Monthly Archives: December 2011

“Technical Debt”

This blog post showed up in my G+ feed from a colleague from UVA.

The author describes “technical debt” as the short-sighted decisions made in the past on a project which ultimately “come due” at some point in the future.  It examines the paradigms of ‘whiz kids’ and ‘greybeards’ and how there is a continual tug-of-war between the two camps.  While I am not sure I agree with the mass categorization, it is true that there are people who care about/plan for the future and there are people who are only focused on the tactical problem at hand.

Essentially, the author is saying “The ghosts of past decisions will bring ruin on the project’s future”.  That has to be inspired by some Shakespearian quote..


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Filed under Systems Engineering

Multi-modal analysis and Sentiment Analysis

A colleague pointed me to this Huffington Post article (which has embedded in it the TED talk “Deb Roy: The Birth Of A Word“) in a discussion about Sentiment Analysis.  I guess I have been dismissing all of the sentiment analysis discussions in the past (without really examining the ideas behind it).  I just couldn’t fathom how effective it could be — is it really better than just what a few people with some time on their hands could generate?

The TED talk started with a strange ‘experiment’ which involved wiring Deb Roy’ house with overhead video and audio in each room, and 200 terabytes of video recordings (he guess it’s probably the largest catalog of home movies).  Three years of recording, starting after the birth of his son, he brought the video to MIT and they started the analysis.  The types of analysis they are performing is extremely interesting — using multi-modal analysis to show correlation.  Proximity (spatially), socially (interaction), audio, and video all play into the analysis they performed.  Watch the video and I think you will be interested in what they are producing.

At ~12:30 min in the video, he describes how one of the MIT researchers on his team made the leap from a closed-space, controlled environment to the public-space.  Using public media (e.g. TV) as the video, and social media (e.g. Twitter) as the ‘audio’, they can start showing how the two relate much like they did with the home movies.  Social interconnectedness also was factored into the analysis.

Maybe I need to think a bit more about whether I should be dismissing these analysis ideas..

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Filed under Machine Learning