There will always be outfits offering formulas and stratagems that will cut down on the risk factors in movie-making. A New Yorker article by Malcolm Gladwell is focusing on a a new permutation of this — a British- based company called Epagogix. If every producer and creative executive in this town were to embrace Epagogix, the effects upon the withered soul of Hollywood would be nothing short of demonic. And yet, to be perfectly honest, if I were running a studio I would probably take a look at it.
The principals are Dick Copaken, Nick Meaney and Sean Verity. They’re basically offering a “neural network” program that, in a Hollywood sense, counts cards at the casino. Their site says that Epagogix “works confidentially with senior management of major film studios to assist in identifying and developing scripts, and in transforming scripts with low box-office revenue potential into properties that can be profitably produced and distributed.”
“If you were developing a $75-million buddy picture for Bruce Willis and Colin Farrell, Epagogix says, it can tell you, based on past experience, what that script’s particular combination of narrative elements can be expected to make at the box office,” writes Gladwell. “If the formula says it’s a $50-million script, you pull the plug.”
The neural network, says Meaney, “can sometimes go on for hours. If you look at the computer, you see lots of flashing numbers in a gigantic grid. It’s like ‘The Matrix.’ There are a lot of computations. The guy is there, the whole time, looking at it. It eventually stops flashing, and it tells us what it thinks the American box-office will be. A number comes out.”
“The way the neural network thinks is not that different from the way a Hollywood executive thinks: if you pitch a movie to a studio, the executive uses an ad-hoc algorithm–perfected through years of trial and error–to put a value on all the components in the story. Neural networks, though, can handle problems that have a great many variables, and they never play favorites — which means (at least in theory) that as long as you can give the neural network the same range of information that a human decision-maker has, it ought to come out ahead.”