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What Makes Paris Look Like Paris? | December 2015 | Communications of the ACM
We argued that the "look and feel" of a city rests not so much on the few famous landmarks (e.g., the Eiffel Tower), but largely on a set of stylistic elements, the visual minutiae of daily urban life. We proposed a method that can automatically find a subset of such visual elements from a large dataset offered by Google Street View, and demonstrated some promising applications. This work is but a first step toward our ultimate goal of providing stylistic narratives to explore the diverse visual geographies of our world. Currently, the method is limited to discovering only local elements (image patches), so a logical next step would be trying to capture larger structures, both urban (e.g., facades), as well as natural (e.g., fields, rivers). Finally, the proposed algorithm is not limited to geographic data. Figure 10 shows promising results for mining discriminative patches on indoor scenes, and cars, suggesting that visual elements can be a useful tool for exploring a wide variety of image data domains
research  urbanism  ai 
6 hours ago by janpeuker
BREAKING: Author and journalist Maria Konnikova becomes PokerStars Ambassador
On what she credits with her success so far
"I think it's a combination of factors. First, I've completely immersed myself in poker. When I'm not playing, I'm studying--8, 9 hours a day. It's an incredibly intense regime, but one that I determined was necessary if I had any shot of ramping up and improving in a short period of time. So, hard work is definitely a huge part of it.

"That, and the fact that I do have a different background from most players, in psychology and writing; I've tried to leverage that to poker to gain an edge at the table in situations where I don't necessarily have the same level of experience as everyone else.
luck  poker  research 
7 hours ago by craniac
People are averse to machines making moral decisions - ScienceDirect
"Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is ‘no’—in part because machines lack a complete mind. Studies 1–6 find that people are averse to machines making morally-relevant driving, legal, medical, and military decisions, and that this aversion is mediated by the perception that machines can neither fully think nor feel. Studies 5–6 find that this aversion exists even when moral decisions have positive outcomes. Studies 7–9 briefly investigate three potential routes to increasing the acceptability of machine moral decision-making: limiting the machine to an advisory role (Study 7), increasing machines’ perceived experience (Study 8), and increasing machines’ perceived expertise (Study 9). Although some of these routes show promise, the aversion to machine moral decision-making is difficult to eliminate. This aversion may prove challenging for the integration of autonomous technology in moral domains including medicine, the law, the military, and self-driving vehicles."
research  ai  decisionmaking  morals  ethics  via:marginalrevolution 
9 hours ago by danhon
Twitter
RT : No Indian university among global top 100, with highest rank in 2018 being 420--a 5-year low. Teaching, h…
research  from twitter_favs
9 hours ago by Varna

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