> software powered by machine learning models leverages data to predict rider supply and driver demand; and data scientists use data to improve machine learning models for better forecasting.
Why does any of that require real-time analysis? What's the business need for this being instantaneous? Feels very NIH...
A friend, who works for Uber, was once explaining the difference between AirBnb’s tech stack and Uber’s even though they are both “marketplaces”
In short, Uber has a ton more infrastructure because they need to do more in real time. Calculating the price of a trip from point A to point B needs to be done in real time. Then there are other factors like Pool, surge, and various rider preferences that all need to be accounted for.
Uber is sort of unique in how much of their stack nessicates real time analytics
Most businesses don't require real time forecasting, but I would speculate that Uber likely uses it to decide when and where to activate surge pricing.
Why does any of that require real-time analysis? What's the business need for this being instantaneous? Feels very NIH...