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GTA 5 has been one of the most successful open-world titles from Rockstar Games. The action-adventure game has received numerous updates in recent months despite the game bbeing released around 8 years ago. And while it still enjoys massive popularity among GTA fans, there have been endless rumours online suggesting that the game developer is focussing its attention on the next Grand Theft Auto game, GTA 6.

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GTA 6 has been a trending topic on Twitterduring the Super Bowl LV event. The event is already in the past, however, there have been speculations that a newGTA 6 commercial will be aired during the show. It is unclear at the moment as to what kick-started the GTA 6 trend on the social networking platform because there were clearly no signs of a GTA 6 teaser.

The trend started to pickup especially during thehalftime show featuringThe Weeknd. Many fans also believed that his soundtrack could have something to do with a GTA 6 reveal.

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There have been a number of reports online suggesting thatGTA 6 will be arriving on the next-generation PlayStation 5 and Xbox Series X / Series S consoles, instead of the current-gen PlayStation 4 and Xbox One. Speaking of its release, a few rumours speculated that the game could release sometime next year, while others stated that it is expected to drop in 2023. A former Rockstar Games insider namedYan2295 had also released astatement on Twitter recently claiming thatGTA 6 is under development, but it won't becoming anytime soon.

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While these claims clearly give fans hope that the gamecould be in the making, the game publisher is yet toopen up about its plan for a GTA 5 successor. One should also note that Rockstar hasn't even confirmed that the game is underdevelopment. However, the fact that GTA 6constantly manages to be one of the top trending topics on Twitter only shows that the game has a huge demand from the fans.

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GTA 6 trends on social media during Super Bowl: Is there a new GTA 6 teaser? - Republic TV

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. In simpler terms, it is making computers think like humans. The term is used to describe machines that mimic cognitive functions such as learning and problem solving.

While the term was coined in 1956, AI has since advanced by leaps and bounds thanks to advanced algorithms, increased data volumes, and improvements in computing power and technology. In the 1950s, early AI research delved into topics such as problem solving and symbolic methods. Ten years later, the US Department of Defense expressed interest and began to train computers to mimic basic human reasoning. By 2003, intelligent personal assistants were produced long before Siri or Alexa were introduced.

Popular examples of artificial intelligence include AI autopilots on commercial flights, spam filters, mobile check deposits, and voice-to-text features on mobile devices.

To understand how AI works, understanding the sub domains of AI and how these domains can be applied to various industry fields is critical.

AI is being used in every industry, and the demand for AI capabilities only continues to grow.

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AI Definition & Meaning | What is Artificial Intelligence?

Artificial Intelligence in Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, medically-oriented human biology, and health care.

Artificial intelligence in medicine may be characterized as the scientific discipline pertaining to research studies, projects, and applications that aim at supporting decision-based medical tasks through knowledge- and/or data-intensive computer-based solutions that ultimately support and improve the performance of a human care provider.

Artificial Intelligence in Medicine considers for publication manuscripts that have both:

Potential high impact in some medical or healthcare domain; Strong novelty of method and theory related to AI and computer science techniques.

Artificial Intelligence in Medicine papers must refer to real-world medical domains, considered and discussed at the proper depth, from both the technical and the medical points of view. The inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly recommended.

Artificial Intelligence in Medicine is looking for novelty in the methodological and/or theoretical content of submitted papers. Such kind of novelty has to be mainly acknowledged in the area of AI and Computer Science. Methodological papers deal with the proposal of some strategy and related methods to solve some scientific issues in specific domains. They must show, usually through an experimental evaluation, how the proposed methodology can be applied to medicine, medically-oriented human biology, and health care, respectively. They have also to provide a comparison with other proposals, and explicitly discuss elements of novelty. Theoretical papers focus on more fundamental, general and formal topics of AI and must show the novel expected effects of the proposed solution in some medical or healthcare field.

Following the information explosion brought by the diffusion of Internet, social networks, cloud computing, and big-data platforms, Artificial Intelligence in Medicine has broadened its perspective.Particular attention is given to novel research work pertaining to:

If you are considering submitting to Artificial Intelligence in Medicine, make sure that your paper meets the quality requirements mentioned above. English exposition must also be clear and revised with due care. Authors are kindly requested to revise their manuscripts with the help of co-authors that are fluent in English or language editing services before submitting their contribution. Papers written in poor English are likely to be rejected.

