China is stepping-up its mass surveillance, with a flock of camera-equipped drones designed to look like doves. The surveillance drones are fitted with flapping wings, allowing them to swoop, dive and glide just like the real thing. The robotic spies are almost indistinguishable from real doves and have even been spotted flying in flocks of real birds – helping them to avoid detection from radar. The machines are fitted with all the technology of a top-end spy drone, including a high-definition camera for photographs and video clips, GPS antenna, flight control system, and satellite data link. More than 30 military and government agencies have already deployed the birdlike drones to spy on the population, sources claim.

London might be tussling with Uber over its taxi license and grappling with Brexit, but it wants you to know that it's still a major hub for artificial intelligence. On Monday the city's Mayor, Sadiq Khan, promoted a survey he'd commissioned that suggested London was the "capital" of AI for Europe. "London has twice as many AI companies as Paris and Berlin combined," Khan said on the sidelines of the launch of London Tech Week, a collection of 200 tech events across the city that also kicked off on Monday. Khan denied his transport office was smothering innovation by moving to take away Uber's taxi license last year. "We're not saying'no' to innovation, but'no' to rule-breaking," he said.

This article focuses on the political and geopolitical consequences of the feedback relationship linking Artificial Intelligence (AI) in its Deep Learning component and computing power – hardware – or rather high performance computing power (HPC). It builds on a first part where we explained and detailed this connection. There we underlined notably three typical phases where computation is required: creation of the AI program, training, and inference or production (usage). We showed that a quest for improvement across phases, and the overwhelming and determining importance of architecture design – which takes place during the creation phase – generates a crucial need for ever more powerful computing power. Meanwhile, we identified a feedback spiral between AI-DL and computing power, where more computing power allows for advances in terms of AI and where new AI and the need to optimize it demand more computing power.

In a 2016 address to propaganda cadres and state-run media personnel, Chinese President Xi Jinping expressed dreams of instilling a new international media order "wherever the readers are, wherever the viewers are; that is where propaganda reports must extend their tentacles." As Xinhua News, China's largest state-run news agency, equips itself with "Media Brain," an artificial intelligence (AI) newsroom to assist all stages of reporting, these "tentacles" of propaganda may extend faster. Bringing AI to newsrooms can improve accuracy, enhance data analysis, and increase efficiency. According to a video released by Xinhua in January, the AI newsroom will do everything "from finding leads to news gathering, editing, distribution, and, finally, feedback analysis." Last week, Xinhua announced an update to Media Brain called "MAGIC," which will use machine generated content (MGC) for "fast-speed news production" and can automatically generate a news video in as fast as 10 seconds.

On her first day at NASA in 1999, Dr. Ayanna Howard walked into the Telerobotics Research and Applications Group at the Jet Propulsion Laboratory, excited to begin programming Mars rovers with her newly assigned staff. But a male staff member barely registered her presence, saying "The secretaries work down the hall." So began the rise of one of the few female African American roboticists in America. To be fair, Dr. Howard's staffer probably didn't realize that the young woman entering the lab was his boss because he had never met a female robotics Ph.D. Even today, although 74 percent of girls are interested in technology-related fields such as computer science, as adults they represent only 25 percent of all computing occupations.

Data management and data analytics are two critical fundamental resources that should be used by Thai enterprises and tech startups to develop innovative services backed by artificial intelligence (AI) technology, instead of working to develop intelligent products or services to compete with global players. Chai Wutiwiwatchai, research unit director of the National Electronics and Computer Technology Center (Nectec), said local enterprises can benefit from the many data sets held by state agencies through 20 ministries and the private sector. "Intelligent products and services driven by AI may not be easy to enter for local enterprises and startups, as there are too many global tech players and AI tech-embedded tools available for free in the market," he said. But the government must urgently digitise the existing data sets of all agencies, 70% of which are stored on paper and in portable document format (PDF) files. Speaking on the sidelines of the "AI Shapes the Future" forum last week, Mr Chai said innovative products and services embedded with AI tech have been increasingly accessible in the global market for four years, especially through popular use cases of image recognition, biometrics, cybersecurity and smart speakers.

These and many other fascinating insights were shared during Eightfold.ai's Panel participants included Monika Fahlbusch, Chief Employee Experience Officer at BMC Software and former Senior Vice President, Global Employee Success at Salesforce, Ciara Ennis, Senior Marketing Manager EMEA for Twilio, Russell Williams, former Vice President of Human Resources at PARC, A Xerox Company and Ashutosh Garg, Eightfold.ai The Honorable Ananth Kumar Hegde, Union Minister of State, India, also addressed in detail his plans for re-skilling India and empowering youth in his nation. The panel provided insights into how CHROs are meeting the many challenges of talent management today and provides valuable lessons learned. How Machine Learning Is Solving One Of HR's Greatest Paradoxes Winning the war for talent must be multidimensional with a strong focus on making every HR process more employee-centric.

With international trade agreements becoming increasingly complex, UNCTAD is working with the Brazilian arm of the International Chamber of Commerce (ICC Brazil) to use artificial intelligence (AI) to help trade negotiators, especially those representing less powerful nations. "Artificial intelligence could help reduce the complexity of information and level the playing field between big and small players in trade negotiations," said Bonapas Onguglo, in charge of UNCTAD's trade analysis branch. A comparison of the 1985 US-Israel trade deal with the one that the United States and Singapore signed in 2004 shows how much such agreements have evolved. AI assists in trade negotiations The 1985 deal has less than 8,000 words and contains just 22 articles, mostly dedicated to tariffs, agricultural restrictions, import licensing and rules of origin – what Harvard economist Dani Rodrik calls conventional trade topics . While these issues are also covered in the US-Singapore deal, most of its 20 chapters and 70,000 or so words deal with other topics such as anti-competitive business conduct, e-commerce, intellectual property, investment rules, labour rights and the environment.

Experts have warned for years that robots will replace humans in restaurants. Instead, a twist on that prediction is unfolding. Amid the lowest unemployment in years, fast-food restaurants are turning to machines--not to get rid of workers, but because they can't find enough. The hospitality industry had 844,000 unfilled positions in April, a record high, according to the Labor Department. Employment in food service and drinking places has increased by 1.6 million since May 2013 to 11.9 million in May 2018.

For the past five years, the hottest thing in artificial intelligence has been a branch known as deep learning. The grandly named statistical technique, put simply, gives computers a way to learn by processing massive amounts of data. Thanks to deep learning, computers can easily identify faces and recognize spoken words, making other forms of humanlike intelligence suddenly seem within reach. Companies like Google, Facebook and Microsoft have poured money into deep learning. And the technology's perception and pattern-matching abilities are being applied to improve progress in fields such as drug discovery and self-driving cars. But now some scientists are asking whether deep learning is really so deep after all.