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#selfdrivingcars_2022-06-01_05-29-21.xlsx

#artificialintelligence

The graph represents a network of 1,612 Twitter users whose tweets in the requested range contained "#selfdrivingcars", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 01 June 2022 at 12:38 UTC. The requested start date was Wednesday, 01 June 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 19-day, 11-hour, 44-minute period from Thursday, 12 May 2022 at 09:04 UTC to Tuesday, 31 May 2022 at 20:48 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


#selfdrivingcars_2022-04-20_05-36-02.xlsx

#artificialintelligence

The graph represents a network of 1,840 Twitter users whose tweets in the requested range contained "#selfdrivingcars", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 20 April 2022 at 12:47 UTC. The requested start date was Wednesday, 20 April 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 25-day, 6-hour, 8-minute period from Friday, 25 March 2022 at 15:16 UTC to Tuesday, 19 April 2022 at 21:24 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


The Self-Driving Car: Crossroads at the Bleeding Edge of Artificial Intelligence and Law

arXiv.org Artificial Intelligence

Artificial intelligence (AI) features are increasingly being embedded in cars and are central to the operation of self-driving cars (SDC). There is little or no effort expended towards understanding and assessing the broad legal and regulatory impact of the decisions made by AI in cars. A comprehensive literature review was conducted to determine the perceived barriers, benefits and facilitating factors of SDC in order to help us understand the suitability and limitations of existing and proposed law and regulation. (1) existing and proposed laws are largely based on claimed benefits of SDV that are still mostly speculative and untested; (2) while publicly presented as issues of assigning blame and identifying who pays where the SDC is involved in an accident, the barriers broadly intersect with almost every area of society, laws and regulations; and (3) new law and regulation are most frequently identified as the primary factor for enabling SDC. Research on assessing the impact of AI in SDC needs to be broadened beyond negligence and liability to encompass barriers, benefits and facilitating factors identified in this paper. Results of this paper are significant in that they point to the need for deeper comprehension of the broad impact of all existing law and regulations on the introduction of SDC technology, with a focus on identifying only those areas truly requiring ongoing legislative attention.


A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method

arXiv.org Artificial Intelligence

In this thesis a probabilistic framework is developed and proposed for Dynamic Object Recognition in 3D Environments. A software package is developed using C++ and Python in ROS that performs the detection and tracking task. Furthermore, a novel Gaussian Process Regression (GPR) based method is developed to detect ground points in different urban scenarios of regular, sloped and rough. The ground surface behavior is assumed to only demonstrate local input-dependent smoothness. kernel's length-scales are obtained. Bayesian inference is implemented sing \textit{Maximum a Posteriori} criterion. The log-marginal likelihood function is assumed to be a multi-task objective function, to represent a whole-frame unbiased view of the ground at each frame because adjacent segments may not have similar ground structure in an uneven scene while having shared hyper-parameter values. Simulation results shows the effectiveness of the proposed method in uneven and rough scenes which outperforms similar Gaussian process based ground segmentation methods.


Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


Autonomous delivery picking up in US

#artificialintelligence

Autonomous vehicles (AV) play an increasingly important role in food and parcel deliveries. In early December, Silicon Valley-based startup Nuro announced that it was launching the first commercial autonomous delivery in California. Partnering with 7-Eleven, the company provides the service for residents of Mountain View, where the business is located. According to a blog post from Nuro's co-founder Zhu Jiajun, customers can access the autonomous delivery through 7-Eleven's 7NOW delivery app. Nuro currently offers the service with its Prius vehicles in fully autonomous mode, expecting to replace them with its R2 autonomous cars later.


Artificial Intellgence -- Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021

arXiv.org Artificial Intelligence

The TriRhenaTech alliance presents the accepted papers of the 'Upper-Rhine Artificial Intelligence Symposium' held on October 27th 2021 in Kaiserslautern, Germany. Topics of the conference are applications of Artificial Intellgence in life sciences, intelligent systems, industry 4.0, mobility and others. The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes \'ecoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.


Apple accelerates work on car as it aims for fully autonomous vehicle

The Japan Times

Apple Inc. is pushing to accelerate development of its electric car and is refocusing the project around full self-driving capabilities, according to people familiar with the matter, aiming to solve a technical challenge that has bedeviled the auto industry. For the past several years, Apple's car team had explored two simultaneous paths: creating a model with limited self-driving capabilities focused on steering and acceleration -- similar to most current cars from Tesla Inc. -- or a version with full self-driving ability that doesn't require human intervention. Under the effort's new leader -- Apple Watch software executive Kevin Lynch -- engineers are now concentrating on the second option. Lynch is pushing for a car with a full self-driving system in the first version, said the people, who asked not to be identified because the deliberations are private. It's just the latest shift for the car effort, known as the Special Projects Group or "Project Titan," which has endured strategy changes and executive turnover since starting around 2014.


Apple accelerates work on car, aims for fully autonomous vehicle

Al Jazeera

Apple Inc. is pushing to accelerate development of its electric car and is refocusing the project around full self-driving capabilities, according to people familiar with the matter, aiming to solve a technical challenge that has bedeviled the auto industry. For the past several years, Apple's car team had explored two simultaneous paths: creating a model with limited self-driving capabilities focused on steering and acceleration -- similar to most current cars from Tesla Inc. -- or a version with full self-driving ability that doesn't require human intervention. Under the effort's new leader -- Apple Watch software executive Kevin Lynch -- engineers are now concentrating on the second option. Lynch is pushing for a car with a full self-driving system in the first version, said the people, who asked not to be identified because the deliberations are private. It's just the latest shift for the car effort, known as the Special Projects Group or "Project Titan," which has endured strategy changes and executive turnover since starting around 2014.


Autonomous Vehicles: When Will We Get There? – Scitech Patent Art

#artificialintelligence

At least one headline, either in newspapers or news channels, is often packed with stories of self-driving vehicles. Driverless cars, as most of us know, have also sparked Hollywood's imagination for the last few decades! The first autonomous cars appeared in the 1980s, with Carnegie Mellon University's Navlab and ALV projects in 1984, and Mercedes-Benz and Bundeswehr University Munich's Eureka Prometheus Project in 1987.Since then, however, limited research had been observed until 2005. SO WHAT'S NEW? It's surprising to know that, the concept of autonomous vehicles is not entirely new, if we drive down history lane a bit. As early as 1925, Houdina Radio Control demonstrated a radiocontrolled driverless car, the "Linrrican Wonder" on New York City streets, traveling up Broadway and down Fifth Avenue through the thick of the traffic.