Historical Evolution of Artificial Intelligence: Analysis of the three main paradigm shifts in AI

Artificial intelligence (AI) can have a major impact on the way modern societies respond to the hard challenges they face. Properly harnessed, AI can create a more fair, healthy, and inclusive society. Today, AI has become a mature technology and an increasingly important part of the modern life fabric. AI is already deployed in different application domains, e.g. recommendation systems, spam filters, image recognition, voice recognition, virtual assistants, etc. It spans across many sectors, from medicine to transportation, and across decades, since the term was introduced in the 1950s. The approaches also evolved, from the foundational AI algorithms of the 1950s, to the paradigm shift in symbolic algorithms and expert system development in the 1970s, the introduction of machine learning in the 1990s and the deep learning algorithms of the 2010s. Starting with the fundamental definitions and building on the historical context, this report summarizes the evolution of AI, it introduces the “seasons” of AI development (i.e. winters for the decline and springs for the growth), describes the current rise of interest in AI, and concludes with the uncertainty on the future of AI, with chances of another AI winter or of an even greater AI spring.JRC.B.6-Digital Econom

Historical Evolution of Artificial Intelligence

Artificial intelligence (AI) can have a major impact on the way modern societies respond to the hard challenges they face. Properly harnessed, AI can create a more fair, healthy, and inclusive society. Today, AI has become a mature technology and an increasingly important part of the modern life fabric. AI is already deployed in different application domains, e.g. recommendation systems, spam filters, image recognition, voice recognition, virtual assistants, etc.It spans across many sectors, from medicine to transportation, and across decades, since the term was introduced in the 1950s. The approaches also evolved, from the foundational AI algorithms of the 1950s, to the paradigm shift in symbolic algorithms and expert system development in the 1970s, the introduction of machine learning in the 1990s and the deep learning algorithms of the 2010s.Starting with the fundamental definitions and building on the historical context, this report summarizes the evolution of AI, it introduces the “seasons” of AI development (i.e. winters for the decline and springs for the growth), describes the current rise of interest in AI, and concludes with the uncertainty on the future of AI, with chances of another AI winter or of an even greater AI spring

Numerical modeling of a Global Navigation Satellite System in a general relativistic framework

International audienceIn this article we model a Global Navigation Satellite System (GNSS) in a Schwarzschild space-time, as a first approximation of the relativistic geometry around the Earth. The closed time-like and scattering light-like geodesics are obtained analytically, describing respectively trajectories of satellites and electromagnetic signals. We implement an algorithm to calculate Schwarzschild coordinates of a GNSS user who receives proper times sent by four satellites, knowing their orbital parameters; the inverse procedure is implemented to check for consistency. The constellation of satellites therefore realizes a geocentric inertial reference system with no a priori realization of a terrestrial reference frame. We perform a simulation of position determination and show that the determination of the four coordinates with a 25-32 digit accuracy takes only around 60 ms. Effects of non-gravitational perturbations on positioning errors are assessed, and methods to reduce them are sketched. In particular, inter-links between satellites could greatly enhance stability and accuracy of the positioning system. Effects of gravitational perturbations are omitted in this paper in order to make a clearer comparison between the relativistic and non-relativistic scheme, but they will be included in subsequent work. We believe that the final algorithm will be a serious alternative to the usual post-Newtonian scheme

An Autonomous Reference Frame for Relativistic GNSS

International audienceCurrent GNSS systems rely on global reference frames which are fixed to the Earth (via the ground stations) so their precision and stability in time are limited by our knowledge of the Earth dynamics. These drawbacks could be avoided by giving to the constellation of satellites the possibility of constituting by itself a primary and autonomous positioning system, without any a priori realization of a terrestrial reference frame. Our work shows that it is possible to construct such a system, an Autonomous Basis of Coordinates, via emission coordinates. Here we present the idea of the Autonomous Basis of Coordinates and its implementation in the perturbed space-time of Earth, where the motion of satellites, light propagation, and gravitational perturbations are treated in the formalism of general relativity

An Autonomous Reference Frame for Relativistic GNSS

International audienceCurrent GNSS systems rely on global reference frames which are fixed to the Earth (via the ground stations) so their precision and stability in time are limited by our knowledge of the Earth dynamics. These drawbacks could be avoided by giving to the constellation of satellites the possibility of constituting by itself a primary and autonomous positioning system, without any a priori realization of a terrestrial reference frame. Our work shows that it is possible to construct such a system, an Autonomous Basis of Coordinates, via emission coordinates. Here we present the idea of the Autonomous Basis of Coordinates and its implementation in the perturbed space-time of Earth, where the motion of satellites, light propagation, and gravitational perturbations are treated in the formalism of general relativity

An Autonomous Reference Frame for Relativistic GNSS

International audienceCurrent GNSS systems rely on global reference frames which are fixed to the Earth (via the ground stations) so their precision and stability in time are limited by our knowledge of the Earth dynamics. These drawbacks could be avoided by giving to the constellation of satellites the possibility of constituting by itself a primary and autonomous positioning system, without any a priori realization of a terrestrial reference frame. Our work shows that it is possible to construct such a system, an Autonomous Basis of Coordinates, via emission coordinates. Here we present the idea of the Autonomous Basis of Coordinates and its implementation in the perturbed space-time of Earth, where the motion of satellites, light propagation, and gravitational perturbations are treated in the formalism of general relativity

Risk Factors and Predictive Value of Depression and Anxiety in Cervical Cancer Patients

Background and Objectives: Women with cervical cancer may experience depression or anxiety, influencing their quality of life and even their adherence to cancer treatments. This study aimed to explore and measure the levels of anxiety and depression in patients suffering from cervical cancer and to identify the possible predictors among known risk factors such as age, cancer stage, smoking status, number of partners, use of contraceptives, and annual gynecological visits. Materials and Methods: In total, 59 patients with cervical cancer were included. A consecutive sampling method was used to select participants in this research. Depression and anxiety were assessed using the Zung Anxiety Scale (SAS) and Zung Depression Scale (SDS). The subjects were divided into three groups, according to the stage of cancer. Results: Scores of depression and anxiety were increased in all recruited cervical cancer patients. A significant correlation was found between disease stage and the scores of depression (p = 0.002) and anxiety (p = 0.016). More severe depressive symptoms correlated to a more advanced stage of the disease. A multiple linear regression showed that disease stage and annual visits to the gynecologist are the risk factors associated with higher depression scores. Conclusions: Patients diagnosed with cervical cancer are a vulnerable group for the development of the psychiatric disorders and they require screening programs, which could potentially detect candidates for co-psychiatric and/or psychotherapeutic treatment. They demand particular attention because anxiety and depression are associated with the significant burden of the underlying disease and unfavorable survival rates