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A Hollywood blockbuster can take a million person-hours to produce and only two hours to consume. But now, cheap and universal tools of creation (megapixel phone cameras, Photoshop, iMovie) are quickly reducing the effort needed to create moving images.

The best editors can remix video as fast as you might type.

TimeTube is the visual equivalent of a citation index; instead of tracking which scholarly papers cite other papers, it tracks which videos cite other videos. All of these small innovations enable a literacy of the screen.

In classic cinematography, a film is planned out in scenes; the scenes are filmed (usually more than once); and from a surfeit of these captured scenes, a movie is assembled. Sometimes a director must go back for “pickup” shots if the final story cannot be told with the available film. With the new screen fluency enabled by digital technology, however, a movie scene is something more flexible: it is like a writer’s paragraph, constantly being revised. Scenes are not captured (as in a photo) but built up incrementally. Layers of visual and audio refinement are added over a crude outline of the motion, the mix constantly in flux, always changeable.

In the great hive-mind of image creation, something similar is already happening with still photographs. Every minute, thousands of photographers are uploading their latest photos on the Web site Flickr. The more than three billion photos posted to the site so far cover any subject you can imagine; I have not yet been able to stump the site with a request. Flickr offers more than 200,000 images of the Golden Gate Bridge alone. Every conceivable angle, lighting condition and point of view of the Golden Gate Bridge has been photographed and posted. If you want to use an image of the bridge in your video or movie, there is really no reason to take a new picture of this bridge. It’s been done. All you need is a really easy way to find it. Similar advances have taken place with 3D models. On Google SketchUp’s 3D Warehouse, you can find insanely detailed three-dimensional virtual models of most major building structures of the world. Need a street in San Francisco? Here’s a filmable virtual set. With powerful search and specification tools, high-resolution clips of any bridge in the world can be circulated into the common visual dictionary for reuse. Out of these ready-made “words,” a film can be assembled, mashed up from readily available parts. The rich databases of component images form a new grammar for moving images.

hyperlinks, which connect one piece of text to another

tags, which categorize a selected word or phrase for later sorting.

All these inventions (and more) permit any literate person to cut and paste ideas, annotate them with her own thoughts, link them to related ideas, search through vast libraries of work, browse subjects quickly, resequence texts, refind material, quote experts and sample bits of beloved artists. These tools, more than just reading, are the foundations of literacy.

Expert software can be used to identify the key frames in a film in order to maximize the effectiveness of the summary.

Researchers have started training computers to recognize a human face. Specialized software can rapidly inspect a photograph’s pixels searching for the signature of a face: circular eyeballs within a larger oval, shadows that verify it is spherical. Once an algorithm has identified a face, the computer could do many things with this knowledge: search for the same face elsewhere, find similar-looking faces or substitute a happier version

With our fingers we will drag objects out of films and cast them in our own movies. A click of our phone camera will capture a landscape, then display its history, which we can use to annotate the image. Text, sound, motion will continue to merge into a single intermedia as they flow through the always-on network. With the assistance of screen fluency tools we might even be able to summon up realistic fantasies spontaneously. Standing before a screen, we could create the visual image of a turquoise rose, glistening with dew, poised in a trim ruby vase, as fast as we could write these words. If we were truly screen literate, maybe even faster. And that is just the opening scene.

We tend to think the tiger represents the animal kingdom, but in truth, a grasshopper is a truer statistical example of an animal. The handcrafted Hollywood film won’t go away, but if we want to see the future of motion pictures, we need to study the swarming food chain below — YouTube, indie films, TV serials and insect-scale lip-sync mashups — and not just the tiny apex of tigers.

The oral skills of memorization, recitation and rhetoric instilled in societies a reverence for the past, the ambiguous, the ornate and the subjective. Then, about 500 years ago, orality was overthrown by technology.

A new distribution-and-display technology is nudging the book aside and catapulting images, and especially moving images, to the center of the culture. We are becoming people of the screen. The fluid and fleeting symbols on a screen pull us away from the classical notions of monumental authors and authority

Even the greatest writers do their magic primarily by rearranging formerly used, commonly shared ones. What we do now with words, we’ll soon do with images.

