Machine Learning: Learn Now
July 18, 2016
If you want the basics taught in most universities, you can start with the papers listed at this link. If you come away from these write ups with some questions, you can refresh your knowledge of Bayesian machine learning in a paper of the same name. To get a sense of some limitations of the much-hyped “new” approach to smart software, check out this sort of slideshow, sort of lecture called “What’s Wrong with Deep Learning?” Balanced views are difficult to track down. There are the cheerleaders, and then there are some implementers. A representative example of cheerleaders are the ad hoc team of Google, Microsoft, and some startups, research computing outfits, and lots of academics. The doubters are old people like myself who have had to deal with the interesting “drift” which can creep into deep learning systems. What’s drift, you may ask? Well, you expect one thing and get another. No human knows why. That’s drift.
Stephen E Arnold, July 18, 2016
Attivio Targets Profitability by the End of 2016 Through $31M Financing Round
July 18, 2016
The article on VentureBeat titled Attivio Raises $31 Million to Help Companies Make Sense of Big Data discusses the promises of profitability that Attivio has made since its inception in 2007. According to Crunchbase, the search vendor has raised over $100 million from four investors. In March 2016, the company closed a financing round at $31M with the expectation of becoming profitable within 2016. The article explains,
“Our increased investment underscores our belief that Attivio has game-changing capabilities for enterprises that have yet to unlock the full value of Big Data,” said Oak Investment Partners’ managing partner, Edward F. Glassmeyer. Attivio also highlighted such recent business victories as landing lab equipment maker Thermo Fisher Scientific as a client and partnering with medical informatics shop PerkinElmer. Oak Investment Partners, General Electric Pension Trust, and Tenth Avenue Holdings participated in the investment, which pushed Attivio’s funding to at least $102 million.”
In the VentureBeat Profile about the deal, Stephen Baker, CEO of Attivio makes it clear that 2015 was a turning point for the company, or in his words, “a watershed year.” Attivio prides itself on both speeding up the data preparation process and empowering their customers to “achieve true Data Dexterity.” And hopefully they will also be profitable, soon.
Chelsea Kerwin, July 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden Web/Dark
Web meet up on July 26, 2016.
Information is at this link: http://bit.ly/29tVKpx.
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The Watson Update
July 15, 2016
IBM invested a lot of resources, time, and finances into developing the powerful artificial intelligence computer Watson. The company has been trying for years to justify the expense as well as make money off their invention, mostly by having Watson try every conceivable industry that could benefit from big data-from cooking to medicine. We finally have an update on Watson says ZDNet in the article, “IBM Talks About Progress On Watson, OpenPower.”
Watson is a cognitive computer system that learns, supports natural user interfaces, values user expertise, and evolves with new information. Evolving is the most important step, because that will allow Watson to keep gaining experience and learn. When Watson was first developed, IBM fed it general domain knowledge, then made the Watson Discovery to find answers to specific questions. This has been used in the medical field to digest all the information created and applying it to practice.
IBM also did this:
“Most recently IBM has been focused on making Watson available as a set of services for customers that want to build their own applications with natural question-and-answer capabilities. Today it has 32 services available on the Watson Developer Cloud hosted on its Bluemix platform-as-a-service… Now IBM is working on making Watson more human. This includes a Tone Analyzer (think of this as a sort spellchecker for tone before you send that e-mail to the boss), Emotion Analysis of text, and Personality Insights, which uses things you’ve written to assess your personality traits.”
Cognitive computing has come very far since Watson won Jeopardy. Pretty soon the technology will be more integrated into our lives. The bigger question is how will change society and how we live?
Whitney Grace, July 15, 2016
There is a Louisville, Kentucky Hidden Web/Dark
Web meet up on July 26, 2016. Information is at this link: http://bit.ly/29tVKpx.
