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) …
Dr. Leila Etaati gained her PhD in University of Auckland. She is world well-known speaker in Machine Learning and Analytics topics, and spoke in world's best international conferences in Data Platform topics, such as; PASS Summits, Data Insight Summit, PASS Rally, SQL Nexus, Microsoft Ignite, and so on. She has more than 10 years experience in Data Mining and Analytics. She is also Microsoft Most Valuable Professional (MVP) because of her dedication on Microsoft Analytics and Machine Learning technologies. She writes blog posts in RADACAD and also publishes YouTube videos in our channel.
Intelligence agencies have a limited number of trained human analysts looking for undeclared nuclear facilities, or secret military sites, hidden among terabytes of satellite images. But the same sort of deep learning artificial intelligence that enables Google and Facebook to automatically filter images of human faces and cats could also prove invaluable in the world of spy versus spy. An early example: US researchers have trained deep learning algorithms to identify Chinese surface-to-air missile sites--hundreds of times faster than their human counterparts. The deep learning algorithms proved capable of helping people with no prior imagery analysis experience find surface-to-air missile sites scattered across nearly 90,000 square kilometers of southeastern China. Such AI based on neural networks--layers of artificial neuron capable of filtering and learning from huge amounts of data--matched the overall 90 percent accuracy of expert human imagery analysts in locating the missile sites.
Australian enterprise software firm TechnologyOne has released its financial results for the 2017 financial year, reporting AU$44.5 million in after-tax profit, on revenue of AU$273.2 million. Speaking with ZDNet about the results, founder, former CEO, and now chairman of TechnologyOne Adrian Di Marco said the massive market that is enterprise cloud in Australia is continuing to pick up pace. "The cloud is a new paradigm for customers. The market is actually massive in Australia, there are government departments, which we've seen huge demand from federal government, state departments, local governments, universities -- they all want to go into the cloud and they really all want it delivered how we're offering, software-as-a-service, not as a hosted thing," he said. "The cloud is growing exceptionally fast.
Detecting art forgeries is hard and expensive. Art historians might bring a suspect work into a lab for infrared spectroscopy, radiometric dating, gas chromatography, or a combination of such tests. AI, it turns out, doesn't need all that: it can spot a fake just by looking at the strokes used to compose a piece. In a new paper, researchers from Rutgers University and the Atelier for Restoration & Research of Paintings in the Netherlands document how their system broke down almost 300 line drawings by Picasso, Matisse, Modigliani, and other famous artists into 80,000 individual strokes. Then a deep recurrent neural network (RNN) learned what features in the strokes were important to identify the artist.
It's a Saturday morning in June at the Royal Society in London. Computer scientists, public figures and reporters have gathered to witness or take part in a decades-old challenge. Some of the participants are flesh and blood; others are silicon and binary. Thirty human judges sit down at computer terminals, and begin chatting. To determine whether they're talking to a computer program or a real person.
Artificial Intelligence, or "augmented intelligence" as IBM (IBM) CEO Ginni Rometty prefers to call it, "looks beautiful," but it could be painful if the world is not prepared for it. "A lot of people say, 'So will A.I. replace jobs?' The answer is: it will," Rometty said during an event on Wednesday hosted by the Economic Club of New York. IBM just finished a study in collaboration with MIT that found that 10% of jobs will be replaced, according to Rometty. In an era of man and machine, these jobs will be 100% changed, she added.
Alzheimer's disease is notoriously difficult to diagnose -- the only way doctors can tell for sure that a patient has the deadly neurodegenerative condition is to examine his or her brain during an autopsy after death. That uncertainty is hard on patients who are starting to experience memory loss, which could be an early sign of Alzheimer's or another, more treatable form of dementia. It also poses a major challenge to the researchers who are working to come up with effective treatments for the disease, which afflicts some 5 million Americans. But now artificial intelligence is learning to do what doctors can't. Separate teams of scientists at the University of Bari in Italy and McGill University in Canada have created artificial intelligence algorithms that can look at brain scans of people who are exhibiting memory loss and tell who will go on to develop full-blown Alzheimer's disease and who won't.
Machine Learning (ML) is now a de-facto skill for every quantitative job and almost every industry embraced it, even though fundamentals of the field is not new at all. However, what does it mean to teach to a machine? Unfortunately, for even moderate technical people coming from different backgrounds, answer to this question is not apparent in the first instance. This sounds like a conceptual and jargon issue, but it lies in the very success of supervised learning algorithms. What is a machine in machine learning First of all here, machine does not mean a machine in conventional sense, but computational modules or set of instructions.
Dementia is caused by damage in the brain and treatment becomes difficult as it progresses. The new system to be created by Shimane University and Erisa Co. is aimed at detecting early signs of "mild cognitive impairment" with high accuracy, as people with this condition often develop dementia later. Under the system, the AI element will learn a number of MRI images showing brain blood flow to identify what changes are characteristic of mild cognitive impairment and early signs of the disease. Studies have already shown that blood flow in a certain area of the brain changes before the brain starts shrinking. Mild cognitive impairment causes a slight but noticeable decline in cognitive abilities, including memory.
Cher Horowitz's closet from the film "Clueless" had a futuristic computer system that helped her put together outfits. Back in 1995, the concept teased what it might be like to get dressed in the future. Technology has evolved a lot since then, but closets have been largely untouched by innovation. Now, that's starting to change. "If algorithms do their job well, people will spend less time thinking about what to wear," said Ranjitha Kumar, an assistant professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign.