WASHINGTON, DC – Around 1200 BC, the Shang Dynasty in China developed a factory system to build thousands of huge bronze vessels for use in everyday life and ritual ceremonies. In this early example of mass production, the process of bronze casting required intricate planning and the coordination of large groups of workers, each performing a separate task in precisely the right order. A similarly complex process went into fashioning the famous army of terracotta warriors that Qin Shi Huang, China's first emperor, unveiled one thousand years later. According to the Asian Art Museum in San Francisco, the statues "were created using an assembly production system that paved the way for advances in mass production and commerce." Some scholars have speculated that these early forms of prescriptive-work technologies played a large role in shaping Chinese society.

The other day, a friend told Jordan Erica Webber that her tech-savvy dad has used the Raspberry Pi – a small and very cheap computer – to build all sorts of creative projects. For example, he created bark-activated door that allowed the family dog to let herself out for her morning pee. Maker culture is on the rise. This kind of tech-based extension of DIY culture covers things like 3D printing and robotics, involving learning how to make physical things yourself. Many view it as a movement against consumerism, a way to avoid just being a passive user of tech, with all that entails. But it's not just people who work in tech who are participating in maker culture.

We get a vague due date for Tesla's next big project, the Model Y, Google's voice assistant makes its way into thousands more smart devices and cheaters never prosper (and possibly go to jail) when it comes to Overwatch and Fortnite. Elon Musk says it'll spark a'manufacturing revolution'. Tesla's latest prediction for Model Y's arrival is 2020 Tesla's forthcoming Model Y is still shrouded in mystery. We know it's a crossover EV, and we know it might not have mirrors... and that's about it. But CEO Elon Musk has now revealed that the company aims to bring the new vehicle to production in 2020, adding in its conference call that doing so will spark a "manufacturing revolution".

Silicon Valley's Jim Breyer explains why today's new AI companies are built differently than previous software and web startups. Q: Your old firm, Accel Partners, invested in a broad range of tech startups. Your new firm exclusively invests in AI. Breyer: I'm two years into a ten-year investment business plan in AI, and it's been fascinating. I spend a lot of time at universities around the world and am on various boards at Harvard, Stanford and Tsinghua University in China.

US-based international market survey agency Compass Intelligence LLC recently released its list of the top 15 artificial intelligence (AI) chip makers, among whom the US NVIDIA Corp. ranked first, while Shenzhen-based HiSilicon Technologies Co., a unit of communications giant Huawei Technologies Co., ranked 12th, the highest among Chinese companies. The list showed the US Intel Corp. and the Netherlands NXP Semiconductors NV ranking second and third. America's IBM Corp., Google Inc. of Alphabet Inc. and Apple Inc. ranked fourth, sixth and eighth, respectively. Compass Intelligence compiled the list of software and hardware companies which produce artificial intelligence chipsets. Products evaluated included central processors, image processors, neural network processors and application-specific integrated circuits, all of which it comprehensively graded and ranked in accordance with market indexes, supplier tracing analyses and company statistics.

"In the long term, harnessing AI and technology will determine the split between winners and losers," said Jeroen van Oerle, Portfolio Manager Robeco Fintech Equities, Robeco. "In order to keep relevant for the future, you need efficient back-office operations. On top of that, you need to be able to tailor make products. If you cannot provide those kinds of services in the future, a competitor will and you will lose." Similar to the largest US institutions, European banks have a strong interest in exploring the impact of AI on business functions.

When Angelica Lim bakes macaroons, she has her own kitchen helper, Naoki. Her assistant is only good at the repetitive tasks, like sifting flour, but he makes the job more fun. Naoki is very cute, just under two feet tall. He's white, mostly, with blue highlights, and has speakers where his ears should be. The little round circle of a mouth that gives him a surprised expression is actually a camera, and his eyes are infrared receivers and transmitters. "I just love robots," said Lim in 2013, at the time a Ph.D. student in the Department of Intelligent Science and Technology at Kyoto University in Japan.

One of the ways that intelligent computers and Artificial Intelligence (AI) platforms "think" is by analysing the relationships between and within large sets of data. Now, using a new type of Quantum Machine Learning (QML) algorithm, an international team have demonstrated that quantum computers can analyse a far wider array of data types than was previously expected. The details of the team's new "Quantum Linear System Algorithm," or QLSA, was published in Arvix, and in the future it could help crunch numbers on problems as varied as commodities pricing, social networks and chemical structures, and usher in a new era of Quantum AI. "Previous quantum algorithms only worked on very specific types of problem. We needed an upgrade if we want to achieve a quantum speed up for other data," said Zhikuan Zhao, who co-authored the paper, and that's exactly what he, and his colleagues, Anupam Prakash at the Centre for Quantum Technologies in Singapore, and Leonard Wossnig from ETH Zurich and the University of Oxford, have done. QLSA's were first proposed in 2009 by a different group of researchers and since then the idea's helped kick start research into new exotic forms of AI such as Quantum Artificial Intelligence (QAI), which gradually I'm seeing more and more research papers reference.

Feng Xiang, a professor of law at Tsinghua University, is one of China's most prominent legal scholars. He spoke at the Berggruen Institute's China Center workshop on artificial intelligence in March in Beijing. BEIJING -- The most momentous challenge facing socio-economic systems today is the arrival of artificial intelligence. If AI remains under the control of market forces, it will inexorably result in a super-rich oligopoly of data billionaires who reap the wealth created by robots that displace human labor, leaving massive unemployment in their wake. But China's socialist market economy could provide a solution to this.

"Artificial intelligence is the future, not only for Russia but for all humankind. Whoever becomes the leader in this sphere will become the ruler of the world," said Vladimir Putin. AI (Artificial Intelligence) is getting really popular and powerful. It's been used in several industries but its use in customer service has been phenomenal. Businesses use AI to augment human customer service agent and tremendous results are being recorded.