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 next time you call an 800 number with a gripe about a product or service, consider this: Even though it's a real live person who answers, he or she might not be the one deciding how to deal with you. Instead, a complex series of algorithms may step in, to gauge your mood and react accordingly. Then, based on precisely how peeved you sound, the system suggests what the service rep should offer as a fix for whatever your problem is--a refund, for instance, or free shipping on your next order--with the aim of holding on to your business. Wondering why a human CSR can't just handle this conversation? "People interpret tones of voice differently, so they respond differently to customers," explains IBM consultant Aman Kochhar.
If you work at IBM or a company equipped with their artificially intelligent employee retention software, your planned two-week's notice may already be old news. According to a recent panel discussion with IBM's CEO, Ginni Rometty, at a Work Talent and Human Resources Summit in New York, the company's'predictive attrition' software is now 95 percent accurate in determining when an employee is ready to quit. Using their predicative software, Rometty says that IBM has been able to preempt employees on the cusp of quitting, bolstering their retention rates, which has reportedly saved them $300 million. Human resources may need a new name as a host of new software has begun to disrupt jobs and efficiency. Among the many AI-powered tools being developed by IBM for human resources is'predictive attrition.'
How do you fix a satellite's instrument that's floating 22,000 miles above the Earth's surface? That's a question that NASA had to answer when it ran into problems with the Solar Dynamics Observatory (SDO), a satellite tasked with studying the Sun and the effects of solar activity on Earth. This is important for all sorts of reasons -- not least because solar storms can knock out GPS satellites, shut down electrical grids, and scramble communications. Unfortunately, one of the SDO's three instruments, responsible for measuring ultraviolet light, stopped working due to a fault. This data is essential to satellite operators.
When an AI algorithm learns a new skill -- say a video game like StarCraft II -- it can get good enough to topple the best human pros. But that's only true if everyone plays by the rules. Change the parameters of the game, and the AI will find itself totally unable to adapt. AI that excels at the game Pong can't handle even the slightest shift in distance between the two paddles. Now, new IBM research set to be presented at an AI conference in May could change that.
IBM receives more than 8,000 resumes a day, making it No. 1 on job-search site Glassdoor for Gen Z applicants, said IBM CEO Ginni Rometty at CNBC's @ Work Talent HR Summit on Tuesday in New York City. But that's not the only way the technology giant, which employs roughly 350,000 workers, knows who in the workforce is currently searching for a new position. IBM artificial intelligence technology is now 95 percent accurate in predicting workers who are planning to leave their jobs, said Rometty. During Rometty's seven-year tenure as CEO, IBM has been improving its AI work devoted to the retention of its employees. "The best time to get to an employee is before they go," she said.
The smartphone video game Flappy Bird was removed from smartphones in 2014 by its creator, Dong Nguyen, because it was too addictive. Specifically, International Business Machines scientists this week unveiled research into how machines can continually learn tasks, including playing Flappy Bird, improving over time rather than learning one level of play and stopping at that. Known as lifelong learning, or continuous learning, the area has been studied for decades but remains a formidable research challenge. Aside from offering an important new tool for AI, the work is something of a meditation on what it means for learning to take place both forward and backward in time. Flappy Bird was one of their chief tests.
The Animal-AI Olympics, which will begin this June, aims to "benchmark the current level of various AIs against different animal species using a range of established animal cognition tasks." At stake are bragging rights and US $10,000 in prizes. The project, a partnership between the University of Cambridge's Leverhulme Centre for the Future of Intelligence and GoodAI, a research institution based in Prague, is a new way to evaluate the progress of AI systems toward what researchers call artificial general intelligence. Such an assessment is necessary, the organizers say, because recent benchmarks are somewhat deceiving. While AI systems have bested human grandmasters in a host of challenging competitions, including the board game Go and the video game StarCraft, these matchups only proved that the AIs were astoundingly good at those particular games.
In 2014, IBM opened swanky new headquarters for its artificial intelligence division, known as IBM Watson. Inside the glassy tower in lower Manhattan, IBMers can bring prospective clients and visiting journalists into the "immersion room," which resembles a miniature planetarium. There, in the darkened space, visitors sit on swiveling stools while fancy graphics flash around the curved screens covering the walls. It's the closest you can get, IBMers sometimes say, to being inside Watson's electronic brain. One dazzling 2014 demonstration of Watson's brainpower showed off its potential to transform medicine using AI--a goal that IBM CEO Virginia Rometty often calls the company's moon shot. In the demo, Watson took a bizarre collection of patient symptoms and came up with a list of possible diagnoses, each annotated with Watson's confidence level and links to supporting medical literature. Within the comfortable confines of the dome, Watson never failed to impress: Its memory banks held knowledge of every rare disease, and its processors weren't susceptible to the kind of cognitive bias that can throw off doctors. It could crack a tough case in mere seconds. If Watson could bring that instant expertise to hospitals and clinics all around the world, it seemed possible that the AI could reduce diagnosis errors, optimize treatments, and even alleviate doctor shortages--not by replacing doctors but by helping them do their jobs faster and better.
IBM has come up with a way to use quantum computers to improve machine learning algorithms, even though we don't have anything approaching a quantum computer yet. The tech giant developed and tested a quantum algorithm for machine learning with scientists from Oxford University and MIT, showing how quantum computers will be able to map data at a far more sophisticated level than any classical computer. Somewhat ironically, the testing was minimized based on the current hardware capabilities, using only two qubits of quantum computing capacity, which can be simulated on a classical computer.. There are no fully working quantum computers because qubits can't stay in an entangled state for more than a few hundred microseconds, even in carefully controlled laboratory conditions. They break down into decoherence and can no longer be used to perform calculations in parallel, the feature of quantum computing that will give it awesome processing power.
Walking around without being constantly identified by AI could soon be a thing of the past, legal experts have warned. The use of facial recognition software could signal the end of civil liberties if the law doesn't change as quickly as advancements in technology, they say. Software already being trialled around the world could soon be adopted by companies and governments to constantly track you wherever you go. Shop owners are already using facial recognition to track shoplifters and could soon be sharing information across a broad network of databases, potentially globally. Previous research has found that the technology isn't always accurate, mistakenly identifying women and individuals with darker shades of skin as the wrong people.