Pelle Cass has put a new spin on people-watching and taken street photography to another level with his project Selected People. For each photo in the series, he essentially crushes time-lapse photography into a single frame.
"You create a little turbulence," says Santa Fe Institute economist John Miller, who specializes in complex adaptive social systems. "By adding a little noise to the system you produce coherence in the flow." (Simplexity, pg.
Yoshua Bengio recently had a vision -- a vision of how to build computers that can learn like people do.
Terry Woodward's insight:
Human brain seems to be good at predicting and filling in patterns for recognition almost to a fault - interesting to see experimental work starting to hint at how this intuitive process make work, and kudos to the researchers for open sourcing the ideas for experimentation!
We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities across the population.
The predictability of consumer visitation patterns
Coco Krumme, Alejandro Llorente, Manuel Cebrian, Alex ("Sandy") Pentland & Esteban Moro