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Try the Amazon Brand Computer Chip
July 14, 2016
Amazon offers its clients cloud storage, software development help, and more services via their Amazon Service Works. The global retailer is also taking on electronics and cable TV with the Kindle and Amazon Fire TV, but now, according to Trusted Reviews, “Amazon Now Selling Own-Brand Computer Chips.” Amazon wants to diversify its offerings even more with its own brand of computer chips.
The Amazon brand computer chips are made by Annapurna Labs that the company purchased last year. Amazon recently announced these chips are now available to the open market and the ARM-based processors can be used in home gateways, WiFi routers, and networked attached storage devices. They are meant to be used as cheap alternatives for home smart devices and data centers, nothing that can compete on the scale of Qualcomm.
The purpose of a capitalistic society is to drive competition and Intel has the computer chip marker monopoly:
“However, it does mark a notable challenge to another major chip manufacturer. As Bloomberg points out, Intel currently has the data-centre infrastructure field pretty much to itself, with a whopping 99% share of the server chip market. Amazon’s entry to this one-sided market could start to change that, although it won’t initially be targeting the kind of high-end servers that represent Intel’s stronghold. Amazon appears to be attacking the low-power edges of the market, which could see it powering (or at least helping to power) that hottest of networks, the Internet of Things.”
Great, Amazon is still working on developing other products, but we want to know when they are going to deploy image search.
Whitney Grace, July 14, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Dark Web Drug Merchant Shiny Flakes Fesses Up
July 14, 2016
Authorities know a bit more about how criminals buy and sell drugs on the dark web, thanks to the cooperation of a captured dealer. DarknetPages’ article, “Dark Web and Clearnet Drug Vendor ‘Shiny Flakes’ Confessed his Crimes,” reveals that the 20-year-old Shiny Flakes, aka Maximilian S., was found with a bevy of illegal drugs, cash, and packaging equipment in his German home. Somehow, the police eventually convinced him to divulge his methods. We learn:
“[Maximilian] actually tried to make money on the internet legally in 2013 by copying fee-based pornographic websites. The thing is that the competition was pretty strong and because of that, he abandoned his idea soon after. So instead of spending the 2 thousand EUR he had at the time on porn, he thought it would be a better idea to spend it on drugs. So he went on to purchase 30 g of cocaine and shrooms from a popular German darknet market dealer and then sold them for a higher price on the dark web….
“Shiny Flakes was really worried about the quality of the drugs he was selling and that is why he always kept an eye on forum posts and read everything that his buyers posted about them. In fact, he took things beyond the opinions on the dark web and actually sent the drugs for testing. The tests conducted were both legally and illegally, with the legal tests taking place at Spain’s Energy Control or at Switzerland’s Safer Party. However, it seems that Maximilian also got in touch with the University of Munich where his products were tested by researchers who were paid in cocaine.”
Sounds efficient. Not only was Mr. Flakes conscientious about product quality, he was also apparently a hard worker, putting in up to 16 hours a day on his business. If only he had stayed on the right side of the law when that porn thing didn’t work out. To give him credit, Flakes had every reason to think he would not be caught; he was careful to follow best practices for staying anonymous on the dark web. Perhaps it was his booming success, and subsequent hiring of associates, that led to Shiny Flakes’ downfall. Whatever the case, authorities are sure to follow up on this information.
Cynthia Murrell, July 14, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
What Could Possibly Go Wrong?
July 13, 2016
After reading The Atlantic’s article, “Technology, The Faux Equalizer” about how technology is limited to the very wealthy and does not level the playing field. It some ways new technology can be a nuisance to the average person trying to scratch out a living in an unfriendly economy. Self-driving cars are one fear, but did you ever think bankers and financial advisors would have to compete with algorithms? The International Business Times shares, “Will Financial Analysts Lose Their Jobs To Intelligent Trading Machines?”
