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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.


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.


On the Opportunities and Risks of Foundation Models

arXiv.org Artificial Intelligence

AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e.g., model architectures, training procedures, data, systems, security, evaluation, theory) to their applications (e.g., law, healthcare, education) and societal impact (e.g., inequity, misuse, economic and environmental impact, legal and ethical considerations). Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization. Homogenization provides powerful leverage but demands caution, as the defects of the foundation model are inherited by all the adapted models downstream. Despite the impending widespread deployment of foundation models, we currently lack a clear understanding of how they work, when they fail, and what they are even capable of due to their emergent properties. To tackle these questions, we believe much of the critical research on foundation models will require deep interdisciplinary collaboration commensurate with their fundamentally sociotechnical nature.


Knowing John McCarthy: The Father Of Artificial Intelligence - AI Summary

#artificialintelligence

As per report of, "Recent results from a large survey of machine learning researchers predict AI will outperform humans in many activities in the next ten years, such as translating languages (by 2024) all the way to working as a surgeon (by 2053). Researchers also believe there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years." Nearly every aspect of our lives is being affected by artificial intelligence machines in order to boost profitability and enhance our human capabilities. After playing a significant role in defining the area devoted to the creation of intelligent machines, John McCarthy, an American computer scientist pioneer and inventor, was called the "Father of Artificial Intelligence." In his 1955 proposal for the 1956 Dartmouth Conference, the first artificial intelligence conference, the cognitive scientist coined the term.


Eight Lincoln Laboratory technologies named 2020 R&D 100 Award winners

#artificialintelligence

Eight technologies developed by MIT Lincoln Laboratory researchers, either wholly or in collaboration with researchers from other organizations, were among the winners of the 2020 R&D 100 Awards. Annually since 1963, these international R&D awards recognize 100 technologies that a panel of expert judges selects as the most revolutionary of the past year. Six of the laboratory's winning technologies are software systems, a number of which take advantage of artificial intelligence techniques. The software technologies are solutions to difficulties inherent in analyzing large volumes of data and to problems in maintaining cybersecurity. Another technology is a process designed to assure secure fabrication of integrated circuits, and the eighth winner is an optical communications technology that may enable future space missions to transmit error-free data to Earth at significantly higher rates than currently possible.


Python vs R for Artificial Intelligence, Machine Learning, and Data Science -- InnoArchiTech

#artificialintelligence

Given that, I've written this series to help give guidance to those wanting to start learning more about data science, machine learning, and/or artificial intelligence, and need help choosing a language. This series is also intended for practitioners that wonder which language and packages work best in certain scenarios. Although we'll cover most considerations in this series, including fundamental computer science concepts, the short answer is that you should learn Python and R, and should definitely learn SQL too. If you're really feeling ambitious, give Java, C, and Scala a shot as well. While not specific to data science, the TIOBE Index is a great, up-to-date way to assess the popularity and relevance of different programming languages. When I say'learn', I mean learn fundamental programming concepts and control flow structures, which are applicable to any computer programming language.


Android of the Auto Industry? How Baidu May Race Ahead Of Google, Tesla, And Others In Autonomous Vehicles

#artificialintelligence

As Baidu accelerates its capabilities in self-driving vehicle technology, we dive into the Chinese tech giant's uniquely collaborative approach. Baidu has become the "dark horse" in the autonomous vehicle arms race. In an effort to play catch up to frontrunners in the US and gain an edge on emerging players in China, Baidu has taken a novel approach to developing self-driving software. From autonomy to telematics to ride sharing, the auto industry has never been at more risk. Get the free 67-page report PDF. The company's Apollo project, which it launched in April 2017, is an open source software platform that's designed to encourage collaboration across the auto industry to accelerate the development of self-driving cars.


Elon Musk: $35,000 Tesla Model 3 arrives but job cuts coming as sales shift online

ZDNet

Tesla's long-awaited $35,000 Model 3 electric car is finally available to buy, just under three years after hundreds of thousands of people started placing deposits for pre-order vehicles. The standard Model 3 has a range of 220 miles and its single electric motor is capable of 0-60mph in 5.6 seconds with a top speed of 130mph. The standard interior includes heated cloth seats, manual seat and steering adjustment, basic audio, standard maps and navigation, and a center console with storage and four USB ports. Tesla has also announced a Standard Range Plus model, which has a 240-mile range with a top speed of 140mph and can do 0-60mph in 5.3 seconds. Along with the Model 3 announcement, Tesla said it will also close most of its showrooms around the world and shift sales to online only.


hckr news - Hacker News sorted by time

#artificialintelligence

Google Cloud Platform is down (cloud.google.com) Credit card thieves using free-to-play apps to launder their ill-gotten gains (kromtech.com) How SSH port became 22 (www.ssh.com) Federal Reserve chair says decline in workers' share of profits'very troubling' (www.latimes.com) Trump's sycophants sink to new lows after (back.ly) U.S. To Make More Drugs Easily Available, Cutting Role Docs Play (www.bloombergquint.com) Iron Ox is hiring a Project Manager to help build the robotic farm (jobs.lever.co) Facebook's algorithm change leads to plummeting traffic and layoffs (thelogic.co)


Linux is under your hood

ZDNet

Elon Musk's new tractor trailer can handle most US shipping routes on a single charge. Way back in 2004, Jonathan Schwartz, then Sun's chief operating officer, suggested that cars could become software platforms the same way feature phones were. But, it's Linux, not Java, which is making the most of "smart cars". That's because Linux and open-source software are flexible enough to bring a complete software stack to any hardware, be it supercomputer, smartphone, or a car. There are other contenders, such as Blackberry's QNX and Microsoft IoT Connected Vehicles, but both have lost ground to Linux.