The beginning, or end, of every year is marked by an eruption of Top 10 lists. Permit me to start with my top pick, the annual Notre Dame Reilly Center Top 10 List of Ethical Dilemmas and Policy Issues in Science and Technology. Would you really want your car to do that? Forget about the prospect of your kids one day taking your keys away when you fail an eye or reflex test. And what happens if your car itself becomes a bit neurotic, consumed with your safety.

Pretty much all of the tech giants attend the vast Vegas expo - either to unveil new products or to clinch deals behind the scene. But in recent years it's been start-ups that have had many of the most eye-arresting and sensational reveals. There are more at this year's show than ever before, thanks in part to crowdfunding. They now have to convince retailers - hunting through the halls for the next bestsellers - that the promise of their concept videos has been delivered upon. Dozens of start-ups are also there thanks to help from governments and other national bodies - France, Israel, Ukraine and the Netherlands all have stands where they'll fly the flag for local talent.

Artificial intelligence has played a role in customer service for some time now, but it's only recently that its full potential for transforming the customer experience has come to light. Conversational commerce is redefining the role of messaging apps in customer engagement, while self-service tools continue to simplify the customer service process and shift the role of human customer service agents in the contact center. Here are six ways artificial intelligence is reshaping customer experiences of both the present and the future. Big data is a key player in targeted marketing practices, offering brands important insights into customer behavior. Artificial intelligence technology may interpret big data to identify customer browsing patterns, purchase history, recent access to customer devices, and most visited webpages.

This book serves as a comprehensive intermediate guide to programming in SQL using Python as a language. Every new programmer needs a reference guide to coding and programming as they learn the basics. The goal of this book is to allow for the reader to get a step by step, comprehensive guide to formulating and gaining new skills. In order to maintain and create a secure system, the importance of both security features to put in place, things to avoid and the basics of good communication with your system are three of the skills you should be able to master at an intermediate level by the end of this book. Within the pages of the book, I share with you the methods I have used to create and maintain websites both as I started my programming and coding journey--and I still use today.

Data science is fast becoming a critical skill for developers and managers across industries, and it looks like a lot of fun as well. But it's pretty complicated - there are a lot of engineering and analytical options to navigate, and it's hard to know if you're doing it right or where the bear traps lie. In this series we explore ways in to making sense of data science - understanding where it's needed and where it's not, and how to make it an asset for you, from people who've been there and done it. This InfoQ article is part of the series "Getting A Handle On Data Science" . You can subscribe to receive notifications via RSS. A lot of Machine Learning (ML) projects consist of fitting a (normally very complicated) function to a dataset with the objective of calculating a number like 1 or 0 (is it spam or not?) for classification problems or a set of numbers (e.g., weekly sales of a product) for regression ones.

The "willing suspension of disbelief" is the idea that we (the audience, readers, viewers, content consumers) are willing to suspend judgment about the implausibility of the narrative for the quality of our own enjoyment. We do it all the time. Two-dimensional video on our screens is smaller than life and flat and not in real time, but we ignore those facts and immerse ourselves in the stories as if they were real. We have also learned the "conventions" of each medium. While we watch a movie or a video, we don't yell to the characters on the screen "Duck!" or "Look out!" when something is about to happen to them.

A great example of vertical vs horizontal machine learning applications can be found in chat bots. There are some horizontal chat bot assistants that help you with any and all requests (viv.ai, Magic, and Awesome to name a few). It would seem obvious that building NLP and intelligent capabilities across all conceivable tasks and requests could be a long slow training slog of manual human validation. These companies are also at a heavy disadvantage to incumbent players tackling the horizontal assistant space.

Hospitals in Paris are trialling Big Data and machine learning systems designed to forecast admission rates – leading to more efficient deployment of resources and better patient outcomes. It's just one more way in which cutting-edge data science is being applied to real-world problems in healthcare, along with creating personalized medicines, fighting cancer and streamlining pharmaceutical trials. At four of the hospitals which make up the Assistance Publique-Hôpitaux de Paris (AP-HP), data from internal and external sources – including 10 years' worth of hospital admissions records has been crunched to come up with day and hour-level predictions of the number of patients expected through the doors. The core of the analytics work involves using time series analysis techniques – looking for ways in which patterns in the data can be used to predict the admission rates at different times. Machine learning is employed to determine which algorithms provide the best indicator of future trends, when they are fed data from the past.

Autonomous vehicles are already making profound choices about whose lives matter, according to experts, so we might want to pay attention. "Every time the car makes a complex manoeuvre, it is implicitly making trade-off in terms of risks to different parties," Iyad Rahwan, an MIT cognitive scientist, wrote in an email. The most well-known issues in AV ethics are trolly problems -- moral questions dating back to the era of trollies that ask whose lives should be sacrificed in an unavoidable crash. For instance, if a person falls onto the road in front of a fast-moving AV, and the car can either swerve into a traffic barrier, potentially killing the passenger, or go straight, potentially killing the pedestrian, what should it do? Rahwan and colleagues have studied what humans consider the moral action in no-win scenarios (you can judge your own cases at their crowd-sourced project, Moral Machine).

Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. It is a very simple idea that can result in accurate forecasts on a range of time series problems. In this tutorial, you will discover how to implement an autoregressive model for time series forecasting with Python. Autoregression Models for Time Series Forecasting With Python Photo by Umberto Salvagnin, some rights reserved. A regression model, such as linear regression, models an output value based on a linear combination of input values.