Yesterday I was sitting in a very interesting meeting with some experts in data visualisation. There was a lot of impressive things presented and the name of Wii remote and Kinect were mentioned a couple of time. As I observed so far, these devices are used as cheap way to get sensors. And they certainly deliver, in the field of user interfaces as well as for robotics there have been achievements made thanks to these peripherals. But why does nobody seem to be using the complete gaming devices? Even the research field of serious gaming shows little overlap with the console gaming industry.
I’m a fan of Nintendo so my argumentation will be a bit Nintendo-centric, but the same point could easily be made about the devices from Nintendo competitors. Developing data visualisation on a Wii-U, or a handled device like the 3DS, has the potential to save time and reach a greater audience. The development kit sold to the gaming industry are reasonably priced and give access to a consumer-product grade gaming toolkit that are just ready to use. As far as the cheap hardware argument goes, the Wii-U is rather interesting: it’s a strong GPU with HDMI output associated to a tablet with all the sensors one may expect. There are also pointing capabilities inherited from the Wii and a dedicated social network for applications running on the Wii-U. Outside of gaming, this social network is already being used on the Wii-U for social TV and will certainly be used for new incarnation of services that used to be on the Wii (Weather, Polls, …). All of this works out of the box, no need to hack new things to get on making great interactive visualisation or serious games.
Then comes the argument of coding for a dedicated platform. It is true that the Wii-U runs a dedicated operating system which can be expect to be deployed on all Nintendo’s devices but not outside of Nintendo’s realm (pretty much like Apple’s iOS !). So far, Nintendo has applied a generation-1 compatibility to his devices meaning that things developed on one generation of console will work on the next one. The Wii-U runs Wii-U and Wii software. The Wii runs Wii and GameCube software, etc… Previous iterations of the backward compatibility required dedicated additional hardware but they seemed to have stopped doing that now. Thus, looking at a new generation of gaming consoles every 6 or 7 years, this gives a 12 to 14 years stability for anything developed on one platform. Another goody is that as a developer you will not need to update your visualisation to deal with the console update that will happen over this period. Actually, things are always developed for a dedicated platform. As far as picking one such platform goes, I would rather bet on the Web platform rather than Java, Android, iOS or Flash. This is the only one focusing on open standards that everyone can implement. Applications developed with modern Web technologies can run everywhere these technologies are supported (including the Wii-U, thanks to the popular WebKit !). The Google street view application for the Wii-U has been coded in HTML5, using no native code.
In term of outreach, developing our research prototype for the hardware from the gaming industry would bring our products to the living room. That is closer to a wide, diverse, share of the people whose money is actually used to fund the (public) research. If the output of a research project can make it to the market place of a console device, everybody will be able to just download it and use it from the couch. Eventually involving other family members and, now, remotely connected friends via the integrated social networking features.
Nintendo and his competitors are working hard at bringing new entertaining and social experiences. This go well beyond the mere gaming they used to focus only a couple of years ago. Entertainment giants expect us to throw out our DVD players, media players, smart TVs and music players to just use their console and a dumb (big) screen. I think it would be a waste not to consider their hardware when we plan our research activities. Let me know if you think otherwise
Last week, I attended a seminar about “Understanding and Managing Complex Systems” organised by the Royal Netherlands Academy of Arts and Sciences (KNAW) together with the Netherlands Organisation for Scientific Research (NWO). The take home message from this seminar is that 1) Complex Systems are highly popular in Amsterdam, all the 200 available seats where taken the day the registration was open and 2) Complex Systems is the science of cooperation.
In a first session, Martin Nowak explained in a very good talk that 5 different cooperation mechanisms can be observed in an evolving population. 1) Direct reciprocity: individuals cooperate if the individuals they interact with are cooperative (“Tit for Tat“), 2) Indirect reciprocity: based on reputation, this motivate cooperation by the social gain to be expected. Cooperators gain reputation points and became known as cooperators in the networks. This important mechanism could not survive without extended communication capabilities making it possible to diffuse this reputation. 3) Spatial distribution: cooperation (and defection) is better achieved in cluster of individuals, both behaviors can co-exist within different clusters of individuals. This connects with 4) Group selection: there is a multi-level aspects of group selection, infections at one scale can have more impact on another. Lastly, 5) Kin selection, Nepotism: individuals tend to cooperate more with others close to their kin and defect those that are less similar. Then, Kees Stam explained how the brain exhibits small world and scale-free properties. It is also modular with several zones dedicated to particular tasks and cooperating. Mental disorders, and also the effect of aging, maps to changes in the connectivity between the different hubs in the network. Although these results where observed on simplified networks, a full model of the network of a brain – with all its neurons – it’s on its way to be created. That will be a huge network to study!
During the second session, Dan Braha gave a fantastic talk on the importance of the in and out degree of the nodes in a network. The notion of hubs and the global degree are not enough to explain network responses and the study of the covariance between in and out degrees can provide better insights on the dissemination of messages along the connections. This talk was followed with that of Michael Batty who described the evolution of cities and some models to predict their growth and increase in complexity.
The day concluded on a pleasant musical session with Marten Scheffer playing and inviting us to reflect around the topic of complexity and interaction within our civilizations.
Update: the presentations are now visible online