Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. 'Gamification'--the application of game elements in a non-game context--is an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit3, EteRNA and EyeWire have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics.

The debate over how robots could affect employment has been going on for more than a century. Those who rage against the machine say robots will steal our jobs, make us their slaves, and then kill us. Others believe robots are the key to ultimate freedom from work that humans find dull or dangerous. Some robots could climb stairs, others could pick up and place objects, while others could drive you around the sidewalk without you exerting any effort. The majority of executives at the conference explained how robots are here to rescue us from manual labor and will help to make our companies leaner, more profitable, more consistent, and more competitive.

Many companies including Google, GoDaddy, Yahoo!, and LinkedIn use what's known as HITL, or Human-In-The-Loop, to improve the accuracy of everything from maps, matching business listings, ranking top search results and referring relevant job postings. Why are we still at this point? Because many times humans are better at labeling content than machines. However, when we combine human knowledge with machine learning, we can create truly robust data flows. With that being said, what's the best way to go about it?

Deep learning has been fantastically successful in recent years, and is responsible for better-than-human performance in image classification, face recognition and playing Go. Not everyone thinks that deep learning is the bee's knees -- because the conclusions it reaches can't be explained easily (they're not'interpretable'), and it tends to require a LOT of data and compute power. Combinations of deep and other learning methods may be far more powerful than one alone. How does machine learning relate to Artificial Intelligence (and Artificial General Intelligence)? AI refers to systems that can act intelligently, even in a very narrow scope.

Real-world artificial-intelligence applications are popping up in unexpected places--and much sooner than you might think. While winning a game of Go might be impressive, machine intelligence is also evolving to the point where it can be used by more people to do more things. That's how four engineers with almost zero knowledge of Japanese were able to create software, in just a few months, that can decipher handwriting in the language. The programmers at Reactive Inc. came up with an application that recognizes scrawled-out Japanese with 98.66 percent accuracy. The 18-month-old startup in Tokyo is part of a growing global community of coders and investors who are harnessing the power of neural networks to put AI to far more practical purposes than answering trivia or winning board games.

Singapore: Cognizant Technology Solutions Corp., a US-based information technology (IT) firm with most of its employees working out of India, expects its business growth in the Asia-Pacific region to outpace the company average this year, maintaining the trend seen in recent years, Jayajyoti Sengupta, president and Asia-Pacific head, said in an interview. Automation, which includes robots, machine learning and artificial intelligence, will be among the new frontiers for Cognizant, as rote and repetitive processes become "digital, instrumented, analyzed and intelligent", he said. Cognizant has said it expects its revenue growth to slow to between 10% and 14.3% for the calendar year 2016. How do you see the situation in the Asia-Pacific? It would be pertinent to note that Cognizant's growth of 21% in calendar 2015 included revenues from the acquisition of TriZetto.

It seemed like a good idea; Microsoft introduced an Artificial Intelligence (AI), Tay, to comment on social media and learn to interact with others. Within hours, Tay had become a genocidal maniac. Microsoft spent hours frantically deleting Tay's racist, misogynistic, Nazi-sympathizing tweets before finally pulling her off-line when she began advocating genocide. Some of the problems stemmed from a function where users could instruct Tay to repeat an offensive tweet verbatim--trolls thought it funny to teach Tay awful ideas. However, by the end, Tay's racist bile was self-generated; she had learned hate.

Deutsch's senior VP and creative technology director, Martin Legowiecki, told Marketing Land, "We are at a point of switching up how we use computers. It used to be we had to talk like computers." With chatbots marketers can use computers to "talk" with consumers, not just the other way around. Of course in creating a chatbot, marketers must craft elaborate decision trees on how the automated communication responds to various interactions. For example, when the TacoBot takes order, if you tell the you happen to be drunk, it automatically adds water to your order -- and humor into the chatbot ordering process.

However even Deep Learning has a very long way to go: 1. Each of the advisers or modules has only learned and trained so much. They are not infallible 2. More complex decisions and problems have many and complex aspects in the decision process and as a team the different layers of advisers or modules can be trained together only so much as the cases they have worked on together. In real life curve balls are the norm and "intelligence" is not merely about dealing with the known. It is most definitely about dealing with the unknown.

Risk Group, an independent and integrated strategic risk research organization, is happy to announce the launch of Risk Roundup, an integrated strategic risk dialogue facing nations: its government, industries, organizations and academia (NGIOA) in cyberspace, geospace and space (CGS). Nations currently stand on the verge of the most transformative period in all of human history. As Information Technology, Genetics, Nanotechnology, Robotics and Artificial Intelligence merge and converge to make the once impossible imagination, possible, it is not only human and machine intelligence that will merge and create unthinkable possibilities: The likes of Molecular manufacturing will bring earth shattering potential to build virtually any physical item quickly and inexpensively directly from pure information. The pace of technological change coming our way will be so rapid, its impact so deep, that human life, its expectations and experiences, will be irreversibly transformed. It will also change the whole global dynamics, security and power structure.