I have a confession to make. I'm a privacy lawyer who researches the risks of face recognition technology – and I will be buying the new iPhone. Apple's next generation smartphone will use face recognition, thanks to infrared and 3D sensors within its front-facing camera. Reports indicate that the face scan and unlock system will be almost instantaneous and require no buttons to be pressed, being always "on" and ready to read your face. Android users can expect similar face unlock features as well.

"One Belt, One Road will connect the ancient Silk Road trade route with southeast Asia and we are in the middle," said Xu Datong, chairman of the Administrative Committee for TEDA. "We need to make sure we are ready." In June, TEDA unveiled the Intelligent Industrial Zone, a 20-sq. "We are embracing smart manufacturing with open arms. It will allow us to respond to the needs of increasingly demanding consumers both here and around the world and it represents the backbone of the next stage of China's development," said Mr. Xu.

Machine learning is a recent technology based on AI (Artificial Intelligence). Using AI, a software application can run its sequential tasks intelligent and independent manner without any logical programming. The AI application can generate an effective throughput by applying statistical and predictive machine learning algorithms and analysis to the existing data. Data collection, data preparation, data modelling, data model testing and performance monitoring are the five phases of machine learning. It can be applicable in many real-time environments like healthcare domain, face recognition and tagging features in social networks, spam detecting in mailbox, relevant ad displays etc.

In the next phase of artificial intelligence development, the firm behind Sophia the robot -- who once said she wanted to destroy humans -- is integrating blockchain into its work. Hanson Robotics' new project is a marketplace in the cloud where AI developers can put up their work, which can be tapped by others to enhance existing robots or build new ones, the company's chief scientist, Ben Goertzel, told CNBC on Monday. "At Hanson Robotics, we've made a cloud-based infrastructure for robot intelligence, but now we're looking to take that to the next level and we've launched a new project called SingularityNET, which is AI and blockchain together," Goertzel said at the sidelines of Switch Singapore. "It's a decentralized, open market for AIs in the cloud so anyone who develops an AI can put it into the SingularityNET, wrap it in our cryptocurrency-based smart contract and then the AI they put there can help to serve the intelligence of robots like Sophia or any other robots or any software programs that need AI," he added. Many proposed applications on blockchain technology -- the same tech that underpins bitcoin -- use cryptocurrencies or other digitised tokens for users to pay for functions.

Alibaba Cloud, a subsidiary of Chinese internet giant Alibaba Group Holding Ltd. [NYSE:BABA], will provide more artificial intelligence products for Hong Kong through its Big Data computing service MaxCompute, the company said in a press briefing on Sept. 18. MaxCompute, which was put into service the same day, provides solutions for users' mass data computing problems and can significantly cut corporate costs while ensuring data security. "Data processing and analysis remain the main services provided by cloud computing providers," said Min Wanli, an AI scientist at Alibaba Cloud. "Offering services through MaxCompute can improve our local service capability and provide comprehensive cloud solutions to our customers to meet users' growing demand for security and extensible computing services."

NEW YORK – The foreign ministers of Japan, the United States and India agreed Monday in New York to work together to develop strategically important ports and other infrastructure in the Indo-Pacific region, apparently seeking to balance China's bid to strengthen its regional influence. Foreign Minister Taro Kono said he, U.S. Secretary of State Rex Tillerson and Indian External Affairs Minister Sushma Swaraj "completely agreed to coordinate with each other toward the realization of a free and open Indo-Pacific." They agreed to work to spread and establish their shared basic values of the rule of law and the freedom of navigation and overflight in the region, Foreign Ministry officials said. The ministers affirmed that they will strengthen connectivity in the region through investment in infrastructure and work together to assist strategically important coastal nations in the region with maritime capacity-building, centering on key ports. According to the U.S. State Department, the ministers "discussed the importance of a free and open Indo-Pacific region underpinned by a resilient, rules-based architecture that enables every nation to prosper."

We consider the estimation of Dirichlet Process Mixture Models (DPMMs) in distributed environments, where data are distributed across multiple computing nodes. A key advantage of Bayesian nonparametric models such as DPMMs is that they allow new components to be introduced on the fly as needed. This, however, posts an important challenge to distributed estimation -- how to handle new components efficiently and consistently. To tackle this problem, we propose a new estimation method, which allows new components to be created locally in individual computing nodes. Components corresponding to the same cluster will be identified and merged via a probabilistic consolidation scheme. In this way, we can maintain the consistency of estimation with very low communication cost. Experiments on large real-world data sets show that the proposed method can achieve high scalability in distributed and asynchronous environments without compromising the mixing performance.

In this paper, we develop a new accelerated stochastic gradient method for efficiently solving the convex regularized empirical risk minimization problem in mini-batch settings. The use of mini-batches is becoming a golden standard in the machine learning community, because mini-batch settings stabilize the gradient estimate and can easily make good use of parallel computing. The core of our proposed method is the incorporation of our new "double acceleration" technique and variance reduction technique. We theoretically analyze our proposed method and show that our method much improves the mini-batch efficiencies of previous accelerated stochastic methods, and essentially only needs size $\sqrt{n}$ mini-batches for achieving the optimal iteration complexities for both non-strongly and strongly convex objectives, where $n$ is the training set size. Further, we show that even in non-mini-batch settings, our method achieves the best known convergence rate for both non-strongly and strongly convex objectives.

This article was originally published at 11:40 a.m.

Aggression and sexual behaviour are controlled by the same brain cells in male mice – but not in females. The finding suggests that males are more likely to become aggressive when they see a potential mate than females. The brain regions that contain these cells look similar in mice and humans, say the researchers behind the study, but they don't yet know if their finding has relevance to human behaviour. Similar to humans, male mice are, on the whole, more aggressive than females. Because of this, most research into aggression has overlooked females, says Dayu Lin at New York University.