What Is the Potential of Social Media?
April 11, 2016
Short honk. I read “How to Hack an Election.” The write up reports that a person was able to rig elections. According to the story:
For $12,000 a month, a customer hired a crew that could hack smartphones, spoof and clone Web pages, and send mass e-mails and texts. The premium package, at $20,000 a month, also included a full range of digital interception, attack, decryption, and defense. The jobs were carefully laundered through layers of middlemen and consultants.
Worth reading and then considering this question:
What are the implications of weaponized information?
Are pundits, mavens, self appointed experts, and real journalists on the job and helping to ensure that information online is “accurate”?
Stephen E Arnold, April 11, 2016
Newly Launched Terbium Software to Monitor Dark Web for Enterprise
April 11, 2016
Impacting groups like Target to JP Morgan Chase, data breaches are increasingly common and security firms are popping up to address the issue. The article Dark Web data hunter Terbium Labs secures $6.4m in fresh funding from ZDNet reports Terbium Labs received $6.4 million in Series A funding. Terbium Labs released software called Matchlight which provides real-time surveillance of the Dark Web and alerts enterprises when their organization’s data surfaces. Consumer data, sensitive company records, and trade secrets are among the types of data for which enterprises are seeking protection. We learned,
“Earlier this month, cloud security firm Bitglass revealed the results of an experiment focused on how quickly stolen data spreads through the Dark Web. The company found that within days, financial credentials leaked to the underground spread to 30 countries across six continents with thousands of users accessing the information.”
While Terbium appears to offer value for stopping a breach once it’s started, what about preventing such breaches in the first place? Perhaps there are opportunities for partnerships with Terbium and players in the prevention arena. Or, then again, maybe companies will buy piecemeal services from individual vendors.
Megan Feil, April 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
What Not to Say to a Prospective Investor (Unless They Just Arrived via Turnip Truck)
April 11, 2016
The article on Pando titled Startups Anonymous: Things Founders Say to Investors That Are Complete BS is an installment from a weekly series on the obstacles and madness inherent in the founder/investor relationship. Given that one person is trying to convince the other to give them money, and the other is looking for reasons to not give money, the conversations often turn comical faster than it takes the average startup to go broke. The article provides a list of trending comments that one might overhear coming from a founder’s mouth (while their nose simultaneously turns red and elongates.) Here are a few gems, along with their translated meanings,
“Our growth has been all organic.” Translation: Our friends are using it. “My cofounder turned down a job at Google to focus on our company.” Translation: He applied for an internship a while back and it fell through. “We want to create a very minimalist design.” Translation: We’re not designers and can’t afford to hire a decent one. “This is a $50 billion per year untapped market.” Translation: I heard this tactic works for getting investors.”
The frustrations of fundraising is no joke, but founders get their turn to laugh at investors in the companion article titled What I’d Really Like to Say to Investors. For example: “If today, we had the revenue you’d like to see, I wouldn’t be talking to you right now. It’s as simple as that.” Injecting honesty into these interactions is apparently always funny, perhaps because as founders get increasingly desperate, their BS artistry rises in correlation.
Chelsea Kerwin, April 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The Exalead Mafia
April 10, 2016
I read “Stupeflix’s Acquisition by Go Pro: The First Exalead Mafia Exit.” The write up stated:
Acquired in 2011 by Dassault Systemes, Exalead was a power-house for big data & search talent in the mid 2000’s – specifically, out of Exalead Labs, their internal ‘playground’ – and the former employees (most of the engineering team left in the years following the acquisition) have gone on to start great startups: Algolia, Dataiku, OpenDataSoft – even Disclose, our own product, is built by our CTO Guillaume Esquevin, an Exalead alumnus – and, of course, Stupeflix. Cofounders Nicolas Steegman & Francois Lagunas met during their time at Exalead.
The PayPal mafia includes Peter Thiel and a handful of other Silicon Valley luminaries. The French version of the innovation gang has generated a winner.
I noted this statement:
For the rest of the Exalead Mafia, I’ll be keeping an eye out. Another round for Dataiku may be in the works – the startup just moved into some luxurious offices overlooking the Rex theater in the heart of Paris’ startup neighborhood. Algolia’s post-YC growth has been incredible, releasing feature after feature and wooing clients. Most recently they launched Super Bowl Search site where you can search all the ads that have ever aired during the Super Bowl. Expect more great things from the Exalead Mafia.
One point: My records show that Dassault acquired Exalead in 2010 for about $160 million.
Stephen E Arnold, April 10, 2016
ResearchCue: Business Intelligence Mash Up Service
April 10, 2016
Short honk: I saw a Tweet about ResearchCue. According to the firm’s Web site, the service handles data aggregation for business intelligence. I checked out the report “Top Companies in Semantic Web.” A search box allows the site visitor to enter Boolean queries. The concept is that a person looking for information wants a report with snippets of relevant information automatically located and displayed in an easy-to-scan format. The presentation highlights important articles, some metrics such as the number of articles and tweets in a time period, and the list of companies in the Semantic Web sector. For vendors of keyword search solutions, this type of service is a reminder that lists of articles are not going to core the apple. Many search vendors talk about “search” and then deliver the 1970s style results. ResearchCue is making more widely available the type of information access tools I discussed in CyberOSINT: Next Generation Information Access. For traditional vendors of proprietary search systems, the future may have already passed many companies by.
Stephen E Arnold, April 10, 2016
Technology and Stuff Like Epistemology
April 9, 2016
I read with amusement “Technology Slaves Missing Out on the Real Experience.” I thought I was going to learn about the travails of a traditional newspaper which is now in the hands of new owners. Nope. I discovered that the write up is about a dinosaur waking up with snow on its feathers. [Gentle reader, you will have to pay money to access the source article. I know. That is a downshift. Take it up with the Financial Times, not me.]
