The dark side of an operations researcher. Or how operations research can be a funny subject. Wanna join me?.
Trough La Pastilla Roja I know about another cloud-based file-storage system: Clever-Safe.
This one though has a slightly different business model, since the later has been articullated as a FLOSS project backed up by a commercial arm, wether the former keeps the software propietary and has arranged it as a social tool.
Both, however, seem to rely on the same mathematical foundation.
Voilà!, new company developes new technology that improves cloud storage; that’s Wuala. I knew from The Economist.
These guys have been more than three years constructing their architecture which consists of… your spare bandwith and disk space. By means of brand new technology based on mathematical polinomial analysis, your files are stored all over the social storing network minimising the redundancy (yes, there’s no whole file stored in a single computer neither a single computer storing a whole file, always taking into account the probability of a computer being offline). So that, hail to private cloud computing.
And I find funny (but clever) their business model: "Need more storage? No problem. Get the storage plan that fits your needs. Our technology allows us to offer extra storage at extremely competitive rates." (extracted from Wuala’s web, the underlined is ours). Sure it is!, but don’t miss their R&D costs during all this three years plus the extraordinary profit they deserve due to the clever breakthrough.
Cheers!!!
That’s an easy question?, so let’s found an easy answer.
Then: ARE YOU A PYTHAGOREAN OR-ER?, or you think maths won’t solve everything?; do you believe in the mighty power of maths?, or you think sometimes are flawed?; and so on, and on, and on…
Now, seriously: I don’t believe in extremes, neither believe you believe so.
Yesterday I was talking to my friend and colleague Pau Rausell-Köster, from the Research Unit in Cultural Economics (Universitat de València), about the Netflix Prize. We were discussing about the foundations of taste and preferences, and how it was quite difficult to, by means of a devil reductionism, create a mathematical model that could predict how you’re going to rate a movie. The question was: it works!.
This conversation though led to another mathematical model it’s been used for a while by a company called Polyphonic HMI S.L. to predict if a song will be successful (aka “a HIT”). They use a methodology they have named as “Hit Song Science”, which basically uses “Spectral Decomposition” to get different musical attributes for all the songs they have analysed (3.5 million to date). They, they apply clustering techniques to the songs that have been a success (aka “a HIT”) in the last 5 years (I imagine, the time-frame is just to take out the trends and account for changes/evolution in people’s preferences). Then, they are able to predict if a new song will succeed in the market and they asign a rating (controlling type-I error).
There’s only a downsize: would the record companies invest in promoting songs with low rating?. This would affect the song to the extent of not helping it to become a hit, so, again our beloved maths would be changing the course of events and distorting the model by means of the feedback in flawed data (the reverse, type-II error, could as well happen, bad songs evaluated as possible hits being highly promoted and succeeding). Moreover, if this happens to be in a big scale, innovation in music creation is aborted…, unless… you’re brave and forget the model!.
PS For the Netflix Prize Teams: food for thought.