We tend to think the tiger represents the animal kingdom, but in truth, a grasshopper is a truer statistical example of an animal. The handcrafted Hollywood film won’t go away, but if we want to see the future of motion pictures, we need to study the swarming food chain below — YouTube, indie films, TV serials and insect-scale lip-sync mashups — and not just the tiny apex of tigers. The bottom is where the action is, and where screen literacy originates.

Digital technology gives the professional a new language as well. An image stored on a memory disc instead of celluloid film has a plasticity that allows it to be manipulated as if the picture were words rather than a photo

Digital technology gives the professional a new language as well. An image stored on a memory disc instead of celluloid film has a plasticity that allows it to be manipulated as if the picture were words rather than a photo.

As moving images become easier to create, easier to store, easier to annotate and easier to combine into complex narratives, they also become easier to be remanipulated by the audience. This gives images a liquidity similar to words. Fluid images­ made up of bits flow rapidly onto new screens and can be put to almost any use. Flexible images migrate into new media and seep into the old. Like alphabetic bits, they can be squeezed into links or stretched to fit search engines, indexes and databases. They invite the same satisfying participation in both creation and consumption that the world of text doe

The recent live-action feature movie “Speed Racer,” while not a box-office hit, took this style of filmmaking even further. The spectacle of an alternative suburbia was created by borrowing from a database of existing visual items and assembling them into background, midground and foreground. Pink flowers came from one photo source, a bicycle from another archive, a generic house roof from yet another. Computers do the hard work of keeping these pieces, no matter how tiny and partial they are, in correct perspective and alignment, even as they move. The result is a film assembled from a million individual existing images.

t is a formidable task, but in the past decade computers have gotten much better at recognizing objects in a picture than most people realize. Researchers have started training computers to recognize a human face. Specialized software can rapidly inspect a photograph’s pixels searching for the signature of a face: circular eyeballs within a larger oval, shadows that verify it is spherical. Once an algorithm has identified a face, the computer could do many things with this knowledge: search for the same face elsewhere, find similar-looking faces or substitute a happier version.

It is a formidable task, but in the past decade computers have gotten much better at recognizing objects in a picture than most people realize. Researchers have started training computers to recognize a human face. Specialized software can rapidly inspect a photograph’s pixels searching for the signature of a face: circular eyeballs within a larger oval, shadows that verify it is spherical. Once an algorithm has identified a face, the computer could do many things with this knowledge: search for the same face elsewhere, find similar-looking faces or substitute a happier version.

Academic research has produced a few interesting prototypes of video summaries but nothing that works for entire movies. Some popular Web sites with huge selections of movies (like porn sites) have devised a way for users to scan through the content of full movies quickly in a few seconds. When a user clicks the title frame of a movie, the window skips from one key frame to the next, making a rapid slide show, like a flip book of the movie. The abbreviated slide show visually summarizes a few-hour film in a few seconds. Expert software can be used to identify the key frames in a film in order to maximize the effectiveness of the summary.

way for users to scan through the content of full movies quickly in a few seconds. When a user clicks

In the West, we became people of the book.

There were more than 10 billion views of video on YouTube in September. The most popular videos were watched as many times as any blockbuster movie.

With the new screen fluency enabled by digital technology, however, a movie scene is something more flexible: it is like a writer’s paragraph, constantly being revised. Scenes are not captured (as in a photo) but built up incrementally. Layers of visual and audio refinement are added over a crude outline of the motion, the mix constantly in flux, always changeable.

To date most fan responses appear in text form, on sites like the Internet Movie Database. But increasingly fans respond to video with video.

With full-blown visuality, I should be able to annotate any object, frame or scene in a motion picture with any other object, frame or motion-picture clip.

On Google SketchUp’s 3D Warehouse, you can find insanely detailed three-dimensional virtual models of most major building structures of the world.