We had a few things that contributed to difficulties during the first week of classes. Our last minute communication to the faculty regarding a welcome change in the time time it took them to login to a Mac in the classroom got us in trouble with some faculty. They felt that such last minute emails create a lot of confusion and concern. I agree that we could have worded it differently by starting the communication with something like “This is about an improvement to the login procedure in classrooms. However, the method you have always used will continue to work. If you are not interested in learning about the new method, you don’t have to read further.” Then a network outage on Friday afternoon disrupted activities on campus and access to the campus resources. Though we have a second connectivity through a different provider, as luck would have it, one of their equipment failed too!

After they came back up, we started seeing weird behaviors – on campus users not being able to get to media heavy resources such as Kaltura or YouTube, and Comcast customers from Massachusetts and New Hampshire were unable to get to the campus resources. Long story short, there were lot of fingerpointing between the ISPs on the actual cause of this and finally, we restored service on Saturday afternoon by clearing routing tables that were found to be corrupt, presumably from all these things going down and passing confusing information back to us.

Now that we are back on line, I thought I would write a bit about the technology “Hype Cycle“, a term coined by Gartner, a well-regarded technology research firm.  As you see in the Wikipedia article, the Hype Cycle consists of five phases.

Gartner publishes the hype cycle every year. I thought it would be interesting to see this year’s hype cycle. This was published earlier this year, therefore some of what you may be expecting to see based on developments now may not be there. As has been in the past, some of these develop in interesting ways that they can easily move across phases at rates that are different from original predictions.

What is interesting in this graphic (Please click on the graphic to see a slightly enlarged version) is how there is nothing that is marked as likely to be obsolete before reaching the plateau. There are many items listed here that are relevant to what we do and therefore we need to be keenly aware of the advances and strategize about when to jump in.

Cloud computing is in the “trough of disillusionment” here, but is expected to reach the plateau of productivity in 2-5 years. We are actually in cloud computing to significant extent, with the full expectation that it is here to stay and it is only going to get better. One way to read this hype cycle chart is that cloud computing is in the state it is in because the expectations for it was so high and it just was not able to meet all those expectations. However, the “market” will adjust its expectations based on what cloud computing can really do and it will become a mainstay for a period of time. Some of the contributors to the early hype & high expectations, like many technologies, is that any of these new technologies will solve all of our problems at no cost. We realize it has significant advantages and provides tremendous efficiencies at a cost. Compared to running local systems, it is still significantly cheaper, but it is not as cheap as we all thought it would be. How did we set those original expectations? Partly based on the hype and partly being irrational.

Big data is another one that is entering the disillusionment phase. Why? Because there are umpteen challenges with Big data that need to be handled first before it shows us the promised land! One of the worst nightmares about big data is the quality of data and the clean up that is required. Everyone I know is jumping on big data right now. I have dealt with “big data” during my graduate work and postdoc time. During the late 70’s to early 90’s, I was involved in dealing with what was “big data” then. I will write about the issues around big data later. I agree that it is past the peak of hype and reality is setting in and it will be a while for it to become mainstream (or the plateau). Gartner predicts that to be 5-10 years.

You do see terms here that you may not be familiar with, such as neurobusiness. Gartner defines it as “Neurobusiness is the capability of applying neuroscience insights to improve outcomes in customer and other business decision situations.” Quantum Computing, something I am fascinated with, is listed here in the early technology trigger phase and at least 10 years away.

This always provides you an insight into emerging technologies that are likely to pass through the hype and then settle into something that will be here to stay, or perhaps not. At least the ones listed here seem to have a future.

Enlighten yourself by scanning yourself in 3-D soon. Just be careful where on the cloud you save the scans 🙂