Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Halong Bay, then head up to the highlands of Sapa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vien while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.
A recent study showed that over 90% of security operating centres are now implementing or considering the use of AI and machine learning to detect and defend against digital threats. What is the traditional method for threat detection, what has AI and ML allowed, and how is the hardware world reacting to threats? Since their introduction, computers have played a key role in modern life, providing services such as internet access, online banking, message exchange, and remote work. However, the transmission of sensitive information along with the processing capabilities of any single computer has also resulted in the development of malware by cybercriminals. These programs fall under several categories, including viruses, trojans, and worms, all of which perform different tasks. Of these, their exact function can be separated further; some malware works to destroy a system while others may steal sensitive information.
Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Ha Long Bay, then head up to the highlands of Sa Pa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vieng while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.
Artificial intelligence (AI) applications have attracted considerable ethical attention for good reasons. Although AI models might advance human welfare in unprecedented ways, progress will not occur without substantial risks. This article considers 3 such risks: system malfunctions, privacy protections, and consent to data repurposing. To meet these challenges, traditional risk managers will likely need to collaborate intensively with computer scientists, bioinformaticists, information technologists, and data privacy and security experts. This essay will speculate on the degree to which these AI risks might be embraced or dismissed by risk management.
Over the last year, we saw a greater shift towards automation and AI applications to streamline insurance, including increased usage of augmented reality to support activities ranging from warning of risks, explaining insurance plans, estimating damages and increasing brand awareness. We also saw insurers starting to explore greater use of blockchain, the tech behind cryptocurrencies, to better support operations. With this came a greater emphasis on cybersecurity, with the expectation for more proactive and preventative measures. As we enter the next decade, we'll continue to see unprecedented growth in innovation in the Insurtech space, which has set up the industry for more market advancements in an increasingly complex environment. The Canadian insurance industry has been largely inert and less agile in the past, and it's this environment where Insurtech has made its mark.
The entire world is going cashless and banking activities and services seem to have moved online. Most customers perform their banking activities by adopting online services. Conversational AI is playing a significant role in attending to bank-related tasks and enabling the smooth functioning of the banks despite Covid constraints. Chatbot acts as a friendly banking assistant and enhances the overall financial services regime. Conversational AI in the financial sector usually deals with confidential user data including credit/ debit cards, bank accounts, sensitive personally identified information, and social security numbers.
On a bright Tuesday afternoon in Paris last fall, Alex Karp was doing tai chi in the Luxembourg Gardens. He wore blue Nike sweatpants, a blue polo shirt, orange socks, charcoal-gray sneakers and white-framed sunglasses with red accents that inevitably drew attention to his most distinctive feature, a tangle of salt-and-pepper hair rising skyward from his head. Under a canopy of chestnut trees, Karp executed a series of elegant tai chi and qigong moves, shifting the pebbles and dirt gently under his feet as he twisted and turned. A group of teenagers watched in amusement. After 10 minutes or so, Karp walked to a nearby bench, where one of his bodyguards had placed a cooler and what looked like an instrument case. The cooler held several bottles of the nonalcoholic German beer that Karp drinks (he would crack one open on the way out of the park). The case contained a wooden sword, which he needed for the next part of his routine. "I brought a real sword the last time I was here, but the police stopped me," he said matter of factly as he began slashing the air with the sword. Those gendarmes evidently didn't know that Karp, far from being a public menace, was the chief executive of an American company whose software has been deployed on behalf of public safety in France. The company, Palantir Technologies, is named after the seeing stones in J.R.R. Tolkien's "The Lord of the Rings." Its two primary software programs, Gotham and Foundry, gather and process vast quantities of data in order to identify connections, patterns and trends that might elude human analysts. The stated goal of all this "data integration" is to help organizations make better decisions, and many of Palantir's customers consider its technology to be transformative. Karp claims a loftier ambition, however. "We built our company to support the West," he says. To that end, Palantir says it does not do business in countries that it considers adversarial to the U.S. and its allies, namely China and Russia. In the company's early days, Palantir employees, invoking Tolkien, described their mission as "saving the shire." The brainchild of Karp's friend and law-school classmate Peter Thiel, Palantir was founded in 2003. It was seeded in part by In-Q-Tel, the C.I.A.'s venture-capital arm, and the C.I.A. remains a client. Palantir's technology is rumored to have been used to track down Osama bin Laden -- a claim that has never been verified but one that has conferred an enduring mystique on the company. These days, Palantir is used for counterterrorism by a number of Western governments.
Building innovative products and services that create a competitive advantage is undoubtedly a strategic priority for most company boards across Australia. So why are less than one-third of senior technology executives in Australia and New Zealand who responded to the 2020 State of the CIO survey spending time on driving business innovation in their current roles? Only 27 per cent of respondents here and across the Tasman, and 32 per cent across the Asia-Pacific region - according to the survey - indicated that this was part of their remit. But it's an activity that more than half (53 per cent) indicated that they would spend more time on in the next three years. What's even more surprising is that 53 per cent of A/NZ respondents said that their teams were not tasked with creating new revenue from the development of new products and services with the remainder (47 per cent) having this responsibility.
In the more advanced consumer goods and services economies, the personal data of billions of people is the most precious of all digital fuels. An entire industry is emerging around the concept that data is the most precious asset in any enterprise, in any industry. Economists are working to determine how to value personal data. Its immense value is reflected in the soaring stock values and astronomical cash flows and profits of companies that monopolize and leverage data. Personal data is a uniquely magical economic asset.
There is a fresh wave of disruption post COVID-19. Banks and financial institutions are adapting digital transformation at a blazing pace, this is a good and a progressive sign for us as this opens doors to the much awaited advancements in the financial sector. Lets just say – now the digital revolution has truly begun. The COVID-19 crisis has triggered customers to adopt digital interaction across segments. Nowadays branch loving customers are also using digital platforms to interact with their banks or NBFCs (Non-Banking Financial Companies) – this routine may become a trend in the future.