Mobile Development: Productivity-Agnostic Opinions Abound

The U.S. has morphed into a polarized Red State - Blue State country, with a pervasive trench warfare mentality. Perhaps reflecting this wider polarization, the software developer community is both confused and deeply split on the subject of mobile device platforms. Developer rifts border on the political where Apple (iPhone), Google (Android) and Microsoft (Windows 7 Mobile) developer environments are concerned. The search for balanced reporting can be arduous and painful. Consider Galen Gruman's invective-ridden InfoWorld piece, "Windows Phone 7: Don't Bother with this Disaster." Fact and opinion are so casually intermixed that the only beneficiary is web traffic resulting from posts by believers and dissenters -- a point made by at least one commenter. On the other hand, a self-described "opinion piece" by Don Burnett at least takes the time to walk through the major IDE screens involved in mobile development so that neutral parties can reach their own conclusions about what works for their particular environment.  Bit.ly shows Gruman's piece with 2,340 links as of this writing, whereas Burnett's gets only 852.  Burnett's piece doesn't pretend to be a thorough comparison, nor does upcoming Paul Thurough's Windows Phone Secrets, but at least they take the time to present the evidence. 

Why does it matter?  Because software paradigm shifts in computing are infrequent and important.  They are opportunities in the making.  They offer a chance to absorb teachings from academia, practitioners, quality managers and consumers and do some things differently.  It's not about whether the Apple Objective C-based, Google ("App Inventor") or Microsoft platform is better.  All three were conceived a long time ago (by technology's clock).  Ideally something in some way new should emerge, or at least evolve, from previous projects, whether built by Red or Blue state companies. Something beyond flame wars and productivity-agnostic opinion pieces. ◦

Mobile Development: Productivity-Agnostic Opinions Abound

USAF HR Initiative Considers Business Rules Framework

A Business Rules Management System (BRMS) may be in the cards for the US Air Force -- at least for some Human Resources applications.  According to an Air Force Request for Information, sources are being invited to "investigate the viability of such a tool in the current Business and IT structure."  The Air Force clearly wants an off-the-shelf solution, not a custom, military-only beast.  They're looking at rules such as those involving policy, eligibility, and vocational speciality-specific requirements. The goal is to reduce application maintenance, facilitate "consistent business policy implementation across applications," and be usable by non-technical staff.  One other thing: the project being contemplated by the 554th Electronic Systems Group must work with IBM's WebSphere.

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USAF HR Initiative Considers Business Rules Framework

Feigenbaum on Domain-Specific Knowledge and Pattern Recognition

The June 2010 issue of Communications of the ACM features an interview with AI pioneer Edward A. Feigenbaum. In addition to providing his view the successes of DENDRAL and Meta-DENDRAL, he observes that "I believe that AI is mostly a qualitative science, not a quantitative science.  You are looking for places where heuristics and inexact knowledge can come into play" (p. 43).  He recaps his experience as Chief Scientist for the Secretary of the Air Force, in which he recounts his "one big report" called It's A Software-First World.

Especially noteworthy was Feigenbaum's observation about the domain-specific nature of AI:

I don’t believe there is a general pattern recognition problem. I believe that pattern  recognition, like most of human reasoning, is domain specific. Cognitive acts are surrounded by knowledge of the domain, and that includes acts of inductive behavior. So I don’t really put much hope in “general anything” for AI. In that sense I have been very much aligned with Marvin Minsky’s view of a “society of mind.” I’m very much oriented toward a knowledge-based model of mind. 

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Feigenbaum on Domain-Specific Knowledge and Pattern Recognition

Error Message Effectiveness

A poor underlying model is often revealed through casually thrown (or thrown off) error messages. One post hoc way to address this deficiency -- though it may not improve the model's weaknesses -- is to request feedback from message recipients.  Microsoft Office users are sometimes requested to indicate whether a particular message is effective, as shown in this screenshot.  Not all messages offer this feature;  it would be interesting to know how Microsoft determines which messages deserve this treatment, and what internal workflow accompanies the feedback.

Posted via email from knowlengr

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Error Message Effectiveness

Define "Mission-Critical"

Today a NetworkWorld survey asked we were "monitoring the percent of storage space being used for non-mission critical data," and whether we were currently "classifying data into tiers based on value to the business."

Risk management based upon information value is difficult, and probably seen as soft technology -- meaning that there is a perception that it need not be done. The Applied Visions project Camus attempts to address this for military applications.  To accomplish project goals, knowledge is drawn from diverse sources, and requires a complex mix of general and specialized knowledge.

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Define "Mission-Critical"

AI and Network Management: AAAI Fall Symposium Proposal

Interested in accelerating the use of artificial intelligence and knowledge sharing in network management and defense? Short fuse, but let prospective organizers know today. Be part of a proposed "Catalysts for Infusion of AI into Network Management and Defense" at the AAAI Fall 2010 Symposium. Contact me if you're interested in attending, monitoring symposium results, co-organizing, or if you just think it's a cool idea.

Problem Statement

To some extent, many existing network and service management suites incorporate ontologies, rules and perform reasoning.  They implement some form of knowledge management.  They collect, filter, aggregate and summarize vast amounts of data using dynamic algorithms that must change when network infrastructure changes. Yet with a few notable exceptions, these AI-like capabilities may not be identified as AI. This matters because, despite a relatively consistent base of domain knowledge, reusable extensible frameworks that leverage existing bodies of knowledge in AI have not evolved.  The resulting capabilities gaps are significant both to practitioners and enterprises, who face numerous challenges that could be mitigated by wider use of intelligent systems. These gaps include:

• Delays in supporting network-enabled applications in specialized user communities
• Errors and misconfigurations caused by opaque device interdependencies
• Unnecessary complexity in the deployment of new network technologies or equipment upgrades
• Weakened network defenses
• Event data overload
• Inability to represent network performance and security data in ways that satisfy human-computer interface needs

Symposium Goals and Methods

The proposed Symposium seeks, though techniques that leverage current collaboration technologies, to identify opportunities to infuse network management products with resources and capabilities from the AI body of knowledge.

Read more at the Secure Decisions web site (where I work). ◦

AI and Network Management: AAAI Fall Symposium Proposal

True or False? Psych, Music and Neuro Quiz Items From "This Is Your Brain on Music"

• Number of neurons in the human brain?  100,000,000,000, or one hundred billion (p. 87).
• Is pitch processed by hearing systems and then interpreted by the brain? Pitch is represented directly in the brain, unlike almost all other attributes of musical sound (p.29).
• Does Eastern music use microtonal scales? While it's commonly thought that "Eastern" music uses microtonal scales, in fact most cultures don't discriminate differences smaller than a semitone, or half step (p. 28)
• What Pink Floyd song is written in 7/4 time? The Pink Floyd song "Money" is written in the infrequently heard 7/4 meter, great for tripping up some toe-tappers.
• Which popular rock group intentionally changed their tuning away from A440, the usual standard?  Led Zeppelin. 

Source:  This Is Your Brain on Music: Science of a Human Obsession by Daniel J. Levitin (Plume, 2006)

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True or False? Psych, Music and Neuro Quiz Items From "This Is Your Brain on Music"