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A Computer Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page M S BE aG F 80 origin or destination, type or amount of goods being traded, name and title of the owner, or some combination of these. Numerous such clay tags have been found at various sites in the Indus civilization, bearing seal impressions on one side and impressions of woven cloth, reed matting, or other packing material on the other. If the Indus script was used for trade, as the evidence suggests, then we would expect to find signs representing numerical quantities and units of measure. Progress in this direction has recently been reported by Bryan Wells, who estimated the volumes of two pots, one bearing the inscription and the other the inscription . By showing that the estimated volume of the second pot was in fact twice that of the first, Wells was able to conclude that strokes such as and represent numbers, and the sign probably represents a unit of volume. Other efforts by Parpola and Mahadevan have assumed that at least some of the texts probably represent names. Phonetic values for specific signs can then be sug- gested by assuming an underlying language—for example, proto-Dravidian—and using the rebus principle to guess the pronunciation of pictorial signs such as “fish,” “jar,” and “arrow.” In English, for example, the rebus principle could be used to represent an abstract word such as “belief” with the picture of a bee followed by a picture of a leaf. Ancient scripts often used the rebus principle to represent language. Probabilistic models could help in this decipherment process in several ways. Recently proposed algorithms for probabilistic grammar induction could allow construction of a partial grammar for the Indus texts, facilitating the identification of root words, suffixes, prefixes, and other modifiers. This may facilitate the use of deciphering techniques similar to those applied to Linear B. Reconstructing a grammar would also allow comparison with the grammars of other languages, helping narrow down the set of candidate language families to consider when using the rebus principle. Silver Bullet Security Podcast COMPUTER AI REDUX In-depth interviews with security gurus. Hosted by Gary McGraw. www.computer.org/security/podcasts Sponsored by A site-by-site analysis of the Indus texts using probabilistic models could indicate whether different languages or dialects were spoken in different regions of the Indus civilization. Similarly, training probabilistic models on texts found on specific types of artifacts, such as seals versus tablets, could ascertain whether the content of the texts varies according to artifact type. In summary, the study of the Indus script has emerged as an exciting area of interdisciplinary research, offering a unique opportunity for probabilistic models to shed new light on one of the world’s oldest civilizations. Rajesh P.N. Rao is an associate professor in the Department of Computer Science & Engineering at the University of Washington. Contact him at rao@cs.washington.edu. ________________ Editor: Naren Ramakrishnan, Dept. of Computer Science, Virginia Tech, Blacksburg, VA; _________ naren@cs.vt.edu _____________________________________________ A Computer Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page M S BE aG F
A Computer Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page M S BE aG F SOFTWARE TECHNOLOGIES When TV Dies, Will It Go to the Cloud? Karin Breitman and Markus Endler, PUC-Rio, Brazil Rafael Pereira and Marcello Azambuja, Globo.com Coupled with the expected growth in bandwidth through the next decade, cloud computing will change the face of TV. The increasing popularity of videos on the Internet, allied to recent advances in network technology, are drastically changing television as we know it. In the past few decades we experienced a very clear role distinction: TV channels and independent companies produced video footage to be distributed by broadcasters and consumed by passive general audiences. Roles and responsibilities were clear down the line, and everyone was happy. A few years ago this “family around the TV set” scenario began to crack. Television faced several daunting challenges as cable multiplied the number of viewing choices and hardware prices let middle-class families own as many TV sets as there were members in the family. SEA CHANGE The Internet brought the potential to completely reinvent TV. First, it let users see what they wanted, when they wanted, while suppressing the need for additional hardware. Digital video recorders, notably the TiVo, popularized the concept of letting users choose more convenient times to watch their favorite programs. However, with the increase in bandwidth availability for the last mile—via cable and asymmetric digital subscriber line (ADSL) technol- 0018-9162/10/$26.00 © 2010 IEEE ogy—it makes more sense to stream the content directly from the Internet than record it for later use. Second, and more importantly, the Net removes the barrier that separates producers, distributors, and consumers. On the Internet, anyone can produce and distribute high-quality content. As a result, there is much more content available, making the competition for audiences tougher and changing viewing habits irreversibly. Third, the Internet allows mixing and matching of multisource content. It has become commonplace for networks to mix their own footage with user-generated content to provide a more holistic experience. Video production, distribution, and selection are no longer the privilege of a few. Users now have a front seat, forcing media giants to explore new business models. From a technical viewpoint, huge challenges remain, however, including the ability to process, index, store, and distribute nearly limitless amounts of data. This is why cloud computing will play a major role in redefining TV in the next few years. RAMPING UP Electronic devices that can be used to consume content on the Internet are proliferating at an increasing rate: PCs, tablet and laptop computers, PDAs, mobile phones, handheld video game consoles, and eBook readers, Published by the IEEE Computer Society not to mention router-type devices that let regular TV sets display Internet content. It seems our lives are driven by media displays, as Steve Jobs demonstrated with his recent unveiling of the iPad. It is easy to imagine a middle-class adult in the work force soon having access to two or more such displays on a regular basis. Displays can be organized in five strata, according to their evolution (B. Mazloff, Le 5éme écran – Les medias urbains dans la ville 2.0 – editions Fyp - 2009), as Figure 1 shows. Movie projection screens were the first to appear, in open public spaces. Then came the TV and PC—no longer public, but still collective. Mobile devices followed, for personal use in both private and public environments. More recently, public electronic displays on everything from billboards to bus stops are changing the urban landscape. Fifty years ago, video was produced in a single format since its consumption was restricted to some specific displays. Today, on the other hand, several different versions are required to enable access on PCs, iPhones, PDAs, game consoles, and other devices. This is a critical problem for broadcasters, as video processing is as computationally expensive as it is data intensive, consuming time and resources. APRIL 2010 A Computer Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page M S BE aG F 81
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