Warc's'Toolkit 2017', in association with Deloitte Digital, indicates that more than half of global CMOs said they expected the impact of Artificial Intelligence (AI) on marketing and communications to be greater than the impact of social media. AI, defined as the ability of computers to take on tasks that have previously required human intelligence to complete, such as speech recognition or interpreting data, will have a major impact on the marketing industry next year. David Tiltman, Warc's head of content, says, "2017 looks set to be the year that many brands take their first steps in artificial intelligence. Machine learning is already being applied to programmatic trading and we have seen brands such as Aviva in the UK improve its media efficiencies as a result. The next major application looks set to be chatbots, as marketers look to respond to consumers' take-up of messaging apps."

Called a murmuration, this defensive behavior is inspiring computer programming and other applications. Flocks of acrobatic starlings have long delighted observers, from Shakespeare to the present day. The birds--sometimes by the thousands--often seem to move as one, coursing through the air at breakneck speeds, turning on an instant. We recently published video of a beautiful starling swarm in the Netherlands. So many wings can be heard flapping in that video that it's easy to get why starling swarms are called murmurations.

Chatbots have captivated the tech world. Facebook, Google, Apple, Microsoft, Amazon, and IBM all heavily invest in conversational platforms. Thousands of developers, businesses, and brands build bots to engage users, but one fact is clear... According to Botanalytics, 40 per cent of a bot's users disengage after one interaction. With thousands of bots launching every month, what growth strategies distinguish successful from useless ones?

As BMW continues to weld a position for itself in the next generation of connected and autonomous car technology, it's signed up for one more partnership that focuses on the data side of the equation. Today, IBM announced that it would be working with BMW on R&D where Watson sensors and computing will be integrated into BMW cars to pick up car data and help with new systems aimed at vehicles running more efficiently and with more personalisation for specific drivers and passengers. To be clear, although there are a lot of efforts underway right now in the industry to built autonomous (self-driving) cars, this is not exactly about that. Rather it's more about figuring out the best way of building systems in vehicles to help make them work better, whether or not they are being driven by humans. "We don't want to replace humans!"

Do you know what is common between San Bernardino's shooting spree and the terrorist attacks in Paris last month? Jillennials, Jihadis who are Millennials. We mine data worldwide, a lot of it, a ton of it, every day and every night, and we do this for a living at PredictifyMe. We have partnership with the United Nations to protect school-goers in Pakistan, Nigeria, Sudan and Lebanon using our proprietary software SecureSim and Soothsayer . When the Paris attacks unfolded, we asked ourselves (and our database), how can we use data sciences to prevent something like this from ever happening again. Can we find out what factors influence an otherwise ordinary citizen to become radicalized?

As the global population ages, the number of cancer cases is going up. New cancer diagnoses are expected to rise by 70% in the next 2 decades, from 14 million to around 22 million, according to an estimate by the World Health Organization. Corporate giants like Google and IBM are already focusing on making breakthroughs in oncology, using advanced AI algorithms for early detection and personalized treatment of cancer. Google DeepMind announced a research partnership with the University College London Hospitals' radiotherapy department. DeepMind will test the use of machine learning to reduce the time it takes to plan radiotherapy treatment for hard-to-treat cancers of the head and neck.

It's a phrase that often pops up in discussions about the safety and ethics of artificial intelligence. How can scientists create AI with goals and values that align with those of the people it interacts with? Very simple robots with very constrained tasks do not need goals or values at all. Although the Roomba's designers know you want a clean floor, Roomba doesn't: it simply executes a procedure that the Roomba's designers predict will work--most of the time. If your kitten leaves a messy pile on the carpet, Roomba will dutifully smear it all over the living room.

Russian hackers have been implicated by the CIA and FBI in an audacious effort to sway voters in the recent U.S. presidential election in the direction of Donald Trump. Like other key events in U.S. history, such as Pearl Harbor or 9/11, the revelation of the Russian cyber intrusion is a wake-up call. It signals that a new "code war" is underway through the weaponization of information. The irony can't be missed, of course, that the CIA, which itself sought to influence democratic elections around the world from the earliest days of the Cold War, is calling out the Russians. Former CIA director Bill Colby once regaled me with tales of his years as a young operative in Italy, paying off journalists and channeling laundered funds to the Christian Democrats in elections during the 1950s to (successfully) defeat the Communists at the polls.

I hope you enjoy them, and it would be great if you would leave brief reviews of these books in the comments below – I'm sure all the authors would appreciate your comments and shares. About the Author Lee Baker is an award-winning software creator with a passion for turning data into a story. A proud Yorkshireman, he now lives by the sparkling shores of the East Coast of Scotland. Physicist, statistician and programmer, child of the flower-power psychedelic '60s, it's amazing he turned out so normal! Turning his back on a promising academic career to do something more satisfying, as the CEO and co-founder of Chi-Squared Innovations he now works double the hours for half the pay and 10 times the stress - but 100 times the fun! He also wanted to be rich, famous and good looking.

In this work, we study the use of logistic regression in manufacturing failures detection. As a data set for the analysis, we used the data from Kaggle competition Bosch Production Line Performance. We considered the use of machine learning, linear and Bayesian models. For machine learning approach, we analyzed XGBoost tree based classifier to obtain high scored classification. Using the generalized linear model for logistic regression makes it possible to analyze the influence of the factors under study. The Bayesian approach for logistic regression gives the statistical distribution for the parameters of the model. It can be useful in the probabilistic analysis, e.g. risk assessment.