Science at Uber: Improving Transportation with Artificial Intelligence
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Science at Uber: Improving Transportation with Artificial Intelligence


Data is everywhere, so the use of data
and algorithms to make better decisions can transform almost every aspect of
life and at Uber, we’re very fortunate because we’re at the center of a
transformation in transportation around the world, as well as providing
employment and work opportunities for lots of people. I’ve always been fascinated by intelligence so even when I was like 15 years old I thought I
wanted to be an AI researcher so I’m pretty consistent. I was an academic for
many, many years at various universities and I loved it, and what’s
happened in the last decade or so is that our field went from being just the
field of science where people were driven by curiosity to a field which is
really of practical value to industry. We use deep learning methods for all sorts of problems involving our understanding of cities, ETAs, traffic, our
conversational AI systems, our computer vision systems, our self-driving vehicles. The really interesting thing is that on their own, deep learning systems are not
the answer to everything. We need many, many tools to be able to solve the really, really challenging problems that we have here. If you consider the problems that we have in our marketplace where we’re trying to match drivers and
riders as efficiently as possible, we do use some deep learning methods as part of that, but we use a lot of other types of algorithms from other fields of AI,
search algorithms, optimization algorithms, etc. AI at Uber is really interesting and really, really exciting.

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