Artificial intelligence that reads and responds to our emotions is the killer app of the digital economy. It will make customers and employees happier--as long as it learns to respect our boundaries. When psychologist Dr. Paul Ekman visited the Fore tribe in the highlands of Papua New Guinea in 1967, he probably didn't imagine that his work would become the foundation for some of the latest developments in artificial intelligence (AI). After studying the tribe, which was still living in the preliterate state it had been in since the Stone Age, Ekman believed he had found the blueprint for a set of universal human emotions and related expressions that crossed cultures and were present in all humans. A decade later he created the Facial Action Coding System, a comprehensive tool for objectively measuring facial movement.

The night before his newest poker competition was set to begin, Carnegie Mellon's Tuomas Sandholm and his PhD student Noam Brown sat down to play a little No Limit Texas Hold'em against the main competition: the artificial intelligence program they designed called "Libratus." "I was totally wrecked," Sandholm told The Washington Post. But he is not a serious poker player, so that's not such a big achievement. For the past 13 days, however, Libratus has been facing off against four world-champion poker players in a Pittsburgh casino. If it can beat them like it beat Sandholm, it would be an enormous breakthrough.

How do you make a robot toy that's both interesting and affordable? It's a hard problem: Making an interesting robot means giving it intelligence and creative autonomy, and giving a robot intelligence and creative autonomy is generally not compatible with it also being cheap. At CES a few weeks ago, we were introduced to Bots_Alive, a small company of roboticists who have managed to develop a robotic critter with a carefully thought-out animal-like personality. And by hacking an existing robot toy and using your phone as a brain, they're ready to sell it to you for 35 bucks. Bots_Alive is, essentially, selling a replacement brain for Hexbug Spider robots.

Instead of 1-to-1 matching, where the task is to verify if you are who you say you are, this requires the harder 1-to-N matching, where we have to check if you're any one of N persons. Here, N is over 10,000. This also has to have very high accuracy, given that this is a security-critical application.

I found these two papers – in of all places the presentation which Emil Kirkegaard and John Fuerst are presenting in London this weekend, which they claim is preventing them from responding to the can of worms they have opened by publishing a large, non-anonymized database of OKCupid dating profiles. This seems like it may become an important case in research ethics and data privacy. You may want to look into it. I recommend starting with this post by Oliver Keyes, but Vox, Vice and Thomas Lumley have all picked up the story. At any rate, the culprits cite these two papers that look quite good, and the second is the lead in to a whole special issue on cumulative science from Psychological Methods in 2009.

Frustrated with the impact of technology advances on infrastructure upgrades and IT budgets, a growing number of organizations are opting for cloud computing investments instead.

SAP's vision is to help the world run better and improve people's lives. As the cloud company powered by SAP HANA, SAP is a market leader in enterprise application software, helping companies of all sizes and industries run better. SAP empowers people and organizations to work together more efficiently and use business insight more effectively. SAP applications and services enable our customers to operate profitably, adapt continuously, and grow sustainably. At SAP, we believe in the power of collaboration and empower our employees to perform at their best in an environment that encourages free and open expression of ideas.

Nowadays, it is quite clear that Chatbots are much more than just a trend. More and more companies offer a chatbot as part of their variety of interfaces. However, as chatbots become a common practice, the need for smarter bots arises. Smart bots can do much more than the simple chatbots. Powered by advanced machine learning capabilities, such as image analysis, NLP and text analytics, these smart bots can understand concepts in a sentence, identify objects within an image and extract entities and sentiment in a given text.

"The industry will continue to focus on refining systems, applications, software, security and network infrastructure to meet their needs. Machine learning is the megatrend: its application and influence, particularly on our mobiles, will be improving all parts of our lives in 2017," he said. So begins Deloitte's annual global TMT (Technology, Media, and Telecommunications) report, that since its inception in 2001 has reached an 87% prediction accuracy rate. The report is long but makes for interesting reading. Deloitte Australia forecasts a year that will see further significant breakthroughs in machine learning, indoor GPS navigation, safer travel in motor cars, more cyber mischief and a growing use of biometric security.

But DevOps, which refers to the increased communication and collaboration between development and IT operations, is an ever-changing, sometimes complicated term. While "dev" and "ops" used to be siloed into separate philosophies, practices, tools, and work flows, they're merging into one. Though the basics aren't exactly new, the DevOps world is still trying to figure out how it will evolve and integrate into already established infrastructures. Whether you head a company that relies heavily on DevOps or you're just now dipping your toes into the DevOps pond, there's plenty to learn--because this movement and culture are anything but set in stone. To get a better feel for what's in store for DevOps in 2017, we reached out to the pros. Read on for challenges and changes you may encounter in the coming year. How has DevOps changed the IT landscape in the last few years? There are increasing signs of improved collaboration between Dev and Ops teams to work on a shared goal, which is the continuous delivery of high-quality applications to customers, employees, and partners.