Casting neural networks in generative frameworks is a highly sought-after endeavor these days. Contemporary methods, such as Generative Adversarial Networks, capture some of the generative capabilities, but not all. In particular, they lack the ability of tractable marginalization, and thus are not suitable for many tasks. Other methods, based on arithmetic circuits and sum-product networks, do allow tractable marginalization, but their performance is challenged by the need to learn the structure of a circuit. Building on the tractability of arithmetic circuits, we leverage concepts from tensor analysis, and derive a family of generative models we call Tensorial Mixture Models (TMMs). TMMs assume a simple convolutional network structure, and in addition, lend themselves to theoretical analyses that allow comprehensive understanding of the relation between their structure and their expressive properties. We thus obtain a generative model that is tractable on one hand, and on the other hand, allows effective representation of rich distributions in an easily controlled manner. These two capabilities are brought together in the task of classification under missing data, where TMMs deliver state of the art accuracies with seamless implementation and design.

Sophia, a humanoid robot with Saudi Arabian citizenship, speaks during the United Nation's innovation conference in Kathmandu, Nepal, on March 21, 2018. Sophia, who is now a citizen of Saudi Arabia, is the most advanced robot with artificial intelligence developed by a Hong Kong based company Hanson Robotics. Sophia, a social humanoid robot developed by Hong Kong-based company Hanson Robotics, addressed a conference on the theme'Public Services and Development' organised by the United Nations Development Programme, at Hotel Yak & Yeti, in Durbarmarg, Kathmandu, on Wednesday. Sophia started the speech with a joke on how the moderator was not like Nepali actor Anmol KC and when asked about her view on how artificial intelligence can help better public services in Nepal, she said, "the opportunities are endless," adding that AI can help improve the education sector, develop medicine, connect remote areas of Nepal to the centre, and help develop Nepal fulfill the Sustainable Development Goals. Similarly, in an answer to what she, as an AI can do, she claims that maybe she will be the first non-human to climb the Mount Everest.

At a time when Google is moving into an'artificial intelligence first' world, the Internet giant sees India playing a key role for many of its AI related bets. Google's AI technologies are being used for numerous applications such as detecting diabetic retinopathy, hunting for exoplanets using data from space agency NASA and analysing a vast amount of footage shot by drones. "I think [India's role] is a very significant one," Prabhakar Raghavan, vice-president of engineering at Google, told The Hindu. "You need a somewhat technically literate workforce and I am not talking about PhDs in computer science. And if you look at that, India is already a leader by any means," he said.

Renowned British theoretical physicist Stephen Hawking died on March 14, 2018. The news generated an online view rate of nearly 500 million in China. At the same time, almost 250,000 viewers responded to the news with comments and messages. According to Agence France-Presse, Stephen Hawking opened a Sina Weibo account two years ago and started posting messages in English and Chinese. These were well received by the Chinese followers, as Hawking wanted to engage fully with his Chinese audience and learn from them.

Cognitive computing and artifical intelligence (AI) will see global spend reach $19.1bn in 2018, with retail overtaking banking as the primary sector driving growth, according to market watcher IDC. IDC's research director of cognitive/AI David Schubmehl, said: "Interest and awareness of AI is at fever pitch. Every industry and every organization should be evaluating AI to see how it will affect their business processes and go-to-market efficiencies." Retail firms will invest $3.4bn this year on AI use cases, including automated customer service agents, expert shopping advisors and product recommendations, and merchandising for omni-channel operations. Banking, meanwhile, will spend $3.3bn, largely on automated threat intelligence and prevention systems, fraud analysis and investigation, and program advisors and recommendation systems.

In a bid to counter China's move towards usage of Artificial Intelligence (AI), the NITI Aayog will be chalking out a national policy on AI to outline its scope in research and commercial adaptation of the technology, according to a report by The Economic Times. The report suggests that the policy is expected to lay out short, medium and long-term goals which will have to be achieved by 2022, 2026 and 2030, starting from this year. The new policy may propose deadline for commercial adaptation of the technology in the fields of agriculture, health, education, banking, retail transportation, the report says. The policy may also incentivise startups and venture capital funds that take up AI research and adaptation. The Aayog has already undertaken half a dozen pilots on AI in agriculture, health, and education.

A team of Microsoft researchers said Wednesday that they believe they have created the first machine translation system that can translate sentences of news articles from Chinese to English with the same quality and accuracy as a person. Researchers in the company's Asia and U.S. labs said that their system achieved human parity on a commonly used test set of news stories, called newstest2017, which was developed by a group of industry and academic partners and released at a research conference called WMT17 last fall. To ensure the results were both accurate and on par with what people would have done, the team hired external bilingual human evaluators, who compared Microsoft's results to two independently produced human reference translations. Xuedong Huang, a technical fellow in charge of Microsoft's speech, natural language and machine translation efforts, called it a major milestone in one of the most challenging natural language processing tasks. "Hitting human parity in a machine translation task is a dream that all of us have had," Huang said.

"Imitation is the sincerest form of flattery" is an adage that is very applicable to the tech industry. This has been the case for Apple, who has always proven to be the trendsetter in more ways than one. But this year is slightly different. The Cupertino giant's rivals may have already copied the design of the iPhone X, but they are skipping the opportunity of bringing Face ID to their premium handsets this year. DigiTimes reported Friday that China-based smartphone vendors are not at all considering incorporating 3D sensors into their upcoming releases.

There hasn't been a major breakthrough in algorithms in the last year.

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