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Classifier Technology and the Illusion of Progress
A great many tools have been developed for supervised classification, ranging from early methods such as linear discriminant analysis through to modern developments such as neural networks and support vector machines. A large number of comparative studies have been
conducted in attempts to establish the relative superiority of these
methods. This paper argues that these comparisons often fail to take
into account important aspects of real problems, so that the apparent
superiority of more sophisticated methods may be something of an illusion. In particular, simple methods typically yield performance almost
as good as more sophisticated methods, to the extent that the difference
in performance may be swamped by other sources of uncertainty that
generally are not considered in the classical supervised classification
paradigm.
ai  machinelearning  cs  bigdata 
yesterday by gnat
Ceres: solving complex problems using computing muscle
Google C++ library for solving non linear equasions. used in robotics, computer vision etc
robotics  math  equasion  solving  AI 
yesterday by jcfischer
Can an Algorithm Write a Better News Story Than a Human Reporter? | Gadget Lab | Wired.com
Once Narrative Science had mastered the art of telling sports and finance stories, the company realized that it could produce much more than journalism. Indeed, anyone who needed to translate and explain large sets of data could benefit from its services. Requests poured in from people who were buried in spreadsheets and charts. It turned out that those people would pay to convert all that confusing information into a couple of readable paragraphs that hit the key points.

After realizing that turning data into stories presented an opportunity far larger than sports, the company changed its name to Automated Insights. “I used to put limitations on what we do, assuming our stories would be specific to data-rich industries,” founder Robbie Allen says. “Now I think ultimately the sky is the limit.”)


As Hammond explained what he did, the critic became agitated. Times are tough enough in journalism, he said, and now you’re going to replace writers with robots?

“I just looked at him,” Hammond recalls, “and asked him: Have you ever seen a reporter at a Little League game? That’s the most important thing about us. Nobody has lost a single job because of us.”
ai  algorithms  journalism  news  wired  data 
yesterday by mwfogleman
Amit's Game Programming Information
Procedure generation of tile worlds, AI, pathfinding etc - thorough
game  programming  procedural  content  AI 
4 days ago by jjsonick

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