Machine learning software can crunch numbers faster and can extrapolate more patterns than a human. Hedge fund companies have hired data scientists, physicists, and astronomers to remove noise from data and help program the artificial intelligence software. The article used UK-based Bridgewater Associates as an example of a financial institute making strides in automizing banking:
“Using Bridgewater as an example, Sutton told IBTimes UK: ‘If you look at their historic trading strategies, it’s been very much long-term bets around what’s happening at a macro level. They have built their entire business on having some of the best research and analytics in the industry and some of the smartest minds thinking on that. When you combine those two things, I would definitely expect artificial intelligence to be applied to identify large-scale trades that might not be evident to an individual researcher.’”
Developing artificial intelligence for the financial sector has already drawn the attention of private companies and could lead to a 30% lose of jobs due to digitization. It would allow financial companies a greater range of information to advise their clients on wise financial choices, but it could also mean these institutes lose talent as the analysts role was to groom more talent.
These will probably be more potential clients for IBM’s Watson. We should all just give up now and hail our robot overlords.
Whitney Grace, July 13, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Defending Against Java Deserialization Ransomware
July 13, 2016
What is different about the recent rash of ransomware attacks against hospitals (besides the level of callousness it takes to hold the well-being of hospital patients for ransom)? CyberWatch brings us up to date in, “My Layman’’s Terms: The Java Deserialization Vulnerability in Current Ransomware.” Writer Cheryl Biswas begins by assuring us it is practicality, not sheer cruelty, that has hackers aiming at hospitals. Other entities, like law enforcement agencies, which rely on uninterrupted access to their systems to keep people safe are also being attacked. Oh, goody.
The problem begins with a vulnerability at the very heart of any Java-based system, the server. And here we thought open source was more secure than proprietary software. Biswas informs us:
“This [ransomware] goes after servers, so it can bring down entire networks, and doesn’t rely on the social engineering tactics to gain access. It’s so bad US-CERT has issued this recent advisory. I’ve laid out what’s been made available on just how this new strain of ransomware works. And I’ve done it in terms to help anybody take a closer look at the middleware running in their systems currently. Because a little knowledge could be dangerous thing used to our advantage this time.”
The article goes on to cover what this strain of ransomware can do, who could be affected, and how. One key point—anything that accepts serialized Java objects could be a target, and many Java-based middleware products do not validate untrusted objects before deserialization. See the article for more technical details, and for Biswas’ list of sources. She concludes with these recommendations:
“Needs to Happen:
“Enterprises must find all the places they use deserialized or untrusted data. Searching code alone will not be enough. Frameworks and libraries can also be exposed.
“Need to harden it against the threat.
“Removing commons collections from app servers will not be enough. Other libraries can be affected.
“Contrast Sec has a free tool for addressing issue. Runtime Application Self-Protection RASP. Adds code to deserialization engine to prevent exploitation.”
Organizations the world over must not put off addressing these vulnerabilities, especially ones in charge of health and safety.
Cynthia Murrell, July 13, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Technology Does Not Level the Playing Field
July 12, 2016
Among the many articles about how too much automation of the labor force will devastate humanity, I found another piece that describes how technology as tools are a false equalizer. The Atlantic published the piece titled: “Technology, The Faux Equalizer.” What we tend to forget is that technology consists of tools made by humans. These tools have consistently become more complicated as society has advanced. The article acknowledges this by having us remember one hundred years ago, when electricity was a luxurious novelty. Only the wealthy and those with grid access used electricity, but now it is as common as daylight.
This example points to how brand new technology is only available to a limited percentage of people. Technological process and social progress are not mutually inclusive. Another example provided, notes that Gutenberg’s printing press did not revolutionize printing for society, but rather the discovery of cheaper materials to make books. Until technology is available for everyone it is not beneficial:
“Just compare the steady flow of venture capital into Silicon Valley with the dearth of funding for other technological projects, like critical infrastructure improvements to water safety, public transit, disintegrating bridges, and so on. ‘With this dynamic in mind, I would suggest that there is greater truth to the opposite of Pichai’s statement,’ said Andrew Russell, a professor at Stevens Institute of Technology. ‘Every jump in technology draws attention and capital away from existing technologies used by the 99 percent, which therefore undermines equality, and reduces the ability for people to get onto the ‘playing field’ in the first place.’”
