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Driving in dataland

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Thursday 15th

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16:55 | 17:35

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Theatre 25



Carlos will talk talk about a recent prototype they are developing @Cabify  of a DeepNet that can accurately predict ETAs of trips without having ever seen a map of the city, just learning from past trajectories of our assets by leveraging embeddings coming from Natural Language Processing. He will frame it with the experiments they ran in real-life, proving how such system can significantly improve the experience of our riders and drivers (mostly by doing smarter assignments and fairer pricing), and thus helps us build smarter and overall better cities. He will touch also on the technical challenge of bringing such system to production considering the scale Cabify has already.