Eel Catcher Presages Future of Doctors and Lawyers
January 21, 2016
I read a poignant article called “The Last Eel Catcher: 3,000-Yo UK Tradition Comes to an End.” The write up points out:
Britain’s last traditional eel catcher announced his decision to stop the ancient practice because he “can’t live on empty pockets.”
Yep, McDo’s chicken nuggets or a vegan smoothie are raking in the dough.
I thought of the last eel catcher when I read “Davos: Doctors and Lawyers Could Be Replaced by Robots.” The business and governmental elite are thinking big thoughts about technology. I learned:
Andrew Moore, Dean of the school of computer science at Carnegie Mellon University, said machines were already performing many “boring tasks of white collar work”, with computers able to sift through millions of legal documents to help lawyers prepare for cases. “One by one you are going to see that things we thought would require our own personal ingenuity can be automated,” he told a panel at the World Economic Forum in Davos, Switzerland.
I assume that’s why Goldman Sachs is jumping on the smart software bandwagon.
What will these displaced, highly paid, quite confident individuals do for a living. Eel catching is out. KFC is a possibility. I know that a few will light their entrepreneurial fires or drive an Uber car until autonomous vehicles make it big. The future could become more interesting for the docs and the legal eagles.
Stephen E Arnold, January 21, 2016
A Death of Dark Web Weapons
January 20, 2016
President Obama recently announced some executive orders designed to curb gun violence; one of these moves, according to the U.S. Attorney General, specifically targets weapon purchases through the Dark Web. However, Deep.Dot.Web asks, “Do People Really Buy Weapons from Dark Web Markets?” Not many of them, as it turns out. Reporter Benjamin Vitáris writes:
“Fast Company made an interview with Nicolas Christin, assistant research professor of electrical and computer engineering at Carnegie Mellon University (CMU). The professor is one of the researchers behind a recent deep-dive analysis of sales on 35 marketplaces from 2013 to early 2015. According to him, dark web gun sales are pretty uncommon: ‘Weapons represent a very small portion of the overall trade on anonymous marketplaces. There is some trade, but it is pretty much negligible.’ On the dark net, the most popular niche is drugs, especially, MDMA and marijuana, which takes around 25% of sales on the dark web, according to Christin’s analysis. However, weapons are so uncommon that they were put into the ‘miscellaneous’ category, along with drug paraphernalia, electronics, tobacco, viagra, and steroids. These together takes 3% of sales.”
Vitáris notes several reasons the Dark Web is not exactly a hotbed of gun traffic. For one thing, guns are devilishly difficult to send through the mail. Then there’s the fact that, with current federal and state laws, buying a gun in person is easier than through dark web markets in most parts of the U.S.; all one has to do is go to the closest gun show. So, perhaps, targeting Dark Web weapon sales is not the most efficient thing we could do to keep guns away from criminals.
Cynthia Murrell, January 20, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Many Companies Worldwide Underprepared for Cyber Attacks
January 19, 2016
A recent survey from KPMG Capital suggests that only about half the world’s CEOs feel their companies are “fully prepared” to counter a cyber breach in the next three years. One notable exception: businesses in the U.S., where about ninety percent of CEOs feel their companies are ready to fend off hackers. We are not surprised that KPMG is gathering information on in the subject, since it recently took an equity stake in cyber-intelligence firm Norse Corp.
KPMG Australia comments on the survey’s results in its post, “Cyber Security: A Failure of Imagination.” The write-up relates:
“According to the 2015 KPMG CEO Outlook Study [PDF] of more than 1,200 CEOs, one out of five indicated that information security is the risk they are most concerned about. ‘Collectively we sleepwalked into a position of vulnerability when it comes to cyber,’ said Malcolm Marshall, Global Head of Cyber Security at KPMG. ‘This combination of lack of preparedness and concern, from those organizations that are among the best equipped to deal with risks of this magnitude, clearly illustrates cyber security challenges remain severely unaddressed.’”
A lack of skilled cyber-security workers seems to be a large part of the problem, particularly ones who also have management or social-science skills. However, we’re told the root cause here is the “failure to imagine” what hackers can do and might try before they’ve tried it. Clearly, many executives would do well to get themselves up to speed on the subject, before their companies fall victim.
