AI Saturdays, also known as AI6, is a community-driven, non-profit movement established to offer education on artificial intelligence (AI) to the masses. Through structured study groups, lectures and project work, the organizers aim to teach everybody how they can use AI in their everyday lives. With the first chapter established in December 2017 in Singapore by Nurture.AI CEO Mr. Yap Jia Qing, followed by the second soon after in Kuala Lumpur, it could be said that the AI6 movement is in its infancy. Yet within a few months, the initiative has grown to include 103 chapters across six continents, including 47 in Asia. At time of writing, there are over 5,000 participants worldwide, from Kathmandu to California.

There has been much speculation about the power and dangers of artificial intelligence (AI), but it's been primarily focused on what AI will do to our jobs in the very near future. Now, there's discussion among tech leaders, governments and journalists about how artificial intelligence is making lethal autonomous weapons systems possible and what could transpire if this technology falls into the hands of a rogue state or terrorist organization. Debates on the moral and legal implications of autonomous weapons have begun and there are no easy answers. The United Nations recently discussed the use of autonomous weapons and the possibility to institute an international ban on "killer robots." This debate comes on the heels of more than 100 leaders from the artificial intelligence community, including Tesla's Elon Musk and Alphabet's Mustafa Suleyman, warning that these weapons could lead to a "third revolution in warfare."

All the major economies in the world understand the strategic importance of artificial intelligence in empowering and transforming economic growth in the coming decades. In July 2017, China's State Council laid out an ambitious AI strategic plan to create a domestic 1 trillion yuan (US$147.80 billion) AI industry and make China the world's leading AI innovation centre by 2030. Although too early to say if China will succeed, all the factors seem to be in China's favour, such as market readiness, start-up money, talent, and supportive government policies and budget. Over the past decade, China's vast population has shown great eagerness and willingness to embrace various new technologies. Take the rapid growth of China's smartphone industry as an example: over the past 10 years, it has grown from a single-digit penetration rate to over 50 per cent in 2017.

Make a trip to any major electronics store today and you're bound to find a section selling drones. Once little more than toys for enthusiasts, today's commercially available drones come in all shapes and sizes and are used for all sorts of purposes, with prices ranging from thousands to hundreds of thousands of yen. But the proliferation of drone technology has brought with it questions about security, and invasion of privacy. The central government and many localities around Japan have put into place a number of ordinances in recent years limiting and forbidding drones near certain locations. Last year the National Policy Agency said there had been 68 cases of illegal drone flights, almost double the previous year's 36.

LawGeex, the legal AI pioneer in contract review has today announced that it has closed a $12m funding round led by venture capital fund, Aleph. The investment brings LawGeex's total funding to date to $21.5m. Previous investors, including Lool Ventures, also participated in this round. The additional capital will be used by LawGeex to'fortify its position…deepen its product offering, and expand its US presence following the opening of its New York office earlier this year' said the Tel Aviv-based company. Aleph partner, Eden Shochat, told Artificial Lawyer why they had so resoundingly backed legal AI company, LawGeex: 'We invest in industries that are going through transformation.

Publicis Media has appointed Ankush Talwar as head, data sciences. Talwar has worked with organisations such as Inductis, Amex, Accenture, Flipkart. He joins from Neo@Ogilvy where he was VP and head of analytics and insights. Anupriya Acharya, CEO, Publicis Media India, added, "Data science is a core expertise in Publicis Media and given our unmatched expertise in Data, Digital and Performance media, it is also a competitive advantage. In fact, PM India has been successfully running the global Data and Analytics Centre Of Excellence for many years now and the team has won multiple global accolades too. Ankush, with his strong and diverse background, has been handpicked to further enhance our capability building on Data Strategy and Insights that includes overseeing Platforms, Advanced Analytics, Artificial Intelligence, Machine Learning and Data engineering. He joins us at an important time and will work closely with our global network, clients and Brand teams."

A new school for machine learning hopes to churn out Chinese tech talent--and surprisingly, it's being helped by some of North America's finest AI minds. Background: China plans to become the world leader in AI by 2030. That feat will only be accomplished with a lot more AI talent. The news: Wired reports that Kai-Fu Lee, the former chief of Google's operations in China who now runs an investment firm focused on AI, just launched a school to train more Chinese AI talent. It could add close to a thousand new AI graduates every year, right from the start.

Advance in artificial intelligence and automation could replace as many as half the financial services workers over the next decade, industry experts say, but it's going to take a big investment to make that happen. James D'Arezzo, CEO of GlenMOBILE VOICE TELEPHONY usage in Africa has remained stable and the situation is likely to persist at least until the end of this year – despite increasing adoption of Over the Top (OTT) applications such as instant messaging and social media platforms, dale-based Condusiv Technologies, says that's where things are headed. And the process will be complicated. "Unless banks deal with the performance issues that AI will cause for ultra-large databases, they will not be able to take the money gained by eliminating positions and spend it on the new services and products they will need in order to stay competitive," he said. Intensive hardware upgrades are often cited as an answer to the problem, but D'Arezzo said that's prohibitively expensive.

Agriculture companies are always striving to produce better tasting, longer lasting fruits and vegetables. Whether it's corn or berries, produce diminishes in value the minute it goes from the stalk or vine to the market. Driscoll's, a $3.5 billion provider of berry plants, is turning to emerging technologies, such as artificial intelligence (AI), machine learning (ML), the internet of things (IoT) and blockchain, to produce hardier plants and fortify its supply chain. "We're just scratching the surface on building an integrated data platform strategy that will take advantage of artificial intelligence and machine learning, both for R&D genetics and on the value chain of fruits as well as business operations," Driscoll's CIO Tom Cullen tells CIO.com. Driscoll's develops and leases strains of berry nursery plants -- strawberries, blueberries, blackberries and raspberries -- to growers around the world, from the Americas to New Zealand, China and Australia.

The purpose of this paper is to re-investigate the estimation of multiple factor models by relaxing the convention that the number of factors is small. We first obtain the collection of all possible factors and we provide a simultaneous test, security by security, of which factors are significant. Since the collection of risk factors selected for investigation is large and highly correlated, we use dimension reduction methods, including the Least Absolute Shrinkage and Selection Operator (LASSO) and prototype clustering, to perform the investigation. For comparison with the existing literature, we compare the multi-factor model's performance with the Fama-French 5-factor model. We find that both the Fama-French 5-factor and the multi-factor model are consistent with the behavior of "large-time scale" security returns. In a goodness-of-fit test comparing the Fama-French 5-factor with the multi-factor model, the multi-factor model has a substantially larger adjusted $R^{2}$. Robustness tests confirm that the multi-factor model provides a reasonable characterization of security returns.