At Filtrbox, we spent the better part of the last three years solving the information overload problem by separating the signal from the noise. With that problem yet to be completely solved, I am already dead smack in the middle of a signal overload problem.

Needless to say, I am used to a great signal because I developed and used Filtrbox for my content filtering. However,  recently my “Folksabox” (human version of Filtrbox powered by folks) , which is Twitter, has also started to produce ever-increasing large quantities of quality signal that is absolutely overwhelming and is now almost impossible to keep up with.  I credit my signal overload to the quality of content shared by people I follow on Twitter.  The majority of the people I follow are sharing thoughts, opinions and notions that they have put a lot of thought into, they are also sharing very valuable data/content (this may not reflect everyone’s experience on Twitter, I tend to follow people and organizations on Twitter who have an inherent understanding and appreciation of its value as an information dissemination/opinion sharing tool).

Too much signal has become a problem for me. As I write this post, I lament as I watch a steady stream of great content that I would love to read but I know is going to go unread because there is just too much of it and I don’t have enough time in the day to do so.  On a good day, I manage to read just 1% of the total amount of content that I would love to read. For me, this is creating an information poverty of a different kind. I am not well informed despite too much good information (try to figure that one out). Given the increase in the zettabytes of content being generated, this problem is bound to get worse – this is just the beginning.

How do we solve the problem of signal overload on our way to becoming SWIFs (super well-informed information freaks)? Until we, ordinary humans, have the means and capacity to absorb large amounts of data and information in a short time, we’ll settle for good ‘ol algorithmic solutions.  The solution lies not in filtering out signal further to get another uber-signal. The solution lies in the extraction of important data, facts and opinion from the signal in order to reduce the amount of information so that it can be human-consumable within a reasonable  amount of time.  Today, there are a few products that perform content summarization but like other NLP-related products (e.g. sentiment), none of them do it well and there is still a long way to go. Given that we are still a long ways, in my opinion, this one of the major “whats next” areas in information processing (are you listening future Techstars 2011 applicant). I hope we can start working on signal overload solutions soon because the problem is bound to get worse.

]]> http://tomchikoore.com/2010/07/08/i-have-a-signal-overload-problem/feed/ 4 http://tomchikoore.com/2010/02/02/guest-speaker-event-filtrbox-a-case-study-from-start-up-to-exit/ http://tomchikoore.com/2010/02/02/guest-speaker-event-filtrbox-a-case-study-from-start-up-to-exit/#comments Tue, 02 Feb 2010 17:57:45 +0000 tomchikoore http://tomchikoore.com/?p=185 I will be speaking at the Rockies Venture Club dinner meeting on February 9, 2010 at the Denver Athletic Club. The title of the event is “Filtrbox – A Case Study from Start-up to Exit”.

It will be “be a fascinating look at how you go from startup, through funding, to building out the sales to investor management to exit – all in two years!”. It’s a review of Life in the Startup Lane. If you are interested in attending, register at the Rockies Venture Club web site here.

PS: For speaking engagement requests, contact me at tom [at] tomchikoore.com