Ping An Insurance (Group), a relative newcomer to the insurance industry, now ranks among the world's largest and most valuable insurers,(1) with more than 160 million customers.(2) Notably, its use of technology to embrace new business models that supplement its core insurance offerings is indicative of a wider global trend of providing customers with digital, value-added services. Significantly, Ping An has recognised the gains to be had by engaging with newer, more innovative online distribution models to connect with consumers, investing approximately $1 billion per year into internet development(3) and spending $1.5 billion in this regard in 2017 alone.(4) This parallels similar moves by insurers in other major jurisdictions. In the wake of the 2008 global financial crisis, insurers and reinsurers in the major insurance jurisdictions have faced a climate of lower interest rates and increased regulatory and capital requirements.

Forter, a company that uses machine learning to detect and prevent fraud in online retail transactions, announced today that it has raised $50 million in a series D funding round led by March Capital Partners, bringing its total financing to $100 million. Salesforce Ventures joined the round, along with previous investors including Sequoia Capital and New Enterprise Associates (NEA). Global online retail sales amounted to more than $2 trillion in 2017, and this number is projected to reach more than $4.5 billion by 2021. But as online retail grows, so does online fraud. Account takeover attacks are on the rise, as are high-volume automated "bot" attacks and so-called policy attacks like coupon abuse.

China-based Inspur rolled out a new set of Open Compute Project (OCP)-based hyperscale rack servers that included support for artificial intelligence. Inspur is the third-largest server vendor in the world and the biggest in China, according to Dolly Wu, vice president of data center and cloud at Inspur. Inspur's technology has cornered 57% of the artificial intelligence (AI) market share in China, and now it has included some of that technology into one of its new server nodes. "The highlight that we want to bring for the OCP community is that Inspur is introducing several new compute modules using the San Jose motherboard, which we contributed to OCP last year," Wu said in an interview with FierceTelecom. Using this motherboard, we've created three new compute modules."

One of the key targets Enlitic is focused on is early detection of lung cancer by combining biopsies along with existing medical data to be able to diagnose lung cancer earlier than with the traditional medical methods. While based in San Francisco, Enlitic is present in Japan, Canada, Australia, and China. AI is the buzzword startups are very keen on using when describing their products. We've been seeing ideas on what it could do in movies for decades. So what qualifies as AI?

To better understand how artificial intelligence (AI) is being adopted differently by nations around the world, we sat down with Virtusa's Executive Vice President of Global Digital Solutions, Frank Palermo. As AI takes a more prevalent role in our society, the issue of ethics and governance has become critical, and policymakers around the globe have a collective responsibility to be forward thinking when deciding how best to regulate it. It is imperative that AI is managed in a way that allows the technology to reach its full potential, while ensuring it doesn't have a negative impact on humans and society. The US has historically left technology companies relatively unimpeded by government oversight or stringent regulation, with the market dominance of the FAANG companies (Facebook, Apple, Amazon, Netflix and Alphabet's Google) serving as a perfect example of this. While China has taken almost the opposite approach, with the Chinese government having a more'hands-on' role, specifically mentioning AI in their'grand vision' for the country, this has somehow still resulted in a similar ecosystem of tech giants, namely the BAT companies (Baidu, Alibaba and Tencent).

Chinese e-commerce company JD.com's finance division has launched a blockchain and artificial intelligence (AI) focused research institute to concentrate on building so-called'smart cities and societies.' The Nanjing-based Smart City Research Institute will attempt to find the most cost-effective and efficient ways of building tech-savvy cities through the utilization of blockchain, AI and big data solutions. It will collaborate with industrial construction operations; focused on China's eastern region for the foreseeable future. The Institute will research advanced intelligent solutions in the areas of urban environment, transportation, planning, energy consumption, commerce, security, healthcare, and e-government. Jingdong Group, known more widely as JD.com, has been keen to make its mark in the blockchain sphere.

Microsoft expects to do more artificial intelligence research in Taiwan. Artificial brains threaten to outnumber real ones in Taiwan, as the island's prowess in artificial intelligence (AI) continues to grow. Global players such as Google, IBM and Microsoft have all expressed their intentions of developing either AI R&D centers or similar initiatives in Taiwan. These companies could have selected other tech-savvy locations in Asia like South Korea and Shenzhen, China, but they chose Taiwan. "Taiwan has a lot going for it with AI research," says William Foreman, president of the American Chamber of Commerce in Taipei.

China is enthusiastically embracing the fast-developing technology of artificial intelligence in an effort to give the country a strategic edge over its rivals. Best known for defeating humans at boardgames as Go and chess as well as US gameshow Jeopardy the technology is being lined up by officials as a useful tool for assessing the potential risk of overseas investment presented by unstable regimes and terrorism. To do this the Chinese Academy of Sciences has coded a program capable of trawling vast amounts of data gleaned from China's sprawling diplomatic and intelligence network to make sense of information that would overwhelm human tacticians. AI is increasingly regarded as a revolution comparable to that of the combustion engine, sparking a global arms race as nations seek to become the first to master the technology. China already has a national AI strategy in place to guide development as it works to become the world's pre-eminent AI research hub by 2030.

Deep neural networks have established as a powerful tool for large scale supervised classification tasks. The state-of-the-art performances of deep neural networks are conditioned to the availability of large number of accurately labeled samples. In practice, collecting large scale accurately labeled datasets is a challenging and tedious task in most scenarios of remote sensing image analysis, thus cheap surrogate procedures are employed to label the dataset. Training deep neural networks on such datasets with inaccurate labels easily overfits to the noisy training labels and degrades the performance of the classification tasks drastically. To mitigate this effect, we propose an original solution with entropic optimal transportation. It allows to learn in an end-to-end fashion deep neural networks that are, to some extent, robust to inaccurately labeled samples. We empirically demonstrate on several remote sensing datasets, where both scene and pixel-based hyperspectral images are considered for classification. Our method proves to be highly tolerant to significant amounts of label noise and achieves favorable results against state-of-the-art methods.