It starts without warning--or rather, the warnings are there, but your ability to detect them exists only in hindsight. First you're sitting in the car with your son, then he tells you: "I cannot find my old self again." You think, well, teenagers say dramatic stuff like this all the time. Then he's refusing to do his homework, he's writing suicidal messages on the wall in black magic marker, he's trying to cut himself with a razor blade. You sit down with him; you two have a long talk. A week later, he runs home from a nighttime gathering at his friend's apartment, he's bursting through the front door, shouting about how his friends are trying to kill him. He spends the night crouching in his mother's old room, clutching a stuffed animal to his chest. He's 17 years old at this point, and you are his father, Dick Russell, a traveler, a former staff reporter for Sports Illustrated, but a father first and foremost.

This document is an invited chapter covering the specificities of ABC model choice, intended for the incoming Handbook of ABC by Sisson, Fan, and Beaumont (2017). Beyond exposing the potential pitfalls of ABC based posterior probabilities, the review emphasizes mostly the solution proposed by Pudlo et al. (2016) on the use of random forests for aggregating summary statistics and and for estimating the posterior probability of the most likely model via a secondary random fores.

This article was originally published on TechRepublic. Remember the famous scene in Stanley Kubrick's 1968 2001: A Space Odyssey, when Hal 9000--the intelligent-turned-malevolent computer--regresses to his "childhood" and sings "Daisy Bell" as he's decommissioned by astronaut Dave Bowman? Its inspiration was a real-life Bell Labs demonstration of speech synthesis on an IBM 704 mainframe in 1961, witnessed by Arthur C Clark, who later incorporated it into his 2001 novel and screenplay. Although Bell Labs' involvement in the field stretches back to the 1930s with Homer Dudley's keyboard-and-footpedal-driven Voder speech synthesis device, it's undoubtedly the classic Kubrick/Clarke movie that cemented the ideas of artificial intelligence (AI) and conversing with computers into the public mind. Depending on how old you are, we're now familiar with computerised voices, thanks to devices like Texas Instruments' popular 1978 Speak & Spell educational toy, Stephen Hawking's speech synthesiser (memorably sampled in the Pink Floyd song Keep Talking), GPS navigational systems in your car, and any number of public information and call handling systems. More recently, the combination of automatic speech recognition (ASR), natural-language understanding (NLU) and text-to-speech (TTS) has come to mainstream attention in virtual assistants such as Apple's Siri, Google Now, Microsoft's Cortana, and Amazon's Alexa. To get a handle on how speech technologies work, we clearly need to know something about the mechanics of human speech and the structure of language. When we speak, air from the lungs passes through the vocal tract to produce "voiced" or "unvoiced" sounds (depending on whether the vocal cords are vibrating or not) that may then be modulated by the tongue, teeth and lips.

After successfully launching a Facebook messenger chatbot in the UK and Ireland that takes customers' pizza orders, Domino's is now making the feature available stateside. Starting today, Domino's says customers with a "Pizza Profile" on the chain's website can place their orders via Messenger by communicating with a bot. Because at least pizza is a comfort when you think about how artificial intelligence will one day vanquish the human race, right? Customers can place and track their orders by clicking the message button on Domino's Facebook page or by searching for Domino's within the Messenger app. If you don't feel like using your words, you can also just send a pizza emoji to get the ball rolling.

We have grown up with poor voice recognition and error prone requests on our mobile devices but Amazon started a full 12 months before Google on developing a high-precision microphone and voice recognition system that is built into its marketplace ecosystem. You can order pizza, pay a credit card bill, order books, check your diary, as well as listen to music and news. You can also ask and use the IFTTT integration function to also link to many home smart appliances across many brands such as switch lights on, set and check home security, switch hot water and heating on or off and control fridges, cookers, TVs and many other things all by simple voice commands.

ON JUNE 1st 2009, an Air France airliner travelling from Rio de Janeiro to Paris flew into a mid-Atlantic storm. Ice began forming in the sensors used by the aircraft to measure its airspeed, depriving the autopilot of that vital data. So, by design, the machine switched itself off and ceded control to the pilots. Without knowing their speed, and with no horizon visible in a storm in the dead of night, the crew struggled to cope. Against all their training, they kept the plane's nose pointed upward, forcing it to lose speed and lift.

Japanese prime minister Shinzo Abe has unveiled a campaign to utilise emerging technologies, including drones and artificial intelligence, to increase productivity at construction sites by 20% by 2025. According to Japanese newspaper The Japan Times, Abe announced the plan at the inaugural meeting of a think tank tasked with formulating new growth strategy policies. The panel of government officials and industry experts is expected to announce details of the construction productivity strategy before the end of 2017. The government intends to ramp up the use of drones and AI to increase the efficiency of surveys on centrally funded infrastructure projects, such as tunnels, bridges and dams. Faced with an ageing population, Japan is already leading the world in advancing the use of autonomous vehicles, with construction drones set to be used to automate groundworks for the 2020 Olympic games.

Summary: What are the earliest seeds of artificial intelligence? To whom do we owe thanks for starting us down this path? Many modern researchers to be sure, but the earliest is Leonardo Torres of Spain, in about 1914. As data scientists it's very cool to be at the forefront in this age of techno-optimism. Since the awakening of the digital age calculated by economic researchers to have begun about 1994, a wave of increased productivity has been credited to computer-related innovations resulting in higher standards of living for many if not most.

The role of technology-fueled algorithms in shaping our society, and how to use them responsibly, is one of the topics I'll be exploring at the Next:Economy Summit in San Francisco, October 10-11. Some years ago, John Mattison, the chief medical information officer of Kaiser Permanente, the large integrated health provider, said to me, "The great question of the 21st century is going to be'Whose black box do you trust?'" Mattison was talking about the growing importance of algorithms in medicine, but his point, more broadly, was that we increasingly place our trust in systems whose methods for making decisions we do not understand. A lot of attention has been paid to the role of algorithms in shaping the experience of consumers. Much less attention has been paid to the role of algorithms in shaping the incentives for business decision-making. For example, there has been hand-wringing for years about how algorithms shape the news we see from Google or Facebook.

Artificial intelligence guru Robert Dale explains the benefits and shortcomings of natural language generation technology and advocates for disclosure of use of the software. Natural language generation, a field in artificial intelligence which automatically turns facts and statistics into coherent English and other languages, offers important advantages for finance and accounting, according to Robert Dale, a longtime expert in the technology. Since 2012, Dale has been CTO and chief strategy scientist at Arria NLG, based in London, and one of the first companies to offer automatic text generation. He is also co-author, with Arria's chief scientist Ehud Reiter, of the textbook, Building Natural Language Generation Systems, first published in 2000 and then again in 2006. In an interview with SearchFinancialApplications, Dale discussed NLG, its benefits for the office of the CFO and the future of artificial intelligence (AI).