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) …
Microsoft has developed an artificial intelligence-based technology that's capable of answering questions just like humans. The Redmond giant has also revealed that it is planning to expand the technology, so that it would be skilled enough to handle follow-up questions as well. In a recent blog post, Microsoft talked about a new technology it has created that is utilizing AI to read documents and respond to queries about such documents the way humans would. The tech company is crediting a research team at Microsoft Research Asia for developing such advanced AI. So just how human-like is Microsoft's new AI?
Amazon wants to put a camera and microphone in your bedroom with the UK launch of its latest Echo home device. The camera on the £119.99 ($129) Echo Spot, which doubles up as a'smart alarm', will probably be facing directly at the user's bed. The device, which is already available in the US has such sophisticated microphones it can hear people talking from across the room - even if music is playing. However, there remain privacy concerns over using such a device in the home. Amazon devices have previously activated when they're not wanted meaning this small device could turn into a potential spy.
As computer scientists attempt to make machines think and learn like humans, the middle ground is being taken up by researchers attempting to use AI to read our minds. In the latest breakthrough, scientists at Kyoto University, Japan, have studied deep neural networks (AI) and discovered that computers wield the capacity to at least visualise what humans are thinking. Before we get ahead of ourselves, it's worth noting that the technology is nascent, and applies in only optimal conditions. If you recoil at someone's dubious new choice of profile picture on Facebook, your laptop isn't going to start registering your distaste and broadcasting it to the world. That being said, the new technology certainly has seemingly impressive – if ominous – potential applications.
Inundated with more data than humans can analyze, the U.S. military and intelligence community are banking on machine learning and advanced computing technologies to separate the wheat from the chaff. The Defense Department operates more than 11,000 drones that collect hundreds of thousands of hours of video footage every year. "When it comes to intelligence, surveillance and reconnaissance, or ISR, we have more platforms and sensors than at any time in Department of Defense history," said Air Force Lt. Gen. John N.T. "Jack" Shanahan, director for defense intelligence (warfighter support) in the office of the undersecretary of defense for intelligence. "It's an avalanche of data that we are not capable of fully exploiting," he said at a technology conference in Washington, D.C., hosted by Nvidia, a Santa Clara, California-based artificial intelligence computing company. For example, the Pentagon has deployed a wide-area motion imagery sensor that can look at an entire city.
Why Big Data is important • Data contains information. "Field of study that gives computers the ability to learn without being explicitly programmed." Starting with a different attribute • Seems like a much better starting point than address • Each node almost completely uniform • Almost completely predicts whether we will be paid back yes no a, -c, i, e, o, u: Y -a, c, -i, e, -o, -u: N a, -c, i, -e, -o, -u: Y -a, -c, i, e, -o, -u: Y -a, c, i, -e, -o, -u: N -a, -c, i, -e, -o, u: Y a, -c, -i, -e, o, -u: N a, c, i, -e, o, -u: N criminal? Support Vector Machine • Binary classification algorithm • SVM generates a (N -- 1) dimensional hyperlane to separate those points into 2 groups. Singular Value Decomposition • PCA is actually a simple application of SVD 25.
In the 2006 film, The Devil Wears Prada, actor Meryl Streep who plays Miranda Priestly, a powerful fashion editor, gives her new assistant a dressing down for not understanding fashion. She tells her that fashion is whatever a select group of designers say it is. But what she fails to anticipate is how these czars of style will one day be challenged on their own turf by another set of fashionistas: machines. As artificial intelligence (AI) pervades almost every field today, lines of an algorithm are now sashaying down the catwalk. India's fashion and retail industry too have started to rely on the power of machines to come up with the latest styles.
Sören Schwertfeger finished his postdoctorate research on autonomous robots in Germany, and seemed set to go to Europe or the United States, where artificial intelligence was pioneered and established. China, which for years watched enviously as the West invented the software and the chips powering today's digital age, has become a major player in artificial intelligence, what some think may be the most important technology of the future. Experts widely believe China is only a step behind the United States. Beijing is backing its artificial intelligence push with vast sums of money.
When the safety and security of an entire nation is at stake, the Central Intelligence Agency (CIA) of the US needs to be "ahead of the curve", said Teresa Smetzer, Director of Digital Futures. It needs to go beyond just reporting on events to actually anticipating the next crisis. The agency's anticipatory intelligence cell uses machine learning and data science to draw insights from events that had happened in the past, and "report to our policymakers any issues of instability that they might have to deal with". "Rather than responding, they are proactively able to understand what they can do to change the situation," Smetzer said at the recent AWS re:Invent conference in Las Vegas, Nevada. Data is the "lifeblood" of many organisations, whether public and private, said Smetzer.
Mon 30 Jan 2017 04.53 EST Last modified on Tue 19 Sep 2017 06.16 EDT In many respects, 2016 was the year of artificial intelligence (AI). Innovations such as big data, advances in machine learning and computing power, and algorithms capable of hearing and seeing with beyond-human accuracy have brought the benefits of AI to bear on our daily lives. By working together with machines, people can now accomplish more by doing less. Yet the power of AI can address far bigger challenges than helping organise our calendars, order our groceries or play games. In collaboration with AI, people can help to solve some of the world's most urgent and difficult problems.
As mankind expands outwards into the universe, unmanned spacecraft will face a growing problem: as Earth becomes more distant, the transmission time for information and instructions to reach these craft becomes longer and longer. This time lag could make it difficult or even impossible for satellites to respond to fast-moving threats, like space debris, or quickly take opportunities to collect data from unexpected sources, like a passing meteorite. A new grant from NASA to the University of Akron in Ohio will fund research to overcome this issue by helping such spacecraft "think" for themselves using deep-learning artificial intelligence (AI) that works over an Ethereum blockchain network. "I hope to develop technology that can recognize environmental threats and avoid them, as well as complete a number of tasks automatically," Akron Assistant Professor Jin Wei Kocsis, who will lead the research, said in a press release. "I am honored that NASA recognized my work, and I am excited to continue challenging technology's ability to think and do on its own."