Cynthia Murrell, January 19, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Machine Learning Hindsight
January 18, 2016
Have you ever found yourself saying, “If I only knew then, what I know now”? It is a moment we all experience, but instead of stewing over our past mistakes it is better to share the lessons we’ve learned with others. Data scientist Peadar Coyle learned some valuable lessons when he first started working with machine learning. He discusses three main things he learned in the article, “Three Things I Wish I Knew Earlier About Machine Learning.”
Here are the three items he wishes he knew then about machine learning, but know now:
- “Getting models into production is a lot more than just micro services
- Feature selection and feature extraction are really hard to learn from a book
- The evaluation phase is really important”
Developing models is an easy step, but putting them in production is difficult. There are many major steps that need attending to and doing all of the little jobs isn’t feasible on huge projects. Peadar recommends outsourcing when you can. Books and online information are good reference tools, but when they cannot be applied to actual situations the knowledge is useless. Paedar learned that real world experience has no comparison. When it comes to testing, it is a very important thing. Very much as real world experience is invaluable, so is the evaluation. Life does not hand perfect datasets for experimentation and testing different situations will better evaluate the model.
Paedar’s advice applies to machine learning, but it applies more to life in general.
Whitney Grace, January 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Hello, Big Algorithms
January 15, 2016
The year had barely started and it looks lime we already have a new buzzword to nestle into our ears: big algorithms. The term algorithm has been tossed around with big data as one of the driving forces behind powerful analytics. Big data is an encompassing term that refers to privacy, security, search, analytics, organization, and more. The real power, however, lies in the algorithms. Benchtec posted the article, “Forget Big Data-It’s Time For Big Algorithms” to explain how algorithms are stealing the scene.
Data is useless unless you are able to are pull something out of it. The only way get the meat off the bone is to use algorithms. Algorithms might be the powerhouses behind big data, but they are not unique. The individual data belonging to different companies.
“However, not everyone agrees that we’ve entered some kind of age of the algorithm. Today competitive advantage is built on data, not algorithms or technology. The same ideas and tools that are available to, say, Google are freely available to everyone via open source projects like Hadoop or Google’s own TensorFlow…infrastructure can be rented by the minute, and rather inexpensively, by any company in the world. But there is one difference. Google’s data is theirs alone.”
Algorithms are ingrained in our daily lives from the apps run on smartphones to how retailers gather consumer detail. Algorithms are a massive untapped market the article says. One algorithm can be manipulated and implemented for different fields. The article, however, ends on some socially conscious message about using algorithms for good not evil. It is a good sentiment, but kind of forced here, but it does spur some thoughts about how algorithms can be used to study issues related to global epidemics, war, disease, food shortages, and the environment.
Whitney Grace, January 15, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Strong and Loud or Quiet and Weak, Googles Robot Grandkids Fail to Impress the Marines
January 15, 2016
The article titled Why the Marines Don’t Want Google’s Robot Soldiers in Combat on Fortune discusses the downside of the Google-owned company Boston Dynamics’ robots. You might guess, moral concerns, or more realistically, funding. But you would be wrong, since DARPA already shelled out over $30 million for the four-legged battle bots. Instead, the issue is that a single robot, which looks like a huge insect wearing a helmet and knee and elbow pads, emits a noise akin to a motorcycle revving, or a jackhammer drilling, for small movements. The article explains,
“Anyone who’s seen Boston Dynamics’ four-legged robots in action typically is wowed by their speed, strength, and agility, but also note how loud they are. They sound like chainsaws on steroids. And that decibel level is apparently a problem for potential customers, namely the U.S. military.
For Marines who took the robot out for a spin, that noise is apparently a deal breaker. “They took it as it was: a loud robot that’s going to give away their position.”
The reason for all this hullaballoo on the part of the robot is its gas engine, intended for increased robustness. The military was looking for a useful helpmate capable of carrying heavy loads of up to 400 lbs. There has been some back and forth between military representatives and Boston Dynamics, but the current state of affairs seems to be a quieter, and weaker, robot. Not ideal.
Chelsea Kerwin, January 15, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Advice for Marketers, Not Consumers, on the Present and Future States of Location Data Technology
January 14, 2016
The article on Mashable titled Location Data’s Dirty Secret: How Accuracy is Getting Lost in Today’s Data Shuffle relates the bad news for marketers, and hugely relieving news for paranoid consumers, that location data quality is far from precise. The money being funneled into location-targeted mobile ad revenues is only part of the picture, but it does illustrate the potential power of this technology for marketers, who want to know everything they can about shopping habits and habits in general. But they may be spending on useless data. In fact, the article states,
“Studies indicate that more than half of mobile location data is inaccurate. In fact, a report from the MMA offers a laundry list of variables that negatively impact location data quality. Culprits include a “lack of accuracy standards and market education,” “urban density,” “inaccurate interpretations” of location data that have been translated into a latitude/longitude coordinate and poor “data freshness.”
