If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The findings, published in Scientific Reports, mark the first time scientists have used machine learning tools for rapid quantitative and qualitative cell analysis in basic science. "This new test will allow investigators to measure NETosis in different diseases and to test drugs that may inhibit or promote the process," said senior author Leslie Parise, PhD, professor and chair of the UNC Department of Biochemistry and Biophysics. When foreign invaders such as viruses or bacteria enter our bodies, white blood cells rush in to fight the invaders in various ways. One type of white cell, the neutrophil, expels its DNA into the bloodstream to trap bacteria and viruses and aid in their killing to prevent infections. This neutrophil DNA has a net-like appearance and is called Neutrophil Extracellular Traps, or NETs.
Kim Il Sung University in the spring of 2017 set up specialist Japanese language and literature courses, it was learned Saturday from the university. The training course for Japanese researchers was established at the prestigious institution in the capital, Pyongyang, at a time when North Korea was repeatedly testing nuclear weapons and launching ballistic missiles, which continued until the fall of 2017 and led to heightened tensions with the United States. There is a possibility that it was judged necessary to strengthen the development of such experts in view of future diplomacy with Japan. Japan and North Korea have no diplomatic relations. The Department of Japanese Language and Literature was established in the university's Faculty of Foreign Languages and Literature.
When Arnold Schwarzenegger said "I'll be back" in The Terminator, he probably didn't realize the film would keep coming back in discussions about robots and artificial intelligence. Yet 35 years after Schwarzenegger portrayed a cyborg assassin from an AI-dominated future, much of Western discourse on robots is repeating a Terminator-like scenario: panic that robots will take our jobs, and that AI will take over the world, Skynet-style. Western culture has had a long history of individualism, warlike use of technology, Christian apocalyptic thinking and a strong binary between body and soul. These elements might explain the West's obsession with the technological apocalypse and its opposite: techno-utopianism. In Asia, it's now common to explain China's dramatic rise as a leader in AI and robotics as a consequence of state support from the world's largest economy.
Chomsky has been known to vigorously defend and debate his views and opinions, in philosophy, linguistics, and politics. He has had notable debates with Jean Piaget, Michel Foucault, William F. Buckley, Jr., Christopher Hitchens, George Lakoff, Richard Perle, Hilary Putnam, Willard Quine, and Alan Dershowitz, to name a few. In response to his speaking style being criticized as boring, Chomsky said that "I'm a boring speaker and I like it that way.... I doubt that people are attracted to whatever the persona is.... People are interested in the issues, and they're interested in the issues because they are important."
In this paper, we (1) argue that the international human rights framework provides the most promising set of standards for ensuring that AI systems are ethical in their design, development and deployment, and (2) sketch the basic contours of a comprehensive governance framework, which we call'human rights-centred design, deliberation and oversight', for ensuring that AI can be relied upon to operate in ways that will not violate human rights.
Facial recognition technology has advanced swiftly in the last five years. As University of Texas at Dallas researchers try to determine how computers have gotten as good as people at the task, they are also shedding light on how the human brain sorts information. UT Dallas scientists have analyzed the performance of the latest echelon of facial recognition algorithms, revealing the surprising way these programs -- which are based on machine learning -- work. Their study, published online Nov. 12 in Nature Machine Intelligence, shows that these sophisticated computer programs -- called deep convolutional neural networks (DCNNs) -- figured out how to identify faces differently than the researchers expected. "For the last 30 years, people have presumed that computer-based visual systems get rid of all the image-specific information -- angle, lighting, expression and so on," said Dr. Alice O'Toole, senior author of the study and the Aage and Margareta Møller Professor in the School of Behavioral and Brain Sciences.
We have a trust issue. In our digital world, it has become increasingly difficult to trust each other. Whether it is another person, an organisation or a device, trust is no longer a given online. This is a serious problem for our society and our democracy. If trust is lacking in society, anarchy can be expected.
The University of Tokyo and SoftBank will set up an artificial intelligence (AI) research base to develop bright minds and start-up ambitions for Japan. Called the Beyond AI Institute, it aims to be an organisation that brings together researchers from the University of Tokyo and universities abroad. The bank will spend $184 million over the next ten years for this institute. Specific initiatives include work in quantum physics and the combination of AI and biofunctions. The Tokyo-based institute will also look at areas such as "health and medical," "public works and social infrastructure" and "manufacturing."
Machine learning is an exciting topic about designing machines that can learn from examples. The course covers the necessary theory, principles and algorithms for machine learning. The methods are based on statistics and probability-- which have now become essential to designing systems exhibiting artificial intelligence. Reference textbooks for different parts of the course are "Pattern Recognition and Machine Learning" by Chris Bishop (Springer 2006) and "Probabilistic Graphical Models" by Daphne Koller and Nir Friedman (MIT Press 2009) and "Deep Learning" by Goodfellow, Bengio and Courville (MIT Press 2016).
The Age of Autonomy is upon us. Truly autonomous devices are quickly replacing those that are merely automated. This is a natural evolution of IoT due to autonomy becoming a necessity to handle the volume, velocity and veracity of real-time data being generated. Every device and even some of the things we don't generally regard as devices (e.g. The centralized solution architectures and services in our enterprise data centers today are not viable for the industry use cases that the Age of Autonomy brings so fundamental changes must be made.