Massachusetts Institute of Technology
There’s a mesmerizing video animation on YouTube of simulated, self-driving traffic streaming through a six-lane, four-way intersection. Dozens of cars flow through the streets, pausing, turning, slowing, and speeding up to avoid colliding with their neighbors. And not a single car stopping. But what if even one of those vehicles was not autonomous? What if only one was?
In the coming decades, autonomous vehicles will play a growing role in society, whether keeping drivers safer, making deliveries, or increasing accessibility and mobility for elderly or disabled passengers.
But MIT Assistant Professor Cathy Wu argues that autonomous vehicles are just part of a complex transport system that may involve individual self-driving cars, delivery fleets, human drivers, and a range of last-mile solutions to get passengers to their doorstep – not to mention road infrastructure like highways, roundabouts, and, yes, intersections.
Caption: Cathy Wu argues that autonomous vehicles are just part of a complex transport system that may involve individual self-driving cars, delivery fleets, human drivers, and a range of last-mile solutions to get passengers to their doorstep – not to mention road infrastructure like highways, roundabouts, and, yes, intersections.
Previous image
There’s a mesmerizing
video animation on YouTube of simulated, self-driving traffic streaming through a six-lane, four-way intersection. Dozens of cars flow through the streets, pausing, turning, slowing, and speeding up to avoid colliding with their neighbors. And not a single car stopping. But what if even one of those vehicles was not autonomous? What if only one was?
Identifying what someone purchased from only the bill total
February 3, 2021MIT
At first, it seemed like the algorithm wasn’t working right.
Michael Fleder, an MIT researcher and recent alumnus working with the Laboratory for Information and Decision Systems (LIDS), had been working on an algorithm that could break down anonymized bill totals into individual item costs, creating an overview of how many people are buying a specific item or service. He was testing it out on a bulk set of data from Netflix, and although most of the data points matched to a list of the usual subscription services, there was an outlier that kept popping up at a price point too high for anything Netflix was offering.
Previous image
At first, it seemed like the algorithm wasn’t working right.
Michael Fleder, an MIT researcher and recent alumnus working with the Laboratory for Information and Decision Systems (LIDS), had been working on an algorithm that could break down anonymized bill totals into individual item costs, creating an overview of how many people are buying a specific item or service. He was testing it out on a bulk set of data from Netflix, and although most of the data points matched to a list of the usual subscription services, there was an outlier that kept popping up at a price point too high for anything Netflix was offering.