Indeed, in-person communication and touch and feel of the products in stores have not been topped by any achievements of e-commerce yet. And just like AI was able to significantly enhance the online experience with sophisticated recommendations algorithms and chatbots, there is a place for it in the physical world as well. Robotics powered by advanced NLP capabilities could be the next step in retail that will bring online and offline shopping experience much closer. In fact, the natural language processing market's size is estimated to grow from 7.63 billion in 2016 to 16.07 billion by 2021, at a CAGR of over 16%.

With all the talk here at Microsoft's Ignite conference around the cloud, office productivity and collaboration (and all that goes with that), CEO Satya Nadella took the keynote stage yesterday afternoon to discuss what he sees as the next horizon of digital transformation: artificial intelligence. This, to be sure, is not about AI for the sake of AI. "We don't want to pursue AI to beat humans at games," he declared with a winking swipe at IBM's Watson supercomputer, which won a Jeopardy Tournament, and Google's AlphaGo, which defeated a world champion at the game of Go. "We want to empower people with the tools of AI so they can build their own solutions." Microsoft's approach to AI, Nadella went on, is about infusing every application with intelligence. He noted that prior to the invention of the printing press with moveable type, there were but 13,000 books in the world. A few years later, there were 12 million books.

Is the Internet of Things the world's most confusing tech trend? On the one hand, we're told it's going to be epic, and soon – all predictions are either in tens of billions (of connected devices) and trillions (of dollars of economic value to be created). On the other hand, the dominant feeling expressed by end users (including at this year's CES show, arguably the bellwether of the industry) is essentially "meh" – right now the IoT feels like an avalanche of new connected products, many of which seem to solve trivial, "first world" problems: expensive gadgets that resolutely fall in the "nice to have" category, rather than "must have". And, for all the talk about a mega tech trend, things seem to be moving at the speed of molasses, with little discernible progress year on year. Part of the problem is perhaps one of semantics. While gadgets are indeