Imagine sending a text message to a friend. As your fingers tap the keypad, words and the occasional emoji appear on the screen. Perhaps you write, "I feel blessed to have such good friends:)" Every character conveys your intended meaning and emotion. But other information is hiding among your words, and companies eavesdropping on your conversations are eager to collect it. Every day, they use artificial intelligence to extract hidden meaning from your messages, such as whether you are depressed or diabetic.

The following editorial appeared in Sunday's Japan News-Yomiuri: Fake videos misusing artificial intelligence are spreading on the internet. Is the information coming from a credible source? It is important to be aware of them on a daily basis. A video of U.S. House of Representatives Speaker Nancy Pelosi looking drunk while giving a lecture was disseminated online in May. The video was deliberately slowed down, and it is not clear who posted it online.

Artificial intelligence, alongside proper training and education, can manage even the worst of security breaches into a positive outcome for airports and their users, says Kristina Dores, Chief, Aerodromes & Ground Aids at Namibia Civil Aviation Authority, and Brad Hayes, CTO at Circadence Corporation. However, the key question is when (not if) will organisations take the steps to prepare for the coming wave of digitisation? Highly-interconnected and increasingly-digitised systems are a necessary part of modern airport infrastructure. Furthermore, vulnerabilities at these interfaces – through personnel and digital systems alike – lead to an increased threat of intrusion and potentially catastrophic disruption. This problem is not one that we can simply train and hire our way out of as these systems and their attack surfaces do not scale linearly in complexity.

Walk into the Decathlon sporting goods store on Market Street in San Francisco and you will find yourself face to face with Tally. She is tall and slender, and has a winning smile--she smiles with her eyes. She is gentle and considerate: if you get in her way, she will quietly glide around you without complaining. She is extremely intelligent and highly efficient: as she moves up and down the aisles, she takes a real-time inventory of the products on the shelves and racks, checking which products are running low or out of stock, and whether they are labeled with the correct price. She can read RFID tags, but she can also use AI-powered image recognition to distinguish different products at a glance.

Anything that has sub-types can be presented as a tree.

On the face of it, NASA's newest probe sounds incredible. Known as Dragonfly, it is a dual-rotor quadcopter (technically an octocopter, even more technically an X8 octocopter); it's roughly the size of a compact car; it's completely autonomous; it's nuclear powered; and it will hover above the surface of Saturn's moon Titan. But Elizabeth Turtle, the mission's principle investigator at the Johns Hopkins Applied Physics Laboratory, insists that this is actually a pretty tame space probe, as these things go. "There's not a lot of new technology," she says. Quadcopters (even X8 octocopters) are for sale on Amazon these days.

Stocks inched up Tuesday, with the benchmark Nikkei 225 average closing above 22,000 for the first time in about five months. The Nikkei rose 13.03 points, or 0.06 percent, to end at 22,001.32, The last time the Nikkei finished above 22,000 was April 26. On Friday, the key market gauge jumped 228.68 points. The market was closed Monday for a national holiday.

Other money supply categories include M1, M2, and M3. In essence, each category is successively less liquid than the next with M1 representing the physical money supply, therefore being the most liquid and useful for cash transactions. By dividing M0 by M2, economists can determine the ratio of people in a national economy who rely on cash for payments. China's M0/M2 ratio is the third lowest, behind only the UK and Hong Kong, at 3.79 percent. By contrast, the U.S.'s is 21.92 percent, one of the highest in the world, indicating its citizens rely on cash 5.8 times more than the Chinese.

Voting and electing are, from a machine learning perspective, classification problems: The „algorithm" in our brain has to choose one from several available options as the correct one. The options are candidates in the case of elections or „YES/NO" in the case of voting (like in the direct democracy in Switzerland). In a democracy, there is not a single „classifier" (King) making the decisions but a large number of people. What is the benefit of this method? Why is democracy historically so successful? We might say that democracies are more stable because everybody is allowed to participate in the decision process and the result will represent the wishes of everybody. But there are many cases in history where the majority in a democratic country suppressed a minority. I personally don't believe in this theory. I rather think that in a democracy, the decisions tend to be much smarter than what can be achieved by a single king or a small group of leaders. It is the collective intelligence formed by the whole voting population which makes democracy superior to other systems of government. The method is also well known in machine learning under the term „ensemble methods".

Conversations with customers have become the need of the hour for businesses. Now we are witnessing a paradigm shift from mass-centered to granular, account-based approach. Banks and other financial institutions, who work closely with customers and rely heavily on customer relationships, have always leveraged technology to assist them. First, it was internet banking in the late 90s, then mobile banking when the smartphone revolution took over the world. Now, with the advent of AI and machine cognizance, conversational banking is on the rise. Conversational banking is nothing but communication between a bank and its customer through text, voice or visual interface. It adds that extra touch of personalization in customer relationships. Conversational banking, though highly effective, comes with the hardship of effective implementation given the sheer volume of customers banks serve (or any B2C business for that matter). That is why AI becomes extremely important in conversational banking.