provider for cognitive computing.  Reuters described the acquisition in very sparse details: “Expert System Signs Agreement To Acquire French TEMIS SA.”

Reuters describes the merger as:

“Reported on Wednesday that it [Expert System] signed binding agreement to buy 100 percent of TEMIS SA, a French company offering solutions in text analytics

  • Deal value is 12 million euros ($13.13 million)”

TEMIS creates technology that helps organizations leverage, manage, and structure their unstructured information assets.  It is best known for Luxid, which identifies and extracts information to semantically enrich content with domain-specific metadata.

Expert System, on the other hand, is another semantically inclined company and its flagship product is Cogito.  The Cogito software is designed to understand content within unstructured text, systems, and analytics.  The goal is give organizations a complete picture of your information, because Cogitio actually understand what is processing.

TEMIS and Expert System have similar goals to make unstructured data useful to organizations.  Other than the actual acquisition deal, details on how Expert System plans to use TEMIS have not been revealed.  Expert System, of course, plans to use TEMIS to improve its own semantic technology and increase revenue.  Both companies are pleased at the acquisition, but if you consider other buy outs in recent times the cost to Expert System is very modest.  Thirteen million dollars underscores the valuation of other text analysis companies.  Other text analysis companies would definitely cost more than TEMIS.

Whitney Grace, June 22, 2015

Sponsored by, publisher of the CyberOSINT monograph


Latest Version of DataStax Enterprise Now Available

June 19, 2015

A post over at the SD Times informs us, “DataStax Enterprise 4.7 Released.” Enterprise is DataStax’s platform that helps organizations manage Apache Cassandra databases. Writer Rob Marvin tells us:

“DataStax Enterprise (DSE) 4.7 includes a production-certified version of Cassandra 2.1, and it adds enhanced enterprise search, analytics, security, in-memory, and database monitoring capabilities. These include a new certified version of Apache Solr and Live Indexing, a new DSE feature that makes data immediately available for search by leveraging Cassandra’s native ability to run across multiple data centers. …

“DSE 4.7 also adds enhancements to security and encryption through integration with the DataStax OpsCenter 5.2 visual-management and monitoring console. Using OpsCenter, developers can store encryption keys on servers outside the DSE cluster and use the Lightweight Directory Access Protocol to manage admin security.”

Four main features/ updates are listed in the write-up: extended search analytics, intelligent query routing, fault-tolerant search operations, and upgraded analytics functionality. See the article for details on each of these improvements.

Founded in 2010, DataStax is headquartered in San Mateo, California. Clients for their Cassandra-management software (and related training and professional services) range from young startups to Fortune 100 companies.

Cynthia Murrell, June 19, 2015

Sponsored by, publisher of the CyberOSINT monograph

Make Your Data Pretty

June 19, 2015

It is very easy to read and interpret data when it is represented visually.  Humans are visual creatures and it can be easier to communicate via pictures for an explanation.  Infographics are hugely popular on the Internet and some of them have achieved meme status.  While some data can be easily represented using Adobe Photoshop or the Microsoft Office Suite, more complex data needs more complex software to simplify it visually.

Rather than spending hours on Google, searching for a quality data visualization tool Usability Tools has rounded up “21 Essential Data Visualization Tools.”  What is great about this list is that it features free services that available to improve how you display data on your Web site, project, or whatever your specific needs are.

Some of the choices are obvious, such as Google Charts and Wolfram Alpha, but there are some stand outs that combine JavaScript and draw on Internet resources.  Plus they are also exceedingly fun to play with.  They include: Timeline.js, Tableau Public, PiktoChart, Canva, and D3.js.

None of the data visualization tools are better than the others, in fact the article’s author says what you want to use is based on your need:

“As you can see, there is plenty of Data Visualization tools that will make you understand your users in a better, more insightful way. There are many tools being launched every day, but I managed to collect those that are the most popular in the ‘industry’. Of course, they have both strong and weak sides, since there is no one perfect tool to visualize the metrics. All I can do is to recommend you trying them yourself and combining them in order to maximize the efficiency of visualizing data.”

It looks like it is time to start playing around with data toys!

Whitney Grace, June 19, 2015

Sponsored by, publisher of the CyberOSINT monograph


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