Suchergebnisse

In this paper, we introduce FIT, a STREP Project sponsored by the European Union starting in 2006. The overall objective of FIT is to develop, test and validate a self-adaptive e-govemment framework based on semantic technologies that will ensure that the quality of public services is proactively and continually fitted to the changing preferences and increasing expectations of e-citizens. We give a brief overview on the FIT scenario and indicate where and how we plan to utilize Semantic Web technologies. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.

Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been involved in fatalities, including a pedestrian; and yet machine learning is unable to explain the contexts within which it operates.