The world was atwitter last week as President Trump crudely took North Korea to task over its nuclear program, a threat that has slowly but surely eclipsed the distractions of our imperialist wars in the Middle East. But according to tech mogul Elon Musk, humans face a far graver threat from something they use in their everyday lives and could be holding in their hands as they read these words: algorithmic artificial intelligence. Specifically, algorithmic AI that evolves into malevolent super-intelligent entities and seeks to end their meatbag parent species -- us. Late last week, Musk tweeted that AI is far more dangerous than North Korea, adding that he believes regulation will be necessary to contain the burgeoning technology. If you're not concerned about AI safety, you should be.

Militants firing from bombed-out buildings had ambushed a U.S.-backed militia on a rubble-strewn street in Raqqah, Islamic State's self-declared capital and one of its last urban strongholds. The militia was pinned down and their commander wanted the drone to take out the gunmen. The pilot studied the surveillance video streaming onto his screen. A captain, he instructed the staff sergeant at his side to set the drone's target sights and powered up a Hellfire missile under its wing. "Rifle," the pilot said and the missile soared away.

It's not news that the evolution of education technologies and models of transformed learning are moving at the speed of sound. "Machine Learning", (The Economist, July 22-28, 2017) jolted me into the certainty that--regardless of educators' embracing and meaningfully engaging technologies--the ecosystem will successfully evolve without them. This is about using new software to alter how learners and teachers best use their time. It is not about infusing technology into the usual way that schools do business. Artificial intelligence (AI) is helping design new ways of education: specifically, having machines learn about the student by analyzing data unleashed in the learning process.

For quick reminders and messages, it is a lot faster and more convenient to simply talk to your phone, rather than pull up an app and type on a keyboard. That's part of the reason Google has been updating Gboard for Android with voice support for more international languages, working with native speakers to train machine learning models. Today, Google announced that it's supporting an additional 20 languages and also adding English dialects for four African countries. This means language support for a total of 30 new international locations, mostly centered on the Indian subcontinent and Africa. The full list of languages is: Amharic, Armenian, Azerbaijani, Bengali, English (Ghana, Kenya, Nigeria, Tanzania), Georgian, Gujurati, Javanese, Kannada, Khmer, Lao, Latvian, Malayalam, Marathi, Nepali, Sinhala, Sundanese, Swahili, Tamil, Telugu and Urdu.

Among the tasks you can train a computer to perform is scanning the skies over the U.S. for the alarming number of surveillance and spy aircraft. The news web site BuzzFeed did just that, reporting this week that it employed a machine-learning algorithm to first recognize known spy planes, and then combine that model with a large set of flight-tracking data from a commercial web site. The AI project mapped thousands of surveillance flights operated by federal agencies over a four-month period, including a military contractor tracking terrorists in Africa that is also flying surveillance aircraft over U.S. cities, BuzzFeed reported. Flightradar24 gathers data from a network of ground-based receivers supplemented by Federal Aviation Administration receivers. The ground radars sweep up a flight data transmitted by aircraft transponders, including unique identifiers for each plane.

Digital technology innovations and advancements, and our adoption of them, have changed us. We are different consumers, employers and employees. We have become mobile, impatient and demanding. We demand immediate, accurate and real-time responses. We use our technology not just for reading historic events and news, but also for predicting our future turn while navigating at 60 MPH.

Making AI models at the University of Southern California (USC) Center for AI in Society does not involve a clean, sorted dataset. Sometimes it means interviewing homeless youth in Los Angeles to map human social networks. Sometimes it involves going to Uganda for better conservation of endangered species. "With AI, we are able to reach 70 percent of the youth population in the pilot, compared to about 25 percent in the standard techniques. So AI algorithms are able to reach far more youth in terms of spreading HIV information compared to traditional methods," said Milind Tambe, a professor at the USC Viterbi School of Engineering and cofounder of the Center for AI in Society.

Among the tasks you can train a computer to perform is scanning the skies over the U.S. for the alarming number of surveillance and spy aircraft. The news web site BuzzFeed did just that, reporting this week that it employed a machine-learning algorithm to first recognize known spy planes, and then combine that model with a large set of flight-tracking data from a commercial web site. The AI project mapped thousands of surveillance flights operated by federal agencies over a four-month period, including a military contractor tracking terrorists in Africa that is also flying surveillance aircraft over U.S. cities, BuzzFeed reported. Flightradar24 gathers data from a network of ground-based receivers supplemented by Federal Aviation Administration receivers. The ground radars sweep up a flight data transmitted by aircraft transponders, including unique identifiers for each plane. The aerial gumshoes then used an algorithm called Random Forest (referred to on Github as randomForest, Random Forests, random-forest and variations of those names).

Most data turns out to have a greater value than the sum of the parts. There's a story about a global courier firm that said it saw a large drop off in its monthly orders at some point in 2007, not too long before the bottom fell out of the global economy. Traditional economic forecasting did not see an issue, but had there been some visibility into trade finance data at that time it would have shown many contracts had been cancelled, affording us some warning of what was ahead. Macro-economic forecasters and statistical analysts know that trade data provides the most precise window into the global economy there is. Trade finance data has always been a notoriously opaque part in the supply chain, but we are now seeing end-to-end digitisation, as a multitude of banks and software providers test out trade/supply blockchains and other digital platforms.

Heino Gevers, Customer Experience Director at Mimecast MEA, explains customer experience is the way a company tracks and organises every interaction between a customer, and the organisation throughout the customer lifecycle. Customer experience is becoming a competitive advantage as the business-consumer relationship shifts, Nicholas O'Connor, Strategic Business Development Consultant at hi.guru, adds. CX, as it is often termed, makes use of data to drive strategic imperatives and build loyalty, he says. Certified Customer Experience Professional and consultant Julia Ahlfeldt adds it costs six to seven times more to acquire a new customer than it costs to keep an existing one. "If companies choose not to embrace CX, they run the risk of delivering negative experiences, which erode loyalty. Over time, these companies will gradually lose favor with customers, and their market share will diminish as consumers vote with their feet."