Artificial intelligence may not be so threatening after all. Amid warnings of the economic disruption that robots and automation could unleash on the world economy as traditional roles disappear, researchers are finding that new technologies will help fuel global growth as productivity and consumption soar. AI will contribute as much as $15.7 trillion to the world economy by 2030, according to a PwC report Wednesday. That's more than the current combined output of China and India. Gains would be split between $6.6 trillion from increased productivity as businesses automate processes and augment their labor forces with new AI technology, and $9.1 trillion from consumption side-effects as shoppers snap up personalized and higher-quality goods, according to the report.

Machine learning is the technology behind any sophisticated dynamic pricing algorithm. These algorithms make optimal pricing decisions in real time, helping a business increase revenues or profits. In the case of a freemium mobile app, a dynamic pricing algorithm sets optimal prices for in-app purchases to increase revenues and engage price-sensitive customers. Dynamic pricing for mobile games and apps is a recent innovation. The majority of mobile apps are not using dynamic pricing algorithms today.

There is a rising demand for IT engineers in Japan as many point out there is a shortage of such professionals domestically. An estimate shows that Japan will face a shortage of close to 600,000 IT-related professionals by 2030. As companies are moving to recruit workers from overseas, skilled IT engineers, especially from Asia, are increasingly garnering attention. Such a trend seems to be in line with the government's policy to further increase the number of foreign workers with technical skills. What are some of the issues Japanese firms need to address when expanding the hiring of foreign workers? Staffing agencies reportedly plan to shore up their efforts to recruit IT workers from Asian countries. Meanwhile, a program called Project Indian Institutes of Technology (PIITs), which involves IT-powerhouse India, invites students from the Indian Institutes of Technology (IIT) to intern at Japanese firms. The Japan Times organized a forum on June 13, titled "IT human resources sought overseas by Japanese companies: an example of an internship program by IIT students," to enhance the discussion regarding the IT engineer situation in Japan. Japanese companies accepting IIT students as interns and Indian students taking part in the program were invited to discuss their thoughts. The participants of this forum were Hiroshi Hirabayashi, president and representative director of the Japan-India Association; Shigeo Mizuno, director and corporate vice president of Fujifilm Software Co.; Koji Iwamoto, deputy manager of the general planning department at Tonichi Printing Co.; and Toyoaki Machida, Japan general manager of the global section at Webstaff Co. Additionally, Himanshu Tolani, a third-year undergraduate student at the Indian Institute of Technology, Ropar; Shubham Jain, a third-year undergraduate student at the Indian Institute of Technology, Jodhpur; and Yash Ubale, a third-year undergraduate student at the Indian Institute of Technology, Ropar, participated. The moderator was Takashi Kitazume, chief editorial writer of The Japan Times. Below are excerpts of their discussion. Moderator: Thank you for your participation despite the bad weather today. At this panel discussion, I'd like to hear the intentions of those taking part in this program, the feedback from Japanese companies accepting Indian Institute of Technology (IIT) students as interns and also from the Indian students to enhance the discussion on the theme of "IT human resources sought overseas by Japanese companies: an example of an internship program by IIT students."

From Alexa and self-driving cars to job applicant screening processes, artificial intelligence is fast becoming the norm in business. But it also could start playing far bigger roles in security, helping law enforcement and other protective agents figure out who's up to no good. As Fredrick Kunkle of The Washington Post reports, there's now an AI-based kiosk designed to detect whether travelers are fibbing. Designed by Aaron Elkins, assistant professor of the Fowler College of Business Administration at San Diego State University, the new AI lie detector goes by the name Automated Virtual Agent for Truth Assessments in Real Time, or AVATAR for short. Once you've scanned your ID or passport, the kiosk asks you a bunch of questions.

AI powered wearables will provide a much-needed impetus to the stagnant wearables segment this year. Categories such as AI powered hearables will be instrumental to drive major growth, with Apple again leading the way to catalyze this trend. Your email address will not be published.

China will roll out a slew of AI research and development projects, allocate more resources to nurturing talent and increase the use of AI in education, healthcare and security among other things, said Wan Gang, the minister of science and technology at a conference in Tianjin.

Bangalore-based Niki.ai, which runs an artificial intelligence-powered personal assistant, has raised $2 million (about Rs 13 crore) in a Series A round of funding from San Francisco-based fund SAP.iO and existing investor Unilazer Ventures. VCCircle had exclusively reported on this development last month. Haresh Chawla of private equity firm True North, and Arihant Patni of Hive Technologies also invested, besides some US- and Germany-based investors, the company said on Wednesday. Software giant SAP launched SAP.iO with an initial investment of $35 million in March this year. The fund seeks to make early-stage investments in software startups with an aim to expand the SAP ecosystem.

Sometimes the best place to showcase the potential of a bold, world-changing technology is a flower garden. Take the case of Ofer Dekel, for example. He manages the Machine Learning and Optimization group at Microsoft's research lab in Redmond, Washington. Squirrels often devoured flower bulbs in his garden and seeds from his bird feeder, depriving him and his family of blooms and birdsong. To solve the problem, he trained a computer-vision model to detect squirrels and deployed the code onto a Raspberry Pi 3, an inexpensive, resource-constrained single-board computer.

Implicit schemes are popular methods for the integration of time dependent PDEs such as hyperbolic and parabolic PDEs. However the necessity to solve corresponding linear systems at each time step constitutes a complexity bottleneck in their application to PDEs with rough coefficients. We present a generalization of gamblets introduced in \cite{OwhadiMultigrid:2015} enabling the resolution of these implicit systems in near-linear complexity and provide rigorous a-priori error bounds on the resulting numerical approximations of hyperbolic and parabolic PDEs. These generalized gamblets induce a multiresolution decomposition of the solution space that is adapted to both the underlying (hyperbolic and parabolic) PDE (and the system of ODEs resulting from space discretization) and to the time-steps of the numerical scheme.

We propose a new neural sequence model training method in which the objective function is defined by $\alpha$-divergence. We demonstrate that the objective function generalizes the maximum-likelihood (ML)-based and reinforcement learning (RL)-based objective functions as special cases (i.e., ML corresponds to $\alpha \to 0$ and RL to $\alpha \to1$). We also show that the gradient of the objective function can be considered a mixture of ML- and RL-based objective gradients. The experimental results of a machine translation task show that minimizing the objective function with $\alpha > 0$ outperforms $\alpha \to 0$, which corresponds to ML-based methods.