Opinion

The Future of Personalization

[Editor's Note: This guest article comes to us from Dr. Nathan Wilson, CTO of Nara. ]

Photo of Thomas Jefferson statue and modern person with smart device The Problem: Information has run amok.

There once was a time when the busiest and greatest minds –the Jeffersons, Hemingways and Darwins – would have time in their day for long walks, communion with nature, and leisurely handwritten correspondence. Today we awaken each day to an immediate cacophony of emails, tweets, websites and apps that are too numerous to navigate with full consciousness. Swimming in wires, pixels, data bits, and windows with endless tabs is toxic to you and to me, and the problem continues to escalate.

How do you connect to this teeming network without electrocuting your brain? “Filtering” is a simple, but ultimately blinding, approach that shields us from important swaths of knowledge. “Forgetting faster” is potentially a valid solution, but also underserves our mindfulness.

A History of Attempted Solutions So Far: How have we tried to solve information glut so far, and why is each solution inadequate?

Phase 1 – The Web as a Linnaean Taxonomy (1994-2000)

The first method to deal with our information explosion came in “Web 1.0” when portals like Yahoo! arose to elegantly categorize information that you could explore at your leisure. For instance, one could find information on the New England Patriots by following a trail of breadcrumbs from “Sports” to “Football” to “AFC East” and finally “New England Patriots” where you were presented with a list of topical websites.

Read more

The Varied Definitions of Machine Learning

6829447421_3bcf8da9a9_z

James Kobielus of Info World recently shared his thoughts on the best definition for machine learning. He writes, “Increasingly, the term ‘machine learning’ is… beginning to acquire a catch-all status. Or, at the very least, machine learning has become a convenient handle that today’s data scientists use to refer to the wide range of leading-edge techniques for automating knowledge and pattern discovery from fresh data, much of it unstructured. People’s working definitions of machine learning seem to be creeping into broader, vaguer territory. That’s my impression from reading the recent article “Learning and Teaching Machine Learning: A Personal Journey.” In it, author Joseph R. Barr of San Diego State University and True Bearing Analytics discusses both the history of machine learning and his own education in the topic. He states that ‘it’s safe to regard machine learning, data mining, predictive analysis, and advanced analytics as more or less synonymous’.” Read more

Do You Have the “Right to be Forgotten”?

5862184631_2126ed167f

Thomas Claburn of Information Week recently opined, “The ‘right to be forgotten,’ recognized in Article 17 of the European Union’s revision of its 1995 data protection rules, is at once admirable and asinine. Forgetfulness is often a prerequisite for forgiveness, and there are many instances when an individual or an organization deserves forgiveness. It wouldn’t be particularly helpful if a search for ‘IBM,’ for example, returned as its top result a link to a website about the company’s business with the Nazi regime. Forgetfulness is enshrined in judicial practices like the sealing of court records for juvenile offenders. It has real social value. European lawmakers are right to recognize this, but their attempt to force forgetfulness on Internet companies is horribly misguided. The right to be forgotten will cause real social harm, to say nothing of the economic and moral cost.” Read more

Keep On Keeping On

“There is nothing more difficult to plan, more doubtful of success, nor more dangerous to manage than the creation of a new order of things…. Whenever his enemies have the ability to attack the innovator, they do so with the passion of partisans, while the others defend him sluggishly, so that the innovator and his party alike are vulnerable.”
–Niccolò Machiavelli, The Prince (1513)

Atlanta's flying car laneIn case you missed it, a series of recent articles have made a Big Announcement:

The Semantic Web is not here yet.

Additionally, neither are flying cars, the cure for cancer, humans traveling to Mars or a bunch of other futuristic ideas that still have merit.

A problem with many of these articles is that they conflate the Vision of the Semantic Web with the practical technologies associated with the standards. While the Whole Enchilada has yet to emerge (and may never do so), the individual technologies are finding their way into ever more systems in a wide variety of industries. These are not all necessarily on the public Web, they are simply Webs of Data. There are plenty of examples of this happening and I won’t reiterate them here.

Instead, I want to highlight some other things that are going on in this discussion that are largely left out of these narrowly-focused, provocative articles.

First, the Semantic Web has a name attached to its vision and it has for quite some time. As such, it is easy to remember and it is easy to remember that it Hasn’t Gotten Here Yet. Every year or so, we have another round of articles that are more about cursing the darkness than lighting candles.

