The Hong Kong government is preparing to issue its maiden policy statement on the use of artificial intelligence in finance, according to people familiar with the matter, in a move that could catalyze the use of the technology in areas from trading to investment banking and cryptocurrencies. The city's Financial Services and Treasury Bureau plans to issue a framework of guidelines to touch on the ethical use of AI and general principles for applying the technology in the finance world, the people said, asking not to be identified discussing private information. Officials are still drafting the document while getting feedback from the industry, the people said. Details are still subject to change in the coming weeks, they added. While specifics remain unclear, the document is broadly intended to signal Hong Kong's support for AI, as governments around the world get to grips with the technology's potential.

Landslide susceptibility assessment (LSA) is of paramount importance in mitigating landslide risks. Recently, there has been a surge in the utilization of data-driven methods for predicting landslide susceptibility due to the growing availability of aerial and satellite data. Nonetheless, the rapid oscillations within the landslide-inducing environment (LIE), primarily due to significant changes in external triggers such as rainfall, pose difficulties for contemporary data-driven LSA methodologies to accommodate LIEs over diverse timespans. This study presents dynamic landslide susceptibility mapping that simply employs multiple predictive models for annual LSA. In practice, this will inevitably encounter small sample problems due to the limited number of landslide samples in certain years. Another concern arises owing to the majority of the existing LSA approaches train black-box models to fit distinct datasets, yet often failing in generalization and providing comprehensive explanations concerning the interactions between input features and predictions. Accordingly, we proposed to meta-learn representations with fast adaptation ability using a few samples and gradient updates; and apply SHAP for each model interpretation and landslide feature permutation. Additionally, we applied MT-InSAR for LSA result enhancement and validation. The chosen study area is Lantau Island, Hong Kong, where we conducted a comprehensive dynamic LSA spanning from 1992 to 2019. The model interpretation results demonstrate that the primary factors responsible for triggering landslides in Lantau Island are terrain slope and extreme rainfall. The results also indicate that the variation in landslide causes can be primarily attributed to extreme rainfall events, which result from global climate change, and the implementation of the Landslip Prevention and Mitigation Programme (LPMitP) by the Hong Kong government.

When it comes to Sub-Saharan Africa, the media always focuses on war, famine and disease. Little is known about the innovation and positive attributes stemming from the region. One such attribute, is the growth of computer science and artificial intelligence. Indeed, the field of AI has skyrocketed in developing nations with the advent of the home computer, but has recently found burgeoning roots, not in Silicon Valley, India or China, but in the bustling capital of Ethiopia. Thanks to a leading AI group in Hong Kong called OpenCog Foundation, funding from the Jeffrey Epstein VI Foundation based in New York, and the Hong Kong government, the AI lab in Sidist Killo, Ethiopia called Addis AI Lab, has become the computer science pioneer in Sub-Saharan Africa.

For years, a group of Chinese hackers known variously as Barium, Winnti, or APT41 has carried out a unique mix of sophisticated hacking activities that has puzzled the cybersecurity researchers tracking them. At times they appear focused on the usual state-sponsored espionage, believed to be working in the service of the Chinese Ministry of State Security. At other times their attacks looked more like traditional cybercrime. Now a set of federal indictments has called out those intruders by name, and cast their activities in a new light. Five Chinese hackers are accused of a sprawling scheme to break into the networks of hundreds of global companies in a broad range of industries, as well as think tanks, universities, foreign government agencies, and the accounts of Hong Kong government officials and pro-democracy activists.

Currently the trending concept behind autonomous vehicles is removing the human and focusing on the machine. But I have a different view. After 12 years at NASA researching autonomous systems for Mars, and seven years at Nissan leading work on autonomous vehicles in Silicon Valley, I believe that an autonomous system without people as a central component will be pretty much useless. As the Hong Kong government targets a 30 percent adoption of connected and autonomous vehicles (CAV), and begins testing autonomous technologies, it's crucial to take a human-centric perspective to reap the real rewards of this technology. Imagine you just bought your first autonomous vehicle.

HONG KONG – Hong Kong law enforcement authorities have access to artificial intelligence software that can match faces from video footage to police databases, but people familiar with the matter say it is unclear if the technology is being used to quell the pro-democracy protests. Police have been able to use the technology from the Sydney-based iOmniscient for at least three years, and engineers from the company have trained dozens of officers on how to use it, said the people, who asked not to be identified because the information isn't public. The software can scan footage, including from closed-circuit television, to match faces and license plates to a police database and pick out suspects in a crowd. In addition to tracking criminals, iOminiscient's artificial intelligence can be used for everything from finding lost children to managing traffic. In one training session after the protests began in June, the people said, officers asked how to automatically identify license plate numbers using dashboard cameras.

Artificial intelligence is being credited for helping Hong Kong customs officials increase seizures of fake goods sold online by about one-third in the first six months of this year, resulting in a haul of counterfeit items worth HK$1.96 million (US$247,000). A new supercomputer they began using last December scoured websites 24 hours a day and detected close to 2,000 of the 5,200 items seized by the Customs & Excise Department. Over the same period last year, officers netted 11,800 pieces of counterfeit goods worth HK$1.47 million. A source said the department might look into expanding the capacity of the computer, which gathers important information during investigations, but he stressed it would complement rather than replace manual enforcement work by customs officers. "The analytics tool saves us a lot of time screening online platforms manually," the source said.

Facial recognition technology is likely to be among innovations on the agenda when bankers, financial regulators and officials from across Asia gather in Hong Kong on Wednesday for a landmark summit. The high-powered meeting comes as the race to regulate the fintech (financial technology) revolution is intensifying amid fears that a regulatory "vacuum" could be exploited by money launderers, fraudsters and underground bankers whose activities threaten national, regional and international financial stability. Organisers of the summit to launch the Alliance for Financial Stability with Information Technology, also known as AFS-IT, say speakers and guests will include top-level representation across the banking, financial, technology and regulatory sectors as well as government officials from China, Hong Kong, Macau, the Philippines, Thailand, Cambodia, Myanmar, Vietnam and Singapore. A key focus will be the fostering of innovation in regulation technology, or regtech, a new field in which information technology is used to enhance regulation. Innovative fintech can be used and adapted to benefit both service providers and regulators, and it includes know-your-customer facial recognition technology recently installed across the ATM network of casino hub Macau as part of an ongoing crackdown on money laundering and capital flight from China.

Hong Kong police on Tuesday arrested 21 Uber drivers for illegal car-hiring as part of a clamp down against Uber's operations in the Asian financial city. The arrests marked the latest upset for the San Francisco-based technology company, which in March said it would help five convicted Uber drivers to appeal their court case in Hong Kong. Police said they began an undercover operation in May and on Tuesday arrested 20 men and one woman between the ages of 21 and 59 for illegally driving a car for hire and driving without third-party risk insurance. "I would like to stress that our law enforcement action is ongoing and we do not rule out further arrests," said Lau Tat-fai, a chief inspector of police in the Kowloon West district. "We would like to say to the operator of the mobile phone application, as a responsible organization, you need to ensure cars for hire are equipped with a permit as required by Hong Kong laws. This is a basic responsibility to passengers and (shows) respect for Hong Kong laws," Mr Lau said.