In science-fiction films depicting the future, we imagine that technology lessens the gap between everyone around the world, but we need to be reminded that the future is now. Only a few people have access to the future, compare the average lifestyle of Europeans and Americans versus many African and Middle East nations. History tells us that this is the trend we will always follow.
Oh, oh. We thought technology would fix any problem. Perhaps technology exacerbates old sores and creates new wounds? Just an idle question.
Whitney Grace, July 12, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The Potential of AI Journalism
July 12, 2016
Most of us are familiar with the concept of targeted advertising, but are we ready for targeted news? Personalized paragraphs within news stories is one development writer Jonathan Holmes predicts in, “AI is Already Making Inroads Into Journalism but Could it Win a Pulitzer?” at the Guardian.
Even now, the internet is full of both clickbait and news articles generated by algorithms. Such software is also producing quarterly earnings reports, obituaries, even poetry and fiction. Now that it has been established that, at least, some software can write better than some humans, researchers are turning to another question: What can AI writers do that humans cannot? Holmes quotes Reg Chua, of Thomson Reuters:
“‘I think it may well be that in the future a machine will win not so much for its written text, but by covering an important topic with five high quality articles and also 500,000 versions for different people.’ Imagine an article telling someone how local council cuts will affect their family, specifically, or how they personally are affected by a war happening in a different country. ‘I think the results might show up in the next couple of years,’ Caswell agrees. ‘It’s something that could not be done by a human writer.’”
The “Caswell” above is David Caswell, a fellow at the University of Missouri’s Donald W Reynolds Journalism Institute. Holmes also describes:
“In Caswell’s system, Structured Stories, the ‘story’ is not a story at all, but a network of information that can be assembled and read as copy, infographics or any other format, almost like musical notes. Any bank of information – from court reports to the weather – could eventually be plugged into a database of this kind. The potential for such systems is enormous.”
Yes, it is; we are curious to see where this technology is headed. In the meantime, we should all remember not to believe everything we read… was written by a human.
Cynthia Murrell, July 12, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Six Cybercriminal Archetypes from BAE Systems
July 11, 2016
Tech-security firm BAE Systems has sketched out six cybercriminal types, we learn from “BAE Systems Unmasks Today’s Cybercriminals” at the MENA Herald. We’re told the full descriptions reveal the kinds of havoc each type can wreak, as well as targeted advice for thwarting them. The article explains:
“Threat intelligence experts at BAE Systems have revealed ‘The Unusual Suspects’, built on research that demonstrates the motivations and methods of the most common types of cybercriminal. The research, which is derived from expert analysis of thousands of cyber attacks on businesses around the world. The intention is to help enterprises understand the enemies they face so they can better defend against cyber attack.”
Apparently, such intel is especially needed in the Middle East, where cybercrime was recently found to affect about 30 percent of organizations. Despite the danger, the same study from PwC found that regional companies were not only unprepared for cyber attacks, many did not even understand the risks.
The article lists the six cybercriminal types BAE has profiled:
“The Mule – naive opportunists that may not even realise they work for criminal gangs to launder money;
The Professional – career criminals who ‘work’ 9-5 in the digital shadows;
The Nation State Actor – individuals who work directly or indirectly for their government to steal sensitive information and disrupt enemies’ capabilities;
The Activist – motivated to change the world via questionable means;
The Getaway – the youthful teenager who can escape a custodial sentence due to their age;
The Insider – disillusioned, blackmailed or even over-helpful employees operating from within the walls of their own company.”
Operating in more than 40 countries, BAE Systems is committed to its global perspective. Alongside its software division, the company also produces military equipment and vehicles. Founded in 1999, the company went public in 2013. Unsurprisingly, BAE’s headquarters are in Arlington, Virginia, just outside of Washington DC. As of this writing, they are also hiring in several locations.
Cynthia Murrell, July 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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