Each week on a Wednesday Nikolas Badminton, Futurist highlights the top stories from the past week relating to the incredible rise of artificial intelligence and its application in society, the workplace, in cities, and in our lives.In Artificial Intelligence Bulletin \u2013 Apple Just Hired an AI Heavyweight\u00a0\u00a0we see\u00a0Apple hiring\u00a0Ruslan Salakhutdinov, more Google developments, more future of work opinion, and Josh.ai is growing up.Apple Just Hired This Artificial Intelligence ExpertA Carnegie Mellon University professor will lead Apple\u2019s A.I. research team.Apple continues to bulk up on artificial intelligence and data crunching smarts.Ruslan Salakhutdinov, an associate professor at Carnegie Mellon University and its computer science school\u2019s machine learning department, said Monday via Twitter that he is joining Apple as its director of A.I. research. He will continue to work at Carnegie Mellon while at Apple.Read more at FORTUNEDifferential neural computer from DeepMind and more advances in backward propagationIn a\u00a0recent study in Nature, we introduce a form of memory-augmented neural network called a differentiable neural computer, and show that it can learn to use its memory to answer questions about complex, structured data, including artificially generated stories, family trees, and even a map of the London Underground. We also show that it can solve a block puzzle game using reinforcement learning.READ MORE ON DEEPMINDRef: Hybrid computing using a neural network with dynamic external memory. Nature(12 October 2016) | DOI: 10.1038\/nature20101…andResearchers have developed a neuro-inspired analog computer that has the ability to train itself to become better at whatever tasks it performs. Experimental tests have shown that the new system, which is based on the artificial intelligence algorithm known as “reservoir computing,” not only performs better at solving difficult computing tasks than experimental reservoir computers that do not use the new algorithm, but it can also tackle tasks that are so challenging that they are considered beyond the reach of traditional reservoir computing.READ MORE ON PHYS.ORGRef: Embodiment of Learning in Electro-Optical Signal Processors. Physical Review Letters (16 September 2016) | DOI: 10.1103\/PhysRevLett.117.128301Read more at Futuristech.info Read more at Science AlertHow Artificial Intelligence Is Redefining The Future Of WorkIn a world where the term \u201cbig data\u201d is being thrown around like the next coming, many business leaders still struggle to understand how\u00a0more information is going to help them make better decisions that drive their businesses forward.But the real challenge goes well beyond merely accessing more data. The key is accessing data in the right way, at the right time, and in the right format to generate beneficial insights.This process is no small feat. It requires both technology and human analysis in order to identify these critical insights for business leaders. This process has historically meant a team of highly specialized data analysts spending hours upon hours sifting through terabytes (or more!) of information to make it digestible and useful.But that\u2019s all about to change in a big way.Read more at ForbesJosh.ai \u2013 Whole Home Voice ControlExplore Josh.ai, a voice control home automation platform. This Los Angeles home has RadioRA2, Sonos, Nest, and more. Voice control using a smartphone, tablet, or far-field microphone such as the Echo. Intuitively control lights, music, shades, garage doors, thermostats, locks, sprinklers, fireplaces, etc.