In that same timeframe, however, we’ve seen the ascent and burn out failure of Service-Oriented Architectures (SOA), Enterprise Service Buses (ESBs), various MVC frameworks, server side architectures, etc. Everyone likes to announce $20 million sales of an ESB to clients. No one generally reports on the $100 million write-downs on failed initiatives when they surface in annual reports a few years later. So we are left with a skewed perspective on the efficacy of these big “conventional” initiatives.

Read more

Should Microsoft Consider Bill Ruh for Its New CEO?

Ruh_Bill-081_0

Anders Bylund of the Motley Fool recently wrote an article for Daily Finance, stating, “Microsoft is looking for a new CEO as current leader Steve Ballmer polishes his golden scepter to a high shine. Ballmer will retire before August 2014, and it’s high time to find a replacement. Reuters claims to have the inside track on a few hot names. The news bureau’s anonymous sources say Microsoft’s headhunters started out with more than 40 external candidates and plenty of insiders on their wish list but have narrowed it down to a handful of internal names and about five outsiders.” Read more

Why Scale is Losing Importance

Greg Satell of Forbes recently wrote, “Digital technology has markedly evened out the playing field. Startups become billion dollar companies overnight while venerable brands like Kodak and Blockbuster hit the skids. This turn of events presents considerable challenges for managers.  While there are still some advantages to scale, the disadvantages often outweigh them.  You have lots of customers, a large workforce and stodgy institutional investors to keep happy, all of which contribute to strategic rigidity.  To compete in the new economy, we need a new playbook.” Read more

Say Hello to the “Mood Graph”

Image of various emoji facesEvan Selinger, a Fellow at the Institute for Ethics and Emerging Technology, has posted an article for Wired, in which he discusses the implications of how we have simplified the expression of emotion in the online systems we use, and how those simplified emotions are being tracked, analyzed and used.

Referring to Facebook’s addition earlier this year of a range of emotional expressions beyond “Like” and Bitly’s recent announcement of its “Feelings” tool, Selinger says, “I’m not singling out Facebook or even Bitly here; Google Plus on mobile also offers such expressions, as do a number of other websites and apps. The point is that all these interfaces are now focusing on the emotional aspects of our information diets. To put this development in a broader context: the mood graph has arrived, taking its place alongside the social graph (most commonly associated with Facebook), citation-link graph and knowledge graph (associated with Google), work graph (LinkedIn and others), and interest graph (Pinterest and others).”

Read more

The Future of Search: Semantics & More

Harsha Rao and Deepali Jain of KMWorld recently wrote, “The future of search is to not search at all. This may sound contrarian, but we are on the threshold of search technology that will eliminate the need to explicitly ask for information. Search has come a long way from its initial focus on relevance, to incorporating a social perspective, to heading towards a future of personalization where the Internet will be essentially customized to each user… In 1994, Yahoo! attempted to organize the Internet by creating the first online directory of websites. As the Internet grew, searching for relevant information became a nightmare. In 1998, Larry Page, co-founder of Google, had an idea that revolutionized search on the Internet. Drawing inspiration from citations in academic journals he developed the PageRank algorithm to rank search results by using links on millions of websites to measure the relevance of web pages.” Read more

In Defense of PRISM’s Big Data Strategy

Doug Henschen of Information Week recently shared his thoughts on the less-than-nefarious intent of the NSA’s PRISM Big Data tools. He writes, “It’s understandable that democracy-loving citizens everywhere are outraged by the idea that the U.S. Government has back-door access to digital details surrounding email messages, phone conversations, video chats, social networks and more on the servers of mainstream service providers including Microsoft, Google, Yahoo, Facebook, YouTube, Skype and Apple. But the more you know about the technologies being used by the National Security Agency (NSA), the agency behind the controversial Prism program revealed last week by whistleblower Edward Snowden, the less likely you are to view the project as a ham-fisted effort that’s ‘trading a cherished American value for an unproven theory,’ as one opinion piece contrasted personal privacy with big data analysis.” Read more

Lucena Research Launches QuantDesk™ Back Tester

Lucena Research, a leading provider of investment decision support technology, today announced the launch of QuantDesk™ Back Tester, the trading strategy simulator component of QuantDesk™. QuantDesk™ Back Tester is a realistic market simulator that allows investors to test trading strategies over critical market periods. Back Tester represents a fourth component of Lucena’s flagship QuantDesk™ cloud-based platform, which allows users to build a strategy using Lucena’s modular algorithms such as scanning, forecasting, optimizing and hedging to help investment professionals validate and refine quantitative investment strategies. Read more

NEXT PAGE >>