2016 Oscars Challenge: [18] “Ex Machina” – Best Visual Effects

EX MACHINA
Andrew Whitehurst, Paul Norris, Mark Ardington and Sara Bennett



The biggest visual effect that “Ex Machina” takes part in is turning actress Alicia Vikander into an Artificial Intelligence robot, with a human face, but a robotic body. As shown in the featurette, the creators stayed away from green screens as much as possible as to be able to film in a real dramatic sense like you would any other film. In accomplishing that, the suit that Vikander wears as Ava included a full body suit, a bald cap with extra skin in place, and eventually the lights and shine to the chrome like parts. The end result is the design of a robot that we have no experienced in any other film in this genre, making it that much more special. The designers biggest task going into it was creating a robot that the audience and the characters alike could fall in love with, which was the only way this story would work.

What’s its competition? As strong a piece as “Ex Machina” is, the film itself falls towards the bottom of the pack, with the sheer volume of visual effects in “Star Wars: The Force Awakens” and “Mad Max: Fury Road” being a huge factor, as well as the fact that there is so much support for those films, as they have 10 or more nominations each. Even “The Martian” and “The Revenant” deliver in many more regards than “Ex Machina.” This isn’t to say that it’s quantity over quality, because the quality of “Ex Machina” is incredible in creating not only Ava, but the other robots, and even the house of Oscar Isaac’s character. However, do not consider “Ex Machina” a safe bet.

Previous nominations? These are the first Academy Award nominations for Andrew Whitehurst, Paul Norris, Mark Ardington and Sara Bennett.

“Ex Machina” (2015) Trailer:


madmaxfuryroad-vfx martian-vfx revenant-vfx starwarstheforceawakens-vfx


// Produced by Andrew Macdonald and Allon Reich //Directed by Alex Garland //
// Dated Viewed: Friday, January 29th, 2016 // AMAZON PRIME //  24 films – 31 days //

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