With a paralyzing spinal cord injury, the biological wiring that hooks up our controlling brains to our useful limbs gets snipped, leading to permanent loss of sensation and control and usually a lifetime of extra health care. Researchers have spent years working to repair those lost connections, allowing paralyzed patients to sip coffee and enjoy a beer with robotic limbs controlled by just their minds. Now, researchers have gone a step further, allowing a paralyzed person to control his own hand with just his mind. In a study published Wednesday in Nature, researchers report using a "neural bypass" that reconnects a patient's mental commands for movement to responsive muscles in his limbs, creating somewhat of a synthetic nervous system. The pioneering patient, Ian Burkhart, a 24-year-old man left with quadriplegia after a diving accident almost six years ago, can once again move his hand.

More than 70 years ago, Isaac Asimov dreamed up his three laws of robotics, which insisted, above all, that "a robot may not injure a human being or, through inaction, allow a human being to come to harm". Now, after Stephen Hawking warned that "the development of full artificial intelligence could spell the end of the human race", two academics have come up with a way of teaching ethics to computers: telling them stories. Mark Riedl and Brent Harrison from the School of Interactive Computing at the Georgia Institute of Technology have just unveiled Quixote, a prototype system that is able to learn social conventions from simple stories. Or, as they put in their paper Using Stories to Teach Human Values to Artificial Agents, revealed at the AAAI-16 Conference in Phoenix, Arizona this week, the stories are used "to generate a value-aligned reward signal for reinforcement learning agents that prevents psychotic-appearing behaviour". A simple version of a story could be about going to get prescription medicine from a chemist, laying out what a human would typically do and encounter in this situation.

Are you skeptical about machines' ability to effectively aid social science decision making? Machines are becoming ever more intelligent, increasingly able to help humans make decisions across the social science spectrum, but cognitive computing is still in its infancy, with much unexplored ground ahead. Accordingly, government leaders who harness the power of cognitive computing are helping usher in a renaissance of simplified operations and enhanced constituent engagement. The secret to effectively using cognitive computing to aid human decision making lies in teaching computers to ask the right questions while taking account context and staying focused on what computers do well. Computers operate at great speed.

Now it's time for us to see how deep learning really works! In case you missed the previous part and is now wondering how deep learning has anything to do with you, go check it out! In this part, we'll show you all the basic concepts you need to get started with deep learning. Machine learning problems are typically where you want a computer to answer some questions without being explicitly programmed. For example, the question can be something like "What's the price of my 1800 sqft apartment in Seattle?", or "Is this news article telling the truth?"

Amzi! 10.x is now an open source release. The very stable 9.x release of the software will remain as a supported commercial version. Amzi! Prolog source code debugger showing call stack, variable bindings, source code at a REDO port, index of predicates, and executing code. Amzi! Prolog Logic Server is an embeddable, extendable, highly portable implementation of ISO standard Prolog, including full support for ISO modules enabling large-scale application development. A rule language and reasoning engine that is embeded in Excel, allowing for the development of rule and pattern-matching applications integrated with Excel spreadsheet data.

Deep learning is a branch of machine learning that has shown incredible results on very difficult tasks like recognizing objects from an image, understanding speech and languages, and of course, playing board games. A bunch of smartest people have been working on it for decades, and it's absolutely state-of-the-art. Since you've clicked into a dummy's guide, chances are that you are a curious dummy. So first of all, let me answer a few questions I know a curious dummy might ask. It's software programs trying to mimic the human brain. The way it forms, the way it learns and the way it responds.

Time to get away from it all, enjoy our families, friends, and free time... and read up on the latest in data science, machine learning, and analytics. For those of us who can't completely disconnect, or are otherwise interested in reading up over the weekend, the following is a roundup of some of the best free recent ebooks and other online reading resources, as well as a classic throwback article worthy of the attention of newcomers to the field of machine learning. As reported earlier this week, the MIT Press Deep Learning book is finished, and the online version has been finalized. Written by deep learning heavyweights Ian Goodfellow, Yoshua Bengio, and Aaron Courville, the book is poised to become the deep learning book on the market. At over 700 pages, and being quite technical in content, this isn't a simple one-weekend read (at least, not for the majority of folks), but getting started this weekend means only a few more needed.

We've seen startling moves in artificial intelligence in 2015. Robots are doing the grunt work in factories. Driverless cars have become a reality. WiFi-enabled Barbie uses speech-recognition to talk (and listen) to children. Companies are using AI to improve their product and increase sales.

Bots seem to be all the rage this week, thanks to the release of Facebook's Messenger Bot program at F8, but not everyone sees bots as the way to keep up with the customer service glut. DigitalGenius, a former TechCrunch Disrupt Battlefield finalist, thinks there's a better way using artificial intelligence and machine learning.

Microsoft is the world's most valuable company, with a 261 billion market cap. And an IBM computer named Deep Blue defeats Garry Kasparov, reigning world chess champion and, at the time, the highest-ranked chess player to have ever lived.