There are over 1 billion people currently in retirement. New types of financial institutions are evolving to satisfy the needs of the aging population. Investment banks, pension funds, and insurance companies are developing new business models, and are using AI to improve the quality of the analytics used to formulate them. In the near future, the synergy between innovative AI and wealth management will lead to the creation of a new financial institutions optimized for the aging population and age-friendly Longevity banks will make banking easier and safer for seniors. Over 150 financial companies are already developing innovative WealthTech and AgeTech products and services and AI is central to the process.

It is easy to understand who is responsible for airline safety. Although Artificial Intelligence (AI) is a new phenomenon, the structure of responsible parties is very similar to air traffic control. Defining who is in charge of artificial intelligence has prompted much discussion. Experts agree that legislation lays the foundation for the ethical use of AI. In regulation, AI should be seen like any other automated system.

We've scoped out these real-world AI use cases so we could detail how artificial intelligence has been a game-changer for FinTech. Few verticals are such a perfect match for the improved capabilities brought by the AI revolution like the financial sector. Traditional financial services have always struggled with massive volumes of records that need to be handled with maximum accuracy. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia. However, before the advent of AI and the rise of Fintech companies, very few giants of this industry had the bandwidth to deal with the inherently quantitative nature of this world.

The past 20 years have seen remarkable advances in the mining industry, particularly in mineral exploration technologies with vast volumes of data generated from geologic, geophysical, geochemical, satellite and other surveying techniques. However, the abundance of data has not necessarily translated into the discovery of new deposits, according to Colin Barnett, co-founder of BW Mining, a Boulder, Colorado-based data mining and mineral exploration company. "One of the problems we're facing in exploration is the huge increase in the amounts of data we have to look at," said Barnett, in his presentation at the Managing and exploring big data through artificial intelligence and machine learning session at the recent PDAC 2020 convention in Toronto. "And although it's high-quality data, the sheer volume is becoming almost overwhelming for human interpreters, and so we need help in getting to the bottom of it." By integrating hundreds or even thousands of interdependent layers of data, with each layer making its own statistically determined contribution, machine learning offers a solution to the problem of tackling the massive amounts of data generated, and a powerful new tool in the search for mineral deposits. But, in an interview with The Northern Miner, he cautioned that to fully exploit the potential of machine learning in mineral exploration, "prospectors will still need to devote considerable time and effort to the preparation of data before machine learning techniques can add value for companies."

Following D-Wave's announcement of Leap 2, a new version of its quantum cloud service for building and deploying quantum computing applications, VentureBeat had the opportunity to sit down with Murray Thom, D-Wave's VP of software and cloud services. We naturally talked about Leap 2, including the improvements the company hopes it will bring for businesses and developers. But we also discussed the business applications D-Wave has already seen to date. Quantum computing leverages qubits to perform computations that would be much more difficult, or simply not feasible, for a classical computer. Based in Burnaby, Canada, D-Wave was the first company to sell commercial quantum computers, which are built to use quantum annealing.

As governments and health care agencies work to stop the spread of Covid-19 and to treat those who are infected, manufacturers in more than a dozen industries are struggling to manage the epidemic's growing impact on their supply chains. Unfortunately, many are facing a supply crisis that stems from weaknesses in their sourcing strategies that could have been corrected years ago. Just how extensive the crisis is can be seen in data released by Resilinc, a supply-chain-mapping and risk-monitoring company, which shows the number of sites of industries located in the quarantined areas of China, South Korea, and Italy, and the number of items sourced from the quarantined regions of China. After the March 2011 earthquake and tsunami in Fukushima, Japan, many multinationals learned painful lessons about the hidden weaknesses in their supply chains -- weaknesses that resulted in loss of revenue, and in some cases, market cap. While most companies could quickly assess the impacts that Fukushima had on their direct suppliers, they were blindsided by the impacts on second- and third-tier suppliers in the affected region.

Since the first report of coronavirus (COVID-19) in Wuhan, China, it has spread to at least 100 other countries. As China initiated its response to the virus, it leaned on its strong technology sector and specifically artificial intelligence (AI), data science, and technology to track and fight the pandemic while tech leaders, including Alibaba, Baidu, Huawei and more accelerated their company's healthcare initiatives. As a result, tech startups are integrally involved with clinicians, academics, and government entities around the world to activate technology as the virus continues to spread to many other countries. Here are 10 ways artificial intelligence, data science, and technology are being used to manage and fight COVID-19. The better we can track the virus, the better we can fight it.

The military has its eye on artificial intelligence solutions to everything from data analysis to surveillance, maintenance and medical care, but before the Defense Department moves full steam ahead into an AI future, they're laying out some ethical principles to live by. "The United States, together with our allies and partners, must accelerate the adoption of AI and lead in its national security applications to maintain our strategic position, prevail on future battlefields, and safeguard the rules-based international order," said Esper wrote. "AI technology will change much about the battlefield of the future, but nothing will change America's steadfast commitment to responsible and lawful behavior." The list is the result of a 15-month study by the Defense Innovation Board, which is made up of academics and executives in tech and business, who presented their proposed principles in a public forum at Georgetown University in October. According to Esper's Monday memo, the Pentagon pledges that its AI efforts will be: 1) Responsible, 2) Equitable, 3) Traceable, 4) Reliable and 5) Governable.

Reporters Without Borders has found a radical new platform for distributing banned journalism in some of the world's most repressive countries: Minecraft. The advocacy group has opened a new virtual space on a dedicated server for the popular video game called'The Uncensored Library,' accessible to any of Minecraft's 145 million monthly players. Inspired by the neoclassical architecture of ancient Rome and Greece, the library will be filled with books containing the text of news stories that have been censored in their countries of origin. To begin with, the library will be stocked with stories from five countries that rank near the bottom of Reporters Without Borders' World Press Freedom Index, including Egypt, Mexico, Russia, Saudi Arabia, and Vietnam. The stories will be published in English and whichever language they were originally written in.