IBM Thinks Big on Data Unification
December 7, 2016
So far, the big data phenomenon has underwhelmed. We have developed several good ways to collect, store, and analyze data. However, those several ways have resulted in separate, individually developed systems that do not play well together. IBM hopes to fix that, we learn from “IBM Announces a Universal Platform for Data Science” at Forbes. They call the project the Data Science Experience. Writer Greg Satell explains:
Consider a typical retail enterprise, which has separate operations for purchasing, point-of-sale, inventory, marketing and other functions. All of these are continually generating and storing data as they interact with the real world in real time. Ideally, these systems would be tightly integrated, so that data generated in one area could influence decisions in another.
The reality, unfortunately, is that things rarely work together so seamlessly. Each of these systems stores information differently, which makes it very difficult to get full value from data. To understand how, for example, a marketing campaign is affecting traffic on the web site and in the stores, you often need to pull it out of separate systems and load it into excel sheets.
That, essentially, has been what’s been holding data science back. We have the tools to analyze mountains of data and derive amazing insights in real time. New advanced cognitive systems, like Watson, can then take that data, learn from it and help guide our actions. But for all that to work, the information has to be accessible.”
The article acknowledges that progress that has been made in this area, citing the open-source Hadoop and its OS, Spark, for their ability to tap into clusters of data around the world and analyze that data as a single set. Incompatible systems, however, still vex many organizations.
The article closes with an interesting observation—that many business people’s mindsets are stuck in the past. Planning far ahead is considered prudent, as is taking ample time to make any big decision. Technology has moved past that, though, and now such caution can render the basis for any decision obsolete as soon as it is made. As Satell puts it, we need “a more Bayesian approach to strategy, where we don’t expect to predict things and be right, but rather allow data streams to help us become less wrong over time.” Can the humans adapt to this way of thinking? It is reassuring to have a plan; I suspect only the most adaptable among us will feel comfortable flying by the seat of our pants.
Cynthia Murrell, December 7, 2016
Wisdom from the First OReilly AI Conference
November 28, 2016
Forbes contributor Gil Press nicely correlates and summarizes the insights he found at September’s inaugural O’Reilly AI Conference, held in New York City, in his article, “12 Observations About Artificial Intelligence from the O’Reily AI Conference.” He begins:
At the inaugural O’Reilly AI conference, 66 artificial intelligence practitioners and researchers from 39 organizations presented the current state-of-AI: From chatbots and deep learning to self-driving cars and emotion recognition to automating jobs and obstacles to AI progress to saving lives and new business opportunities. … Here’s a summary of what I heard there, embellished with a few references to recent AI news and commentary.
Here are Press’ 12 observations; check out the article for details on any that spark your interest: “AI is a black box—just like humans”; “AI is difficult”; “The AI driving driverless cars is going to make driving a hobby. Or maybe not”; “AI must consider culture and context”; “AI is not going to take all our jobs”; “AI is not going to kill us”; “AI isn’t magic and deep learning is a useful but limited tool”; “AI is Augmented Intelligence”; “AI changes how we interact with computers—and it needs a dose of empathy”; “AI should graduate from the Turing Test to smarter tests”; “AI according to Winston Churchill”; and “AI continues to be possibly hampered by a futile search for human-level intelligence while locked into a materialist paradigm.”
It is worth contemplating the point Press saved for last—are we even approaching this whole AI thing from the most productive angle? He ponders:
Is it possible that this paradigm—and the driving ambition at its core to play God and develop human-like machines—has led to the infamous ‘AI Winter’? And that continuing to adhere to it and refusing to consider ‘genuinely new ideas,’ out-of-the-dominant-paradigm ideas, will lead to yet another AI Winter? Maybe, just maybe, our minds are not computers and computers do not resemble our brains? And maybe, just maybe, if we finally abandon the futile pursuit of replicating ‘human-level AI’ in computers, we will find many additional–albeit ‘narrow’–applications of computers to enrich and improve our lives?
I think Press is on to something. Perhaps we should admit that anything approaching Rosie the Robot is still decades away (according to conference presenter Oren Etzioni). At this early date, we may do well to accept and applaud specialized AIs that do one thing very well but are completely ignorant of everything else. After all, our Roombas are unlikely to attempt conquering the world.
Cynthia Murrell, November 28, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Half of the Largest Companies: Threat Vulnerable
October 24, 2016
Compromised Credentials, a research report by Digital Shadows reveals that around 1,000 companies comprising of Forbes Global 2000 are at risk as credentials of their employees are leaked or compromised.
As reported by Channel EMEA in Digital Shadows Global Study Reveals UAE Tops List in Middle East for…
The report found that 97 percent of those 1000 of the Forbes Global 2000 companies, spanning all businesses sectors and geographical regions, had leaked credentials publicly available online, many of them from third-party breaches.