The mere application of well-known or already published algorithms and techniques to medical data is not regarded as original research work of interest for Artificial Intelligence in Medicine, but it may be suitable for other venues.

Artificial Intelligence in Medicine features the following kinds of papers:

Special Issues are regularly published and included among regular issues. Artificial Intelligence in Medicine special issuesdeal with current theoretical/methodological research or convincing applications related to AI in medicine. Special Issues are managed by one or more guest editors who are outstanding experts on the selected topic.Special Issues of Artificial Intelligence in Medicine are directly proposed to potential guest editors by the Editor in Chief, also according to suggestions from the editorial board members."External" proposals of Special Issues will no longer be considered.

Artificial Intelligence in Medicine does not publish conference volumes or conference papers. However, selected and high-quality research results presented earlier at conferences may be published in Artificial Intelligence in Medicine, in the form of a thoroughly revised (rephrased) and extended (including new research results) original research paper.

Information for authors and further details about the editorial process can be found in the Guide for Authors section of the Artificial Intelligence in Medicine web page.

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Artificial Intelligence in Medicine | Journal ...

These eight books about artificial intelligence cover a range of topics, including ethical issues, how AI is affecting the job market, and how organizations can use AI to gain a competitive advantage.

Artificial intelligence (AI) is an ever-evolving technology. With several different uses, it's easy to understand why it's being implemented more and more frequently. These titles answer common questions about AI, discuss what current AI technologies businesses are using, how humans can lose control over AI, and more.

T-Minus AI: Humanity's Countdown to Artificial Intelligence and the New Pursuit of Global Power

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In T-Minus AI, author, national expert, and the US Air Force's first Chairperson for Artificial Intelligence Michael Kanaan explains a human-oriented perspective of AI. He offers his view on our history of innovation to illustrate what we should all know about modern computing, AI, and machine learning. Additionally, Kanaan discusses the global implications of AI by illuminating the cultural and national vulnerabilities already present as well as future pressing issues.

The Alignment Problem: Machine Learning and Human Values

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The "alignment problem," according to researchers, occurs when the tech systems that humans attempt to teach don't do what is wanted or expected. Best-selling author Brian Christian discusses the alignment problem's "first-responders," and their plans to solve the problem before it is out of human hands. Using a blend of history and on-the-ground reporting, Christian follows the growth of machine learning in the field and examines our current technology and culture.

Rise of the Robots: Technology and the Threat of a Jobless Future

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With the possibility of AI making jobs like paralegals, journalists, and even computer programmers obsolete, author Martin Ford looks at the future of the job market and how it will continue to transform. Rise of the Robots helps us understand how employment and society will have to adapt to the changing market.

Artificial Intelligence: A Guide for Thinking Humans

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In Artificial Intelligence, author Melanie Mitchell asks urgent questions concerning AI today: How intelligent are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Mitchell also covers the dominant models of modern AI and machine learning, cutting-edge AI programs, and human investors in AI.

AI Ethics (The MIT Press Essential Knowledge series)

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AI Ethics discusses the major ethical issues artificial intelligence raises and addresses several concrete questions. Author Mark Coeckelbergh uses narratives, relevant philosophical discussions, and describes different approaches to machine learning and data science. AI Ethics takes a look at privacy concerns, responsibility and the delegation of decision-making, transparency and bias as it arises at all stages of data science processes, and much more.

The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge)

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In The AI Advantage,Thomas Davenport offers a practical guide to using AI in a business setting. Davenport not only explains what AI technologies are available, but also how companies can use them to gain a competitive advantage.

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity

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In her book, author Amy Webb looks at how the foundations of AI are broken--all the way from the people working on the system to the technology itself. Webb suggests that the big nine corporations (Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM, and Apple), "may be inadvertently building and enabling vast arrays of intelligent systems that don't share our motivations, desires, or hopes for the future of humanity."

Artificial Intelligence: 101 Things You Must Know Today About Our Future

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Artificial Intelligence: 101 Things You Must Know Today About Our Futurecontains many timely topics related to AI, including: Self-driving cars, robots, chatbots, as well as how AI will impact the job market, business processes, and entire industries. As the title suggests, readers can learn the answers to 101 questions about artificial intelligence, and have access to a large number of resources, ideas, and tips.

