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BETTER THAN HUMAN. "Recently, some impressive feats have been achieved with deep neural networks, including object classification that exceeds human performance, and of course the much-discussed victory of the computer program AlphaGo over human Go champion Lee Sedol. Some amazing projects such as the neural artistic style transfer and and deep networks that learn to synthesize new images have also surfaced." https://pointersgonewild.com/ View in LinkedIn

QUEST FOR AI. "These successes lead to great optimism, and the belief that computers would be able to effectively handle human language, machine translation and vehicle driving before 1980. It was found, as philosophers had predicted, that you could hardly build a machine capable of reasoning about the real world through purely symbolic means. The problem was one of grounding. Symbols in a vacuum don’t mean anything." https://pointersgonewild.com/ View in LinkedIn

SCHOOLED FRAUD. "Professor Roland Arkin from the School of interactive computing at the University of Georgia presented the results of an experiment in which scientists were able to teach a group of robots to cheat and deceive. The strategy for such fraudulent behavior was based on the behavior of birds and squirrels." https://lnkd.in/d9TbGeJ View in LinkedIn

"NEURAL NETWORKS have made great strides in allowing us to build computer programs that can process images, speech, text, and even draw pictures." https://lnkd.in/dQpQxhq View in LinkedIn

GÖDEL MACHINE. "We believe that among the most promising approaches for learning to memorize are our recurrent neural networks, policy gradients, and the Optimal Ordered Problem Solver. An ambitious long-term goal is to implement a full-fledged Gödel machine for a real learning robot." https://lnkd.in/d8GTmxc View in LinkedIn

INDIVIDUALIZED LEARNING. "Robot learning in realistic environments requires novel algorithms for learning to identify important events in the stream of sensory inputs, and to temporarily memorize them in adaptive, dynamic, internal states until the memories can help to compute proper control actions." https://lnkd.in/d8GTmxc View in LinkedIn

DIFFERENT LEARNING STYLES. "Some hardwired, pre-programmed robots such as BU Munich's fast robot car (1994) and TU Munich's humanoid walking biped perform impressive tasks. But they do not learn like humans do. Unfortunately, traditional reinforcement learning algorithms are limited to simple reactive behavior and do not work well for realistic robots." https://lnkd.in/d8GTmxc View in LinkedIn

WORKER BOTS. "The scientists at UC Berkeley hope to move closer to a world where robots are autonomous, nimbly performing many functions typically done by humans. In the future, robots may be able to provide care for the elderly, conduct rescue efforts, clean up in disaster areas and even deliver mail." (2015!) http://www.cnbc.com/2015/12/04/a-baby-step-on-way-to-robots-learning-every-human-thing.html View in LinkedIn

UNFAIR ADVANTAGE. "Japanese researchers introduced a robot that can play rocks-paper-scissors against humans and wins 100 percent of the time. And this robot wins by watching. Its perfect track record is the result of a built-in high-speed camera and extremely fast reflexes that allow it to read microscopic physical cues—wrist angle, finger movement, head tilt—and (essentially) cheat its way to victory." https://lnkd.in/dZT3Xg7 View in LinkedIn

NAUTILUS ”is another self-learning supercomputer. This unit was fed millions of newspaper articles starting from 1945, by basing its search on two criteria: the nature of the publication and location. Using this wealth of information about past events, the computer was asked to come up with suggestions on what would happen in the “future.” And these turned out to be surprisingly accurate guesses. How accurate? Well, for example, it had located Bin Laden." http://www.learning-mind.com/five-creepiest-advances-in-artificial-intelligence/ View in LinkedIn