Owing to large-scale data breaches in recent times, credentials of 5.5 million employees are available in public domain for anyone to see. Social networks like LinkedIN, MySpace and Tumblr were the affliction points of these breaches, the report states.
Analyzed geographically, companies in Middle-East seem to be the most affected:
The report revealed that the most affected country in the Middle East – with over 15,000 leaked credentials was the UAE. Saudi Arabia (3360), Kuwait (203) followed by Qatar (99) made up the rest of the list. This figure is relatively small as compared to the global figure due to the lower percentage of organizations that reside in the Middle East.
Affected organizations may not be able to contain the damages by simply resetting the passwords of the employees. It also needs to be seen if the information available is contemporary, not reposted and is unique. Moreover, mere password resetting can cause lot of friction within the IT departments of the organizations.
Without proper analysis, it will be difficult for the affected companies to gauge the extent of the damage. But considering the PR nightmare it leads to, will these companies come forward and acknowledge the breaches?
Vishal Ingole, October 24, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Is the Cloud Really Raining Dollar Signs?
October 5, 2016
Cloud computing offers people the ability to access their files from any place in the world as long as they have a good Internet connection and a cloud account. Many companies are transferring their mainframes to the cloud, so their employees can work remotely. Individuals love having their files, especially photos and music, on the cloud for instantaneous access. It is a fast growing IT business and Forbes reports that “Gartner Predicts $111B In IT Spend Will Shift To Cloud This Year Growing To Be $216B By 2020.”
Within the next five years it is predicted more companies will shift their inner workings to the cloud, which will indirectly and directly affect more than one trillion projected to be spent in IT. Application software spending is expected to shift 37% towards more cloud usage and business process outsourcing is expected to grow 43%, all by 2020.
Why wait for 2020 to see the final results, however? 2016 already has seen a lot of cloud growth and even more is expected before the year ends:
$42B in Business Process Outsourcing IT spend, or 35% of the total market, is forecast to shift to the cloud this year. 25% of the application software spending is predicted to shift to the cloud this year, or $36B.
Gartner is a respected research firm and these numbers are predicting hefty growth (here is the source). The cloud shift will surely affect more than one trillion. The bigger question is will cloud security improve enough by 2020 that more companies will shift in that direction?
Whitney Grace, October 5, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
eBay Struggles with Cluttered, Unstructured Data, Deploys Artificial Intelligence Strategy
May 24, 2016
The article on Forbes titled eBay’s Next Move: Artificial Intelligence To Refine Product Searches predicts a strong future for eBay as the company moves further into machine learning. For roughly six years eBay has been working with Expertmaker, a Swedish AI and analytics company. Forbes believes that eBay may have recently purchased Expertmaker. The article explains the logic behind this logic,
“One of the key turnaround goals of eBay is to encourage sellers to define their products using structured data, making it easier for the marketplace to show relevant search results to buyers. The acquisition of Expertmaker should help the company in this initiative, given its expertise in artificial intelligence, machine learning and big data.”
The acquisition of Expertmaker should allow for a more comprehensive integration of eBay’s “noisy data.” Expertmaker’s AI strategy is based in genetics research, and has made great strides in extracting concealed value from data. For eBay, a company with hundreds of millions of listings clogging up the platform, Expertmaker’s approach might be the ticket to achieving a more streamlined, categorized search. If we take anything away from this, it is that eBay search currently does not work very well. At any rate, they are taking steps to improve their platform.
Chelsea Kerwin, May 24, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
How Multitasking Alters Our Brains
December 22, 2015
An article at Forbes, “Is Technology Making Us Dumb and Numb?” brings neuroscience to bear on the topic, and the conclusion is not pretty. Contributor Christine Comaford, who regularly writes about neuroscience in relation to leadership, tells us:
“Multitasking reduces gray matter density in the area of the brain called the Anterior Cingulate Cortex (ACC)…. The ACC is involved in a number of cognitive and emotional functions including reward anticipation, decision-making, empathy, impulse control, and emotion. It acts like a hub for processing and assigning control to other areas of the brain, based on whether the messages are cognitive (dorsal) or emotional (ventral). So when we have reduced gray matter density in the ACC due to high media multitasking, over time we see reduced ability to make sound decisions, to modulate our emotions, to have empathy and to connect emotionally to others.”
Hmm, is that why our national discourse has become so uncivil in recent years? See the article for a more detailed description of the ACC and the functionality of its parts. Maybe if we all kick the multitasking habit, the world will be a slightly kinder place.
Cynthia Murrell, December 22, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Big Data Myths Debunked
December 4, 2015
An abundance of data is not particularly valuable without the ability to draw conclusions from it. Forbes recognizes the value of data analysis in, “Text Analytics Gurus Debunk Four Big Data Myths.” Contributor Barbara Thau observes:
“And while retailers have hailed big data as the key to everything from delivering shoppers personalized merchandise offers to real-time metrics on product performance, the industry is mostly scratching its head on how to monetize all the data that’s being generated in the digital era. One point of departure: Over 80% of all information comes in text format, Tom H.C. Anderson, CEO of, which markets its text analytics software to clients such as Coca-Cola KO +0.00% told Forbes. So if retailers, for one, ‘aren’t using text analytics in their customer listening, whether they know it or not, they’re not doing too much listening at all,’ he said.”
