INSUBCONTINENT EXCLUSIVE:
self-driving car startup founded by Amar Shah and Alex Kendall, two machine learning PhDs from University of Cambridge, is de-cloaking today
conventional thinking on self-driving cars.Specifically, as Wayve CEO Shah explained in a call last week, the young company believes that
the key to making an autonomous vehicle that is truly just that (i.e
able to drive safely in any environment it is asked to), is a much greater emphasis on the self-learning capability of its software
In other words, self-driving cars is an AI problem first and foremost, and one that he and co-founder Kendall argue requires a very specific
our system, which would learn from experience and not simply be given if-else statements
Our learning-based system will be safer in unfamiliar situations than a rule-based system which would behave unpredictably in a situation it
one city can quickly adapt to the differences in a completely new city, without having to be given extra training or instruction beforehand
are throwing an engineering mindset at making vehicles autonomous, in the sense of designing rule-based systems that try to pre-empt and
deal with every edge case, whilst in tandem adding more sensors and capturing more data
by getting something working because they have stakeholders who have been investing for a decade into autonomous driving
once it understands what it sees
Wayve uses end-to-end machine learning to drive cars autonomously, with little data, in novel environments
the ten-person Wayve is said to be made up of experts in robotics, computer vision and artificial intelligence from both Cambridge and
Oxford universities, who have previously worked at the likes of NASA, Google, Facebook, Skydio and Microsoft
Their work ranges from using deep learning for visual scene understanding to autonomous decision-making in uncertain environments
with the academic background and technical capabilities to at all have a credible shot at this
You only stand a chance to compete against Google, Uber, et al
