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Indexing even the digital content. satisfy both Google and users
As an artist and media educator. I am constantly thinking about the meaning of images – how they travel and proliferate; and how our relationship with them has shifted over time and through technology. There is a growing recognition that the arrival of the Internet is challenging older models of thinking about media as it becomes networked and flung across the world with great speed. And eight years on from the so-called arrival of “Web 2. 0”. the Internet now resembles a massive archive of media inexpensive cheap canada goose femme noire . photographs and videos compete for our attention, cheap canada goose men chateau parka toronto . and websites offer us the tools to tag. share and organize this content. Faced with an overload of information. we increasingly rely on machines to assist us in organising and discovering rich media online.

But the Web was not always so overwhelming and visual. In the 1990s we “surfed” the web cheap canada goose femme noire . following trails of hyperlinks on the “information superhighway”. During this period (quaintly now referred to as “Web 1. 0”). Yahoo employed human editors to help index the web cheap canada goose femme noire for cheap . and presented the Web as a catalogue of links cheap canada goose femme noire . But today. the search engine has become the default map of the Web. and a powerful tool for directing attention online. The human archivist has been taken out of the picture – instead purchase cheap canada goose femme noire . software agents crawl the web cheap canada goose femme noire . collecting information about content and analyzing its relevance through computer algorithms. In this respect. our films, canada goose jacket in london ontario 2015 . photographs and songs now have two audiences. the human and computer. who both “see” and sense pixels in very different ways.

This demands a completely new way of thinking about media. as machines cannot easily determine the content of a video or image. Instead. the meaning of visual content is determined by evaluating the keywords cheap canada goose femme noire shop . metadata. tags and comments associated with the content. This indicates a shift away from the visual qualities of media valued by a humans in favor of different range of (text-oriented) signals which are able to be analyzed by machines. Today. photographers and video makers are share notes on how to make their content more appealing to search engine spiders and how to ensure their work gets pulled to the top of the virtual pile by computational filters such as Flickr’s Interestingness algorithm or Google’s PageRank algorithm discount canada goose jacket victoria bc .

But beyond the commercial implications of making one’s content visible and accessible across a network canada goose dawson jacket online store . there are larger theoretical implications in this shift. Historically. the study of images and their meanings has been the domain of the human sciences – for example. art theory. philosophy. sociology and cultural studies. But as we outsource the retrieval. labeling and categorization of images to machines. the meaning from images has become a problem for computer scientists canada goose down skirt store . New fields such as Content Based Image Retrival (CBIR) have had some success using pattern recognition algorithms to mimic human vision. These methods underpin “reverse image” search engines such as TinEye and AQUINE – a tool for the automatic aesthetic evaluation of images.

But for now canada goose jacket vaughan store online . the complete automation of analyzing and organizing visual information is some way off. It is therefore salutary to note that the one thing that makes us human – for now – is the ability to watch a video or view an image and translate it into words.

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