In 2015, an A.I.-powered Twitter bot did something a little out there—avant-garde, one might say. It tweeted, “I seriously want to kill people,” and mentioned a fashion event in Amsterdam. Dutch police questioned the owner of the bot over the death threat,claiming he was legally responsible for its actions, because it was in his name and composed tweets based on his own Twitter account.
Source: slate.com
The paper attempts to predict whether crimes are gang-related using a neural network, a complex computational system modeled after a human brain that “learns” to classify or identify items based on ingesting a training dataset. The authors selected what they determined to be the four most important features (number of suspects, primary weapon used, the type of premises where the crime took place, and the narrative description of the crime) for identifying a gang-related crime from 2014–16 LAPD data and cross-referenced the crime incidents with a 2009 LAPD map of gang territory to create a training dataset for their neural network.
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Designing applications that can program computers is a long-sought grail of the branch of computer science called artificial intelligence (AI). The new application, called Bayou, came out of an initiative aimed at extracting knowledge from online source code repositories like GitHub. Users can try it out at askbayou.com.
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In our paper, Measuring the Intrinsic Dimension of Objective Landscapes, to be presented at ICLR 2018, we contribute to this ongoing effort by developing a simple way of measuring a fundamental network property known as intrinsic dimension. In the paper, we develop intrinsic dimension as a quantification of the complexity of a model in a manner decoupled from its raw parameter count, and we provide a simple way of measuring this dimension using random projections. We find that many problems have smaller intrinsic dimension than one might suspect.
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