The article is largely optimistic that if marketers do a little research into the source of their locating data, they will know whether it can be trusted or not. That, and an objective third party will help marketers avoid big money-wasting mistakes. Must be nice to be a marketer instead of a consumer, the latter has little chance to avoid being a pawn followed around the chess board by her cell phone.
Chelsea Kerwin, January 14, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Feeding the Google AI Beast and Keeping in Mind, You Are What You Eat
January 13, 2016
The article titled We are All SkyNet in the Googlesphere on Disinformation refers to the Terminator’s controlling A.I., SkyNet, who determines the beginning of a machine age in the movie, and the conspiracy that Google is taking on that role in reality. Is it easy to understand the fear of Google’s reach, it does sometimes seem like a gigantic arm with a thousand hands groping about in cyberspace, and collecting little pieces of information that on their own seem largely harmless. The article discusses cloud computing and its relationship to the conspiracy,
“When you need your bits of info, your computer gathers them from the cloud again. The cloud is SkyNet’s greatest line of defense, as you can’t kill what is spread out over an entire network. Since the magnificent expose of the NSA and their ability to (at least) access every keystroke, file or phone call and Google’s (at minimum) complicity in managing the data, that is to say, nearly all data being collected, it’s hard to imagine the limitations to what any such Google AI program could learn.”
The article ends philosophically with the suggestion that the nature of a modern day SkyNet will depend on the data that it gathers from us, that we will create the monster in our likeness. This may not be where we expected the article to go, but it does make sense. Google as a company will not determine it, at least if literature has taught us anything.
Chelsea Kerwin, January 13, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There Is a Hole in the Cloud
January 11, 2016
Everyone is running to the cloud to reserve their own personal data spot. Companies have migrated their services to the cloud to serve a growing mobile clientele. If you are not on the cloud, it is like you’re still using an old flip phone. The cloud is a viable and useful service that allows people to access their data anytime and anywhere. Business Insider reveals that cloud usage is heavily concentrated in the US: “Latest Data From The Valley’s Oldest VC Firm Shows One Big Flaw In The Hype Around The Cloud.”
Bessemer Venture Partners is the longest running venture capitalist company in Silicon Valley. To celebrate its 100th cloud investment, it surveyed where the company’s cloud investments are located. Seventy-six of the startups are in the US, eleven are in Israel, and four are in Canada.
“The fact that less than one-quarter of BVP’s cloud investments are in non-US startups shows the adoption of cloud technologies is lagging in the rest of the world. It’s also a reminder that, even after all these years of cloud hype, many countries are still concerned about some aspects of cloud technology.”
Cloud adoption around the world is slow due to the US invents a lot of new technology and the rest of the world must catch up. Security is another big concern and companies are hesitant to store sensitive information on a system with issues.
The cloud has only been on the market for ten years and has only gained attention in the past five. Cell phones, laptops, and using open source software took time to catch on as well.
Whitney Grace, January 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
IBMs CFO Reveals IBMs Innovation Strategy: Why Not Ask Watson
January 11, 2016
The article on TechTarget titled IBM CFO Schroeter on the Company’s Innovation Strategy delves into the mind of Martin Schroeter regarding IBM’s strategy for chasing innovation in healthcare and big data. This year alone IBM acquired three healthcare companies with data on roughly one hundred million people as well as massive amounts of data on medical conditions. Additionally, as the article relates,
“IBM’s purchase of The Weather Co.’s data processing and analytics operations brought the company a “massive ingestion machine,” which plays straight into its IoT strategy, Schroeter said. The ingestion system pulls in 4 GB of data per second, he said, and runs a lot of analytics as users generate weather forecasts for their geographies. The Weather Co. system will be the basis for the company’s Internet of Things platform, he said.”
One of many interesting tidbits from the mouth of Schroeter was this gem about companies being willing to “disrupt [themselves]” to ensure updated and long-term strategies that align technological advancement with business development. The hurtling pace of technology has even meant IBM coming up with a predictive system to speed up the due diligence process during acquisitions. What once took weeks to analyze and often lost IBM deals has now been streamlined to a single day’s work. Kaboom.
Chelsea Kerwin, January 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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