Boasting one of the most advanced rail networks in the world, Japan is investigating the use of artificial intelligence and a machine learning technology approach that would attempt to add what promoters call a "train time delay" function intended to provide riders with up-to-date route-planning information. Fujitsu Ltd. (TYO: 6702) said this week it has begun field trials in Japan for a delay time prediction engine developed with partner SRI International of Menlo Park, Calif. The trial also leverages a route-planning app developed by partner Jorudan Co. that claims about 10 million monthly users. The partners said the time delay engine learns from past train delay information. Updates on train delays are delivered as a cloud service.

No need to panic, but automation and artificial intelligence may already be playing a role in reducing IT hiring in India. According to Nasscom, an Indian IT industry association, fresh hiring in the current financial year is expected to decline compared to last year as IT companies face stiff margins, and move more jobs to automation. Campus hiring may fall for the first time since 2009. "Hiring activity in the year before last was 2.20 lakh (new jobs were created in IT sector). Last year there were about two lakh additions.

Experimentations have been improving their function more and more with each new test. Tej Kohli wrote a post on the company's blog recently on just that topic. They brought up the use of limited (but effective) chatbots in China that allow customers to ask questions, and then be given step based solutions to their issues. Businesses there have specifically been using the program WeChat for the task.

The brain is relatively uncharted territory for tech. Harvard University geneticist George Church has written about impending technologies that "extend our brain both biologically and electronically," while AFP describes the brain as "the next frontier for the tech sector." We used the CB Insights database to identify 17 startups targeting the brain with their products and tech-enabled therapies. In just the past year, companies like Halo Neuroscience, InteraXon, Headspace, Nootrobox, and Israel-based BrainsGate have raised VC funds for supplements, apps, wearables and other brain-boosting technologies. Some companies hope to "hack the brain" to improve cognitive performance and reduce stress, while others are looking to treat mental illnesses and nervous system disorders.

VIENTIANE – Southeast Asian nations are in unparalleled disarray over Beijing's saber-rattling in the South China Sea, analysts and insiders say, with the fractures set to deepen as staunch China ally Laos hosts top regional diplomats this weekend. U.S. Secretary of State John Kerry and Chinese Foreign Minister Wang Yi are among the delegates due to fly in from Sunday for two days of meetings in Vientiane, the capital of the communist nation. The South China Sea is set to cast a long shadow over the summit that is hosted by the 10-member Association of Southeast Asian Nations (ASEAN). Earlier this month a U.N.-backed tribunal found there was no legal basis for China's claims to most of the strategic and resource-rich seas -- a ruling rejected as "waste paper" by Beijing. ASEAN prides itself on consensus diplomacy but divisions have never been starker with Beijing blamed for driving a wedge between members.

With the unemployment rate falling to 5.3 percent, the lowest in seven years, policy makers are heaving a sigh of relief. Indeed, with the technology boom in progress, there is a lot to be optimistic about. Manufacturing will be returning to U.S. shores with robots doing the job of Chinese workers; American carmakers will be mass-producing self-driving electric vehicles; technology companies will develop medical devices that greatly improve health and longevity; we will have unlimited clean energy and 3D print our daily needs. The cost of all of these things will plummet and make it possible to provide for the basic needs of every human being. I am talking about technology advances that are happening now, which will bear fruit in the 2020s. But policy makers will have a big new problem to deal with: the disappearance of human jobs. Not only will there be fewer jobs for people doing manual work, the jobs of knowledge workers will also be replaced by computers.

Machine learning is an intelligence that helps machines to learn without being programmed. It involves embedding programs to computers which help them to react to fresh data. In performing machine learning in real-time, there are many constraints that limit the ability to outperform the best in showing its effective use. The algorithms of machine learning perform well with the similar type of data the machine is trained with, but they fail to perform accurately when facing a new set of information. Limitations arise when the machine has to face data different from the trained set of data.

So, DeepMind's basic approach can be quickly and effectively adapted to the temperature of air currents around a data center, and the flow of heat through air vents -- what else could it improve? The flow of air through physical space is far better understood than, say, the flow of shipments through major ports, or of bee populations across a continent, or of students through university programs. We should expect that assigning a sufficiently insightful AI to find and eliminate inefficiencies in cargo routing, or field-pollinating, or graduate-producing, will produce more than a few percentage points of progress. The need for warehouse managers, public agricultural engineers, and academic advisers is about to plummet right alongside the more traditionally threatened sectors like customer service and manufacturing.

We propose a scalable temporal latent space model for link prediction in dynamic social networks, where the goal is to predict links over time based on a sequence of previous graph snapshots. The model assumes that each user lies in an unobserved latent space and interactions are more likely to form between similar users in the latent space representation. In addition, the model allows each user to gradually move its position in the latent space as the network structure evolves over time. We present a global optimization algorithm to effectively infer the temporal latent space, with a quadratic convergence rate. Two alternative optimization algorithms with local and incremental updates are also proposed, allowing the model to scale to larger networks without compromising prediction accuracy. Empirically, we demonstrate that our model, when evaluated on a number of real-world dynamic networks, significantly outperforms existing approaches for temporal link prediction in terms of both scalability and predictive power.

The risk that your job will be automated out of existence depends, of course, on the job you do. For many, that's already happened--typically in roles and industries where the name of the game is eliminating human error and improving efficiency. But in order for artificial intelligence to take a much bigger bite out of the knowledge-economy workforce, the technology may need to start behaving more like humans, not less. And that will mean mastering one key behavior: small talk. Sociolinguists involved in the Language in the Workplace Project at Victoria University of Wellington in New Zealand have discovered that people switch naturally between "transactional" talk--such as discussing a business goal--and "interactional" talk, like when you encourage or show concern for a distressed coworker.