Myanmar in Mobile: A Reminder of How Easy It Is to Make Assumptions
January 25, 2016
I suggest you read the write up “The Facebook Loving Farmers of Myanmar.” Useful information. You can work through the article and get a sense of the importance of connectivity to farmers in a region which is quite a bit different from Silicon Valley and Route 128.
I want to highlight two points which I noted. My hunch is that these will be different from many other folks’ reaction to the article.
The first point is a reference to the failure of the “one laptop per child” thing cooked up by someone in the US of A’s right coast. Here’s the quote I highlighted:
But the more we probe, the less justifiable the Samsung premium becomes. The Chinese phones are cheap but capable. I wonder if this makes Negroponte happy. His one laptop-per-child dream was never fully realized but one smartphone-per-human—far more capable and sensible than a laptop, in many ways—has most certainly arrived. I take notes.
The point is that traditional desktops and laptops are not what has captured the attention of the farmers of Myanmar. The shift to phones, Chinese phones in particular, can be described as a miss, a big miss for the “one laptop per child” idea. How many other high tech beliefs are going to be shown to be just wrong enough? This, for me, is a reminder that what seems obvious to those on the left and right coasts in the United States are pitching the equivalent of snowshoes to people who live where it does not snow.
The second point I circled was:
I realize then that smartphone tech crossed the Good Enough threshold years ago.
What if the money pumped into improving smartphones by making them bigger, smaller, in different colors, etc. is a living, breathing example of diminishing returns. No mater what the phone designers and manufacturers cook up, the pay back will keep getting smaller. Apple is becoming mobile dependent. Google is becoming mobile dependent. What if these investments creep toward lower and lower returns. In a lousy economic environment, could there be financial trouble ahead for these and allied companies?
My hunch is that there are more farmers in Myanmar type folks than there are those who can get hired at the likes of the sparkling tech citadels on the left and right coast of the US, the silicon fen, and the other confections of techno-wizardry.
The one laptop per child play was not just wrong by a little; it was wrong by a mile unless Google knows something the folks in Myanmar do not. See “Google Donates More Than $5 Million to Give Chromebooks to Refugees.”
Stephen E Arnold, January 25, 2016
Alphabet Google Justifies Its R&D Science Club Methods
January 23, 2016
In the midst of the snowmageddon craziness in rural Kentucky, I noted a couple of Alphabet Google write ups. Unlike the sale of shares, the article tackle the conceptual value of the Alphabet Google’s approach to research and development. I view most of Google’s post 2006 research as an advanced version of my high school science club projects.
Our tasks in 1960 included doing a moon measurement from central Illinois. Don’t laugh, Don and Bernard Jackson published their follow on to the science club musing in 1962. In Don’s first University of Illinois astronomy class, the paper was mentioned by the professor. The prof raised a question about the method. Don raised his hand and explained how the data were gathered. The prof was not impressed. Like many mavens, the notion that a college freshman and his brother wrote a paper, got it published, and then explained the method in front of a class of indifferent freshman was too much for the expert. I think the prof shifted to social science or economics, both less rigorous disciplines in my view.
Google’s research interests.
The point is that youth can get some things right. As folks age, the view of what’s right and what’s a little off the beam differ.
Let’s look at the first write up called “How Larry Page’s Obsessions Became Google’s Business.” Note that if the link is dead, you may have to subscribe to the newspaper or hit the library in search of a dead tree copy. The New York Times have an on again and off again approach to the Google. It’s not that the reporters don’t ask the right questions. I think that the “real” journalists get distracted with the free mouse pads and folks like Tony Bennett crooning in the cafeteria to think about what the Google was, is, and has become.
The article points out:
Mr. Page is hardly the first Silicon Valley chief with a case of intellectual wanderlust, but unlike most of his peers, he has invested far beyond his company’s core business and in many ways has made it a reflection of his personal fascinations.
I then learned:
Another question he likes to ask: “Why can’t this be bigger?”
The suggestion that bigger is better is interesting. Stakeholders assume the “bigger” means more revenue and profit. Let’s hope.
Then this insight:
When Mr. Page does talk in public, he tends to focus on optimistic pronouncements about the future and Google’s desire to help humanity.
Optimism is good.
I then worked through “Google Alphabet and Four times the Research Budget of Darpa and Larger Moonshot Ambitions than Darpa.”
The bigger, I thought, may not be revenue. The bigger may be the budget of the science club. If Don and Bernie Jackson could build on the moon data, Google can too. Right?
Microsoft Cortana Update Draws Users to Bing
January 22, 2016
The article titled Microsoft Updates Windows 10 Cortana With New Search Tools for Better Results on IB Times heralds the first good news for Bing in ages. The updates Microsoft implemented provide tremendous search power to users and focused search through a selection of filters. Previously, Cortana would search in every direction, but the filters enable a more targeted search for, say, applications instead of web results. The article explains,
“It’s a small change, but one that shows Microsoft’s dedication to making the assistant as useful as possible. Cortana is powered by Bing, so any improvements to the Windows 10 assistant will encourage more consumers to use Microsoft’s search engine. Microsoft made a big bet when it chose to deeply integrate Bing into Windows 10, and there is signs that it’s paying off. After the June 2015 Windows 10 launch, Bing attained profitability for the first time in October 2015.”
That positive note for Bing is deeply hedged on the company’s ability to improve mobile search, which has continued to grow as a major search platform while desktop search actually peaked, according to research. Microsoft launched Cortana on Android and iOS, but it is yet to be seen whether this was sufficient action to keep up the Bing momentum.
Chelsea Kerwin, January 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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
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