The workforce in 2040 is projected to be 20 percent smaller than in 2017 due to overall population decline if the economy sees no growth and women and the elderly continue to have difficulty landing jobs, according to government study released Tuesday. A study group of the labor ministry, releasing the first official projection for the size of Japan's workforce in 2040, called for additional policies to boost employment and promotion of artificial intelligence as measures to sustain productivity. The study did not take into consideration the expansion of the foreign workforce in 14 fields, including construction and nursing care, from April this year. The panel on employment policies set up by the Health, Labor and Welfare Ministry estimated that the number of workers in Japan will stand at 60.82 million in 2025 and 52.45 million in 2040, down from 65.3 million in 2017. The number of male workers in 2040 will fall by 7.11 million from 2017, while that of females will decrease by 5.75 million.

Investors including Google parent Alphabet Inc. and Saudi Arabia's main wealth fund have poured money into this much-hyped maker of augmented-reality glasses. The bugeye-like glasses with tinted lenses--released only to software developers thus far--overlay virtual reality-like images onto the real world, designed for use by gamers and neurosurgeons alike. Early reviews have been lukewarm. Priced at $999, Focals by North represents a less flashy but potentially more practical version of futuristic glasses. The glasses, released last fall, can display directions, texts and other simple displays by beaming hologram-like images into eyes.

Isaac Asimov, one of the Big Three--along with Arthur C. Clarke and Robert Heinlein--who brought science fiction literature to its golden age in the middle of the 20th century, used to celebrate his birthday on the second of January. But the man who bequeathed us the three laws of robotics was himself a great fictional character, starting with the first of his fictions--his own date of birth. Born in Petrovichi, a remote village in rural Russia, the day that he entered the world left no record even in the memory of his family, who came up with tentative range of dates between October 4, 1919 and January 2, 1920; it was Asimov himself who chose this last date as his birthday.

One of the big trends at this year's Consumer Electronics Show was the ever noticeable presence of robots on the showroom floor. As a kid growing up, I always wanted my own Johnny 5 robot, but at the time the idea was too farfetched, given the limitations of technology in the late '80s. But with the recent advancements in modern robotics, a childhood dream is now a reality. This year, multiple companies from all over the world flocked to CES 2019 to showcase their small wonders to attendees. While I was at the show, I made it my mission to check out as many robots as I possibly could, and here's my list of the best of the best.

Last week, Deqing county hospital in Guangdong Province launched free consultations featuring artificial-intelligence (AI) cameras to detect ocular fundus diseases, which are major causes of blindness, according to a report by Xinhua News. About 300 residents from Zhaoqing City in Dequing County attended the free consultation sessions. The hospital became the first to use the device, co-developed by China's search engine Baidu and Sun Yat-sen University, to serve the general public. The instrument is capable of diagnosing three types of fundus disorders -- diabetic retinopathy, glaucoma and macular degeneration. It scans the eyes and generates a report in 10 seconds, all done without the need for an ophthalmologist to be present.

Machine learning sure is an umbrella word for many methodologies and tools but one must be clear about the fact that it is not an umbrella word for all the solutions. No one can deny that machine learning has revolutionised the way data can be squeezed in for discoveries. What one should care about is that the enhancement of any technology also depends on a relentless introspective approach in attacking the shortcomings. The rise in popularity sure lures every amateur into believing that they have reached their destination. With tools and frameworks being open-sourced, everyone can play with data, experiment with MNIST datasets and get really good accuracy scores.

To look back on the year, we compiled a list of our most popular posts for your enjoyment. We found London, Paris, Singapore, Munich, and Tel Aviv to be five innovation hotspots and examined what makes them so attractive to entrepreneurs. We analyzed over 10,000 news articles published over a year span reporting on the food and beverage category. We decided to find out what focus areas of fintech have grown and received the most investment, and which companies are leading the public narrative behind innovation in the finance and banking sectors. We used Quid software to dig deeper into the overall effects from the campaign.

Kai Fu Lee, an artificial intelligence (AI) expert, venture capitalist, and former executive of such companies as Apple, Microsoft, and Google, tells Scott Pelley of "60 Minutes" in an interview airing Sunday night on CBS News that he believes AI will displace 40 percent of the jobs out there -- jobs not exclusive to blue-collar work -- across the globe in as little as 15 years. The native of Taipei, Taiwan, and the Columbia University and Carnegie Melon graduate goes into detail about his claims in his "60 Minutes" interview airing Sunday at 7 p.m. ET. "AI will increasingly replace repetitive jobs, not just for blue-collar work, but a lot of white-collar work," Lee tells Pelley on the program, as CBS News reported in advance. "Chauffeurs, truck drivers, anyone who does driving for a living -- their jobs will be disrupted more in the 15 to 20-year time frame. Many jobs that seem a little bit complex, chef, waiter, a lot of things will become automated … stores … restaurants, and altogether in 15 years, that's going to displace about 40 percent of the jobs in the world." Lee is CEO of Sinovation Ventures and is considered one of the "world's foremost experts" on artificial intelligence. Pelley pushed back on the claim of 40 percent -- and Lee said the jobs will be "displaceable."

End-to-end task-oriented dialogue is challenging since knowledge bases are usually large, dynamic and hard to incorporate into a learning framework. We propose the global-to-local memory pointer (GLMP) networks to address this issue. In our model, a global memory encoder and a local memory decoder are proposed to share external knowledge. The encoder encodes dialogue history, modifies global contextual representation, and generates a global memory pointer. The decoder first generates a sketch response with unfilled slots. Next, it passes the global memory pointer to filter the external knowledge for relevant information, then instantiates the slots via the local memory pointers. We empirically show that our model can improve copy accuracy and mitigate the common out-of-vocabulary problem. As a result, GLMP is able to improve over the previous state-of-the-art models in both simulated bAbI Dialogue dataset and human-human Stanford Multi-domain Dialogue dataset on automatic and human evaluation.

In this paper, We Apply Reinforcement learning (RL) techniques to train a realistic biomechanical model to work with different people and on different walking environments. We benchmarking 3 RL algorithms: Deep Deterministic Policy Gradient (DDPG), Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) in OpenSim environment, Also we apply imitation learning to a prosthetics domain to reduce the training time needed to design customized prosthetics. We use DDPG algorithm to train an original expert agent. We then propose a modification to the Dataset Aggregation (DAgger) algorithm to reuse the expert knowledge and train a new target agent to replicate that behaviour in fewer than 5 iterations, compared to the 100 iterations taken by the expert agent which means reducing training time by 95%. Our modifications to the DAgger algorithm improve the balance between exploiting the expert policy and exploring the environment. We show empirically that these improve convergence time of the target agent, particularly when there is some degree of variation between expert and naive agent.