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AI reading list: 8 interesting books about artificial intelligence to check out - TechRepublic

Innovations centered on the megatrend of artificial intelligence (AI): the finalists for the 2021 KUKA Innovation Award have been selected. Five teams convinced the international jury with their robotics concepts on the topic of AI. A monetary prize of 20,000 euro awaits the winner.

AI is becoming increasingly important for industry and the combination with robotics, in particular, is opening up completely new possibilities and applications.

An international jury of experts evaluated the concepts for the Artificial Intelligence Challenge and selected five finalists. The teams are provided with a KUKA robot free of charge and are being trained and coached by KUKA experts throughout the competition. The five finalist teams now have until the virtual Hannover Messe in April to implement their ideas. They will present their applications to a large specialist audience at the international industrial trade fair before the jury chooses the winner of the renowned competition during the fair.

These are the finalists of the Artificial Intelligence Challenge:

Implicit knowledge instead of complex programming codes: the goal of the team from theBrandenburg University of Technology Cottbus-Senftenbergis intelligent robot programming based on manual manufacturing sequences. The individual process steps are recorded by means of innovative data gloves and reproduced on the industrial robot using an AI-based self-learning system. The operator is freed from the need to formulate explicitly what the task is and how the robot has to perform it. Instead, the implicit knowledge of the operator during the manual manufacturing process is accessed. A corresponding skill sequence is automatically generated with this information, and the robot carries out its task without the need to write a single line of code.

Humans can often easily explore closed spaces with their hands and pick up objects without even looking. The application by the international team of researchers fromthe Indian Institute of Science and the U.S. Massachusetts Institute of Technologyaims to bring such capabilities to robots. The goal is for robots to explore, recognize and pick up objects in vision-denied environments using the sense of touch. To this end, the BlindGrasp team is designing a novel gripper with tactile sensing capabilities that gathers the contact and proximity information. This data, coupled with the force-sensing capabilities of KUKAs lightweight robot LBR iiwa, is used by a machine learning agent to learn motion policies and thus safely explore the environment and pick up objects.

Team Chorrobot

The goal of Chorrobot fromBelgiums Katholieke Universiteit Leuven and Flanders Make@KU Leuvenis to leverage artificial intelligence in order to enhance the productivity of car manufacturers as well as small and medium-sized enterprises by facilitating and expediting the deployment of bimanual robot manipulation tasks. The concept enables users without extensive expertise in robotics to demonstrate some aspects of the task and to intuitively specify other aspects via a graphical user interface. This approach facilitates the commissioning of challenging bimanual tasks including fixtureless assembly operations that involve non-rigid and non-fixed elements as well as bimanual inspection operations in unstructured environments.

Particularly during the COVID-19 pandemic, collaborative robots could help to reduce human-to-human interaction. However, configuring these machines for a set of given tasks still requires a great effort. The team from theA*STAR Institute for Infocomm Research in Singaporeis developing a programming-free approach that leverages the latest developments in AI capabilities. The technology enables more natural and safer human-robot collaboration. This allows the robot to support operators, especially in a high-mix low-volume manufacturing environment. The concept from Team CHRIS is comprised of intuitive object and task teaching, activity understanding as well as multimodal perception (vision, touch and speech) and reasoning.

The COVID-19 pandemic and social distancing are increasing the reliance on remote work. However, the impact of online tools for the construction industry is limited. Team CRC from theChair for Individualized Production / RWTH Aachen University & Robots in Architecture Researchis therefore integrating automation technology into online collaboration. Cloud Remote Control enables users to run robots, monitor processes and adapt tool paths from the comfort of their home or international office. This increases accessibility to worldwide robotic production, adding layers of Industrie 4.0 device communication and artificial intelligence to path planning. In this way, Cloud Remote Control empowers teams to remain safely at a distance while still collaborating closely on automated construction.

KUKA launched the innovation competition in 2014, focusing on different technologies each year. The goal of the award is to promote and expedite the transfer of technology from research to industry. All information about the competition as well as the topics and winners in recent years can be foundhere.

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Artificial Intelligence Challenge: These are the finalists for the 2021 KUKA Innovation Award - MarketScale