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.

The environmental costs of moving data around the world or building a better smartphone often go unappreciated. Both tasks take a great deal of energy and other resources, though the effects are often felt hundreds or thousands of miles from most end users. The world's biggest technology firms are increasingly focused on finding ways to go green. Facebook announced in January that it is building a new data center in Ireland powered entirely by renewable energy. In March, Apple introduced a recycling robot named "Liam" that can surgically disassemble old iPhones so their parts can be reused.

The IDLF project can be used by application developers, cloud service providers, academic researchers, or anyone seeking the best performance on the full spectrum of Intel platforms for Deep Learning. Support for additional hardware platforms can be added over time in a completely API-agnostic manner allowing for maximum code reuse. This is an active open source project distributed under the BSD 3-clause open source license. Intel is the leading contributor to IDLF, enabling application and system developers to make the most of Intel Xeon and Xeon Phi processors as well as Intel Iris Pro graphics.

Technology has transformed how customers and brands interact with each other. Shoppers once relied on face-to-face, in-store interactions to make purchases and receive support. Now, shoppers do their research before entering a store (81 percent of shoppers conduct online research before buying) and seldom rely on salespeople to help them make decisions. Retailers, for their part, have realized that by embracing technology, they can extend their storefronts to their customers' fingertips. The Internet, buy buttons, mobile payment apps such as Square and Venmo, and couponing and price-matching apps like SnipSnap have changed how we shop.

Making sense of the mountains of data collected on a daily basis requires specialized data science skills that are hard to come by, and hard to keep. Augmented or even eliminated some of these specialized tasks with machine learning. Making sense of the mountains of data collected on a daily basis requires specialized data science skills that are hard to come by, and hard to keep. But what if some of these specialized tasks could be augmented or even eliminated by machine learning? DataRobot customers are enjoying these game changing benefits and more, right now.