Image by Federico Fieni

I then asked my friend, “so why would they ever use the Google (non open source) license version.” (EDIT: One of the commenters below pointed out that all Android is open source, and the Google apps pack, including the GPS, is licensed on top. Doesn’t change the argument, but wanted the correct data included here.) Here was the big punch line – because Google will give you ad splits on search if you use that version! That’s right; Google will pay you to use their mobile OS. I like to call this the “less than free” business model. This is a remarkable card to play. Because of its dominance in search, Google has ad rates that blow away the competition. To compete at an equally “less than free” price point, Symbian or windows mobile would need to subsidize. Double ouch!!

From the “Google is the new Microsoft” department:  Bill Gurley writes about Google’s bundling offer of free turn-by-turn navigation with their Android mobile OS, and how it’s a case of Google using their dominance as leverage to pay people to adopt their product.  Hmm…where have I heard this before?  Though the practice isn’t quite as new as Gurley makes it sound, the article is interesting because it goes into the relationships Google established and broke off as it’s Maps service developed.  Again, there’s a familiar template:  Buy data and expertise until you can ramp up your own service that competes with the people you were just partnered with at a level that ensures you will win.

I do have to wonder, though, if building critical data applications on a framework that is dependent upon advertising dollars is a good idea.  Look at what has happened to journalism, a socially-critical industry that became tied to advertising money–the almost inevitable response to increased competition has been the development of outlets like Fox and MSNBC.  Google’s less than free model may be tying people to their version of Android for the moment, but that will only last as long as it takes for somebody to figure out how to make more money using the true open source version of Android than they can get from Google’s kickbacks.  When the competition inevitably increases, what happens then?  Can Google continue to make money without coloring their data to make whatever constituents give them the most cash happy?  With other mapping companies having been put out of business in the interim, it could well turn into another case of money-generated reality.

via Google Redefines Disruption: The “Less Than Free” Business Model « abovethecrowd.com.

Bus.tops – a city wide canvas for sharing the art of our streets, our communities, our London, our experience.

Bus.tops – if you can’t tell from the slide above that I’m sure made much more sense with people talking over it – is a series of LED panels that are going to be attached to the top of bus stops around London for people to view from the second floor of the famous double-decker buses.  The content will come from a number of artists and programmers, and will presumably be made interactive using the interfaces shown in the slide.  It seems like an interesting way to make a piece that is unique to London by utilizing a resource that wouldn’t be available anywhere else in the world (or at least, not as famously available.)  I might question how much interaction would be possible during a quick stop of the bus, but that’s a challenge for the artists to work out, not me.  I’m just glad it wasn’t turned into ad space.

via a project to transform London’s Bus journeys | Bus-Tops.

Researching the history of criticality accidents made me wonder how accidental exposure to massive levels of radiation became the de rigueur method of achieving superhero-dom. And, while I suppose comic book writers would have a well-formed opinion or two on this, I decided to ask a group of people whose point of view I’d never seen–actual nuclear scientists.

via The Blue Flash: Nuclear Accidents and the Origins of Superhero Origins — Boing Boing.

[Lauren] has created a facial conditioning device dubbed the Happiness Hat. The hat measures a sensor at the wearer’s cheek to determine if the wearer is smiling. When the hat does detects the wearer is not smiling, it activates a servo that prods the wearer.

Ok.  I’m disturbed.  Maybe it’s just because I read too much Sluggy.

via Headpiece Jabbing for Smiles — Hack a Day.

Microsoft’s search engine Bing has struck a deal with Facebook and the hot micro-messaging service Twitter, a brash attempt to add real-time web updates to its search results in order to make Google look like a lumbering dinosaur.

While we’re still digesting the news of Bing adding Twitter to its search engine, Google has some news of their own: they’re about to do the same exact thing.

Searching Twitter traffic initially seems kind of odd.  Then, after a bit of thought, it starts to sound a bit better.  Finally, after a lot of reflection, it starts to venture into the realm of the bizarre.  Here a quick summary of the stages of acceptance:

1 — Oddity:  Why would you want to add Twitter traffic to a search engine?  Twitter is all about quick thoughts between you and your ten thousand closest friends.  Search engines are supposed to be good at answering questions, and most questions require more than 140 characters to answer completely.  (I’ll blithely ignore the question of whether most people doing searches actually care about complete answers.)  On first blush, it doesn’t seem like a great match.

2 — Sense:  So why would Google and Microsoft be interested in indexing tweets, then?  Assuming it’s more than just a PR chasing-buzzwords stunt (not necessarily a good assumption, but…) how would indexing tweets add value to the core of their search businesses?  Well, if you treat tweets more as metadata than search data, it starts to make more sense.  A good percentage of tweets contain links, and once you filter out spam you’re left with a lot of links that have been determined–by actual humans!–to be interesting.  Machine intelligence is great, but humans are still better at figuring out which pages are worthwhile and which aren’t…this is the idea behind Mahalo and the like.  If Google and Microsoft can mine that data to improve the quality of their hits, indexing tweets suddenly makes more sense.