Anderson and his CTO Chris Lehew went on to outline four data myths they’ve identified; mistakes, really: a misplaced trust in survey scores; putting more weight on social media data than direct contact from customers; valuing data from new sources over the customer-service department’s records, and refusing to keep an eye on what the competition is doing. See the article for the reasons these pros disagree with each of these myths.
Text analytics firm OdinText promises to draw a more accurate understanding from their clients’ data collections, whatever industry they are in. The company received their OdenText patent in 2013, and was incorporated earlier this year.
Cynthia Murrell, December 4, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
How Semantic Technology Will Revolutionize Education
November 27, 2015
Will advanced semantic technology return us to an age of Socratic education? In a guest post at Forbes, Declara’s Nelson González suggests that’s exactly where we’re heading; the headline declares, “The Revolution Will Be Semantic: Web3.0 and the Emergence of Collaborative Intelligence.” In today’s world, stuffing a lot of facts into each of our heads is much less important than the ability to find and share information effectively. González writes:
“Most importantly, Web3.0 is opening paths to collaborative intelligence. Isolated individual learning is increasingly irrelevant to organizational health, which is measured largely through group metrics. Today, public and private institutions live or die based on the efficiency, innovation, and impact of corporate efforts.”
The post points to content curators like Flipboard and Pinterest as examples of such collective adaptive capacity, then looks at effects this shift is already beginning to have on education. González gives a couple of examples he’s seen around the world, and discusses ways collaboration software like his company’s can facilitate new ways of learning. See the article for details. He writes:
“Web 3.0 is unleashing a kind of ‘back to the future’ innovation, the digital democratization of what élites have always practiced: deep learning through imitative apprenticeship, humanistic personalization via real-time observation, and mastery through crowdsourced validation. Silicon Valley is thus enabling us all to become the sons and daughters of Socrates.”
Launched in 2012, Declara set out to build better bridges between online sources of knowledge. The company is based in Palo Alto, California.
Cynthia Murrell, November 27, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Forbes Bitten by Sci-Fi Bug
September 1, 2015
The article titled Semantic Technology: Building the HAL 9000 Computer on Forbes runs with the gossip from the Smart Data Conference this year. Namely, that semantic technology has finally landed. The article examines several leaders of the field including Maana, Loop AI Labs and Blazegraph. The article mentions,
“Computers still can’t truly understand human language, but they can make sense out of certain aspects of textual content. For example, Lexalytics (www.lexalytics.com) is able to perform sentiment analysis, entity extraction, and ambiguity resolution. Sentiment analysis can determine whether some text – a tweet, say, expresses a positive or negative opinion, and how strong that opinion is. Entity extraction identifies what a paragraph is actually talking about, while ambiguity resolution solves problems like the Paris Hilton one above.”
(The “Paris Hilton problem” referred to is distinguishing between the hotel and the person in semantic search.) In spite of the excitable tone of the article’s title, its conclusion is much more measured. HAL, the sentient computer from 2001: A Space Odyssey, remains in our imaginations. In spite of the exciting work being done, the article reminds us that even Watson, IBM’s supercomputer, is still without the “curiosity or reasoning skills of any two-year-old human.” For the more paranoid among us, this might be good news.
Chelsea Kerwin, September 1, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Search Companies: Innovative or Not?
June 11, 2015
Forbes’ article “The 50 Most Innovative Companies Of 2014: Strong Innovators Are Three Times More Likely To Rely on Big Data Analytics” points out how innovation is strongly tied to big data analytics and data mining these days. The Boston Consulting Group (BCG) studies the methodology of innovation. The numbers are astounding when companies that use big data are placed against those who still have not figured out how to use their data: 57% vs. 19%.
Innovation, however, is not entirely defined by big data. Most of the companies that rely on big data as key to their innovation are software companies. According to Forbes’ study, they found that 53% see big data as having a huge impact in the future, while BCG only found 41% who saw big data as vital to their innovation.
Big data cannot be and should not be ignored. Forbes and BCG found that big data analytics are useful and can have huge turnouts:
“BCG also found that big-data leaders generate 12% higher revenues than those who do not experiment and attempt to gain value from big data analytics. Companies adopting big data analytics are twice as likely as their peers (81% versus 41%) to credit big data for making them more innovative.”
Measuring innovation proves to be subjective, but one cannot die the positive effect big data analytics and data mining can have on a company. You have to realize, though, that big data results are useless without a plan to implement and use the data. Also take note that none of the major search vendors are considered “innovative,” when a huge part of big data involves searching for results.
Whitney Grace, June 11, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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