Source: intelligenttransport.com
Autonomous vehicle software company Oxbotica has developed and deployed deepfake technology to help expose its autonomous vehicles to near-infinite variations of the same situation – without the need for genuine real-world testing of a location.
Deepfaking uses deep learning artificial intelligence (AI) to generate fake photo-realistic images. Seeing beyond its potential to create viral internet videos, Oxbotica believes the technology will make autonomous vehicles smarter and safer, and immediately accelerate the race to autonomy.
Sophisticated deepfake algorithms allow the autonomous vehicle software firm to reproduce the same scene in poor weather or adverse conditions, and subject its vehicles to rare occurrences. The technology can even reverse road signage or ‘class switch’ where one object (e.g. a tree) is replaced with another (e.g. a building). It can also change the lighting of an image, to show a particular frame at a different time of the day or season of the year, all while ensuring shadows or reflections appear exactly as they should. It then uses these synthetic images to teach its software, producing thousands of accurately-labelled, true-to-life experiences and rehearsals which are not real but generated – even down to the rain drops on lenses.
Paul Newman, Co-Founder and CTO at Oxbotica, said: “Using deepfakes is an incredible opportunity for us to increase the speed and efficiency of safely bringing autonomy to any vehicle in any environment – a central focus of our Universal Autonomy vision. What we’re really doing here is training our AI to produce a syllabus for other AIs to learn from. It’s the equivalent of giving someone a fishing rod rather than a fish. It offers remarkable scaling opportunities.
“There is no substitute for real-world testing but the autonomous vehicle industry has become concerned with the number of miles travelled as a synonym for safety. And yet, you cannot guarantee the vehicle will confront every eventuality, you’re relying on chance encounter.
“The use of deepfakes enables us to test countless scenarios, which will not only enable us to scale our real-world testing exponentially; it’ll also be safer.”
The data is generated by an advanced teaching cycle made up of two co-evolving AIs, one is attempting to create ever more convincing fake images while the other tries to detect which are real and which have been reproduced. Oxbotica engineers have designed a feedback mechanism which sees both entities improve over time in a bid to outsmart their adversary. Over time, the detection mechanism will become unable to spot the difference, which means the deepfake AI module is ready to be used to generate data to teach other AIs.