The write up states with confidence:
Mobile device addiction is essentially about communication.
Ah, ha. Addiction. That’s an objective statement. Where’s the evidence? Well, in newspaper land, the proof is an anecdote from a quite talkative 30-something.
Another point.
In Plato’s Phaedrus, writing was portrayed as a disruptive, undesirable technology. Conversation and debate were the proper way to understand things.
Now we are cooking with gas. I would ask, gentle reader, what are the “things” one is to understand.
What must a person do when the notions of reality and things underpin an article about technology. In fact, what is technology? The newspaper which had to sell itself leaves that area murky or unconsidered.
Someone, methinks, needed a column and did not have time to check Facebook or tweet. The dinosaur with snow on its feathers is someone who is uncomfortable with change. Ah, where are the good old days of dead tree papers sold on corners by paupers?
Stephen E Arnold, April 9, 2016
Weekly Watson: On the Road to Italy
April 9, 2016
Don’t art history majors flock to Italy? IBM Watson is not going to marvel at David or the Vatican’s collection of Roman statues.
I read “IBM Watson Takes Analytics Prowess Overseas: Supercomputer to Work on Big Data and Genomics in Italy.”
I learned:
Watson, IBM’s supercomputing brainchild, will soon have its own pied-à-terre across the pond. Big Blue announced Thursday it would launch its first Watson Health European Center of Excellence in Milan near the Human Technopole Italy 2040 research campus.
No revenue yet. The write up revealed:
IBM data scientists, engineers and programmers will collaborate with organizations across Europe to create a new class of cloud-based connected solutions to help speed research of new treatments, personalized medicine, and discoveries to boost public health management while advancing sustainable health systems.
How long will it take for Watson to cure IBM’s revenue respiratory problem? Will the Italian climate, food, and get ‘er done attitude do the job? We can, as always, ask Watson.
Stephen E Arnold, April 9, 2016
Business Analytics: April Fool or Not
April 8, 2016
I read “Business Analytics Is a Big Sham and Over Rated.” My hunch is that the write up is a bit of April fool baloney. But, maybe not?
Many vendors are changing their marketing collateral to proclaim one very special outfit can make sense out of oodles of data and textual information.
The write up makes some interesting statements; for example:
Analysts waste every one’s time. Perhaps the statement should be “often are too busy to deal with requests for their services.”
But the write up is an April Fool joke. The problem is that large organizations and government entities want a silver bullet. Who has witnessed the implosion of a massive enterprise software project?
In my experience, business analytics are becoming a must have function. The problem is that the hoo haa tossed around by vendors and pundits seems reasonably accurate.
Humor and reality are one.
Stephen E Arnold, April 8, 2016
Machine Learning: 10 Numerical Recipes
April 8, 2016
The chatter about smart is loud. I cannot hear the mixes on my Creamfields 2014 CD. Mozart, you are a goner.
If you want to cook up some smart algorithms to pick music or drive your autonomous vehicle without crashing into a passenger carrying bus, navigate to “Top 10 Machine Learning Algorithms.”
The write up points out that just like pop music, there is a top 10 list. More important in my opinion is the concomitant observation that smart software may be based on a limited number of procedures. Hey, this stuff is taught in many universities. Go with what you know maybe?
What are the top 10? The write up asserts:
- Linear regression
- Logistic regression
- Linear discriminant analysis
- Classification and regression trees
- Naive Bayes
- K nearest neighbors
- Learning vector quantization
- Support vector machines
- Bagged decision trees and random forest
- Boosting and AdaBoost.
The article tosses in a bonus too: Gradient descent.
What is interesting is that there is considerable overlap with the list I developed for my lecture on manipulating content processing using shaped or weaponized text strings. How’s that, Ms. Null?
The point is that when systems use the same basic methods, are those systems sufficiently different? If so, in what ways? How are systems using standard procedures configured? What if those configurations or “settings” are incorrect?
Exciting.
Stephen E Arnold, April 8, 2016
Microsoft Does Cognitive Too
April 8, 2016
I read “Microsoft Launches Cognitive Services Based on Project Oxford and Bing.” I immediately thought of MIcrosoft’s smart chatbot adventure. Do I doubt the efficacy of Microsoft’s smart systems? No, I just think that the same approach manifested in Tay probably exists in the suite of APIs announced on March 30, 2016.
I learned:
The brand name Cognitive Services is a nod to IBM’s Watson, which for the past few years has been marketed as a “cognitive computing” product — that is, one that’s based on the way the human brain works.
That is working out very well for IBM. There is a recipe book and many projects. Revenues? Well, sure. Some.
Microsoft offers a search API. That, one hopes, will actually work reasonably well. Microsoft’s track record in the information access department has been interesting.
According to this Microsoft page, there are give search APIs which are available for preview. Use is like a taxi ride, and that type of metered pricing is often unsettling.
The five APIs are:
- Bing Autosuggest
- Bing Image Search
- Bing News Search
- Bing Video Search
- Bing Web Search.
I assume one can mix in academic knowledge, entity linking, and knowledge exploration. In addition, it appears thate is a language understanding intelligent service called Luis. I noted linguistic analysis as an API as well. And for good measure, one can tap text analytics.
For a developer, these Lego blocks offer an opportunity to code up a solution.
On the other hand, there are goodies from outfits from Baidu to Facebook, from Google to X.ai from which to choose.
Just as IBM is saddled with the Jeopardy and recipe book, Microsoft is going to have to live with Tay’s capabilities.
What happens if Tay works into a routine search query? That will be intriguing. Perhaps Tay and Watson can get together and do smart thing?
Stephen E Arnold, April 8, 2016
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