3 — Nonsense:  But if that’s the goal, why make the tweets themselves searchable?  That’s going back to treating the tweets as actual data again, which seems questionable at best.  If people start to see their tweets show up in search engines that will change the way Twitter is used.  Right now it’s treated as an ephemeral medium; incorrectly in theory, since Twitter is already searchable, but given how well Twitter’s search engine works, it might actually be true.  With stories popping up all over the place reminding people to be cautious about what they put on Facebook or MySpace, does Twitter really want to be included in the list of services to fear?  I’m sure there are good reasons–probably money–for Twitter to get involved in this deal, but it’s not without risk.

via Bing Partners With Twitter and Facebook for Real-Time Search and  BREAKING: Google Announces Search Deal With Twitter.

[…] many web-based services make it difficult for you to export your data. Worse, they’ll charge you a fee for the privilege. Some offer APIs — a bonus if you’re technically astute, but a solution that leaves the average user short on options.

To prevent such headaches, Google recently launched the Data Liberation Front, an initiative within the company to ensure every one of its products has a clear, easy option for users to export their data in bulk and take their business elsewhere.

Very encouraging interview up on Webmonkey with Brian Fitzpatrick, a Google engineering manager who’s leading a team that’s making sure all the data you give to Google can actually be retrieved and ported to another service.  (Ok, not all the data…I suspect things like discovering your AdSense will be curiously absent since Google probably doesn’t consider it your data.  Though they do at least let you opt out now.)  The ability to download all of your data is great, and I hope that other online services follow suit.  Of course, there are leaks in the system (the interview mentions that metadata isn’t quite as easy to export as actual data) but it’s a start.

via Pack Up Your Data and Leave Whenever You Want It s the New Rule of the Cloud — Webmonkey.

Photo by Amanda Gyllenhaal

There’s a bit of discussion right now about a working paper coming from Serguei Netessine and Tom F. Tan at Wharton that’s wondering how solid the Long Tail effect really is.  A lot the criticism seems to come down to some definitions:

Anderson is also author of The Long Tail: Why the Future of Business Is Selling Less of More. The key difference between the opinion of the book and the study by Wharton researchers is how they define “hits” and “niches.” In the book, Anderson focuses on the definition of hits in absolute terms such as the top 10 or top 1,000 products, while Netessine and Tan argue that, to take growing product variety into account, one has to define popularity in relative terms, such as the top 1% or top 10% of products, to properly assess the presence or absence of the Long Tail.

The question of absolute v. relative definitions can obviously be looked at either way, but it seems to me that the real question is not how many total products are available (relative) but how many products are available that would not be were Netflix not shooting for the niches.  That is, if we define a hit as the top 1% and 3000 movies are stocked by a standard brick and mortar company that isn’t capable of the logistics of being a Long Tail business, then the top 30 movies are the hits across the entire industry.  For there to be a meaningful comparison between standard and Long Tail you’d have to consider that Long Tail is based on the premise that inventories are expanding and that is one of the things it is looking at, not try to calculate the expanding inventories into the definition of hits and niches.  So I guess I have to agree with Anderson on that one.

Of course, this definitional question doesn’t change some of the very good points that the paper brings up about how the Long Tail effect is being used now.  The most important one to me is the criticality of recommendation systems in a Long Tail business.  All those niche products are just overhead if consumers don’t know they’re there.  Netflix is obviously aware of the problem, given that the data used in this study was released by Netflix as part of a million dollar contest to improve their recommendation system.  Based on my own experience as a Netflix customer, I have to say improvement is sorely needed–though I might question whether the recommendation system itself is the issue or the horribly non-browsable interface Netflix uses.  (Well, really interfaces plural, since a large part of the problem is how they bounce back and forth between different looks depending on how you get to the data…but that’s a different discussion.)

It makes me wonder how much social recommendations are actually useful for Netflix.  I don’t use that system myself, and it wouldn’t be visible in the data used in this study which was just of ratings data, but it seems like improvements to the social tools used by Netflix would provide a far superior recommendation system to the algorithms developed in the competition.  For me, the issue is the lack of control that Netflix gives its customers.  For instance, I don’t have any ability to choose which movies I’ve rated or rented will be visible to which friends in any sort of granular way.  There’s no official integration between the closed “Netflix friends” community and other social networks, at least that I can find on Netflix’s site.  That alone would be incredibly valuable; the idea of social networking is to make the person the center of knowledge, not the network, and Netflix’s friends don’t allow that.

via Rethinking the Long Tail Theory: How to Define ‘Hits’ and ‘Niches’ — Knowledge@Wharton.

“We need not destroy the past; it is gone. At any moment it might reappear and seem to be and be the present. Would it be a repetition? Only if we thought we owned it, but since we don’t, it is free and so are we.”

John Cage, Lecture on Nothing

I have an article up in this month’s issue of the Open Source Business Resource journal with an introduction to some of the work I do at the Still Water lab.  It looks at how we are applying the ideas of open source software development to other types of creative production and preservation in The Pool and the Variable Media Questionnaire.  Cage’s quote above opens the article and neatly summarizes one of the assumptions built into the VMQ: creation is a constant act of renewal.  Much like software, art is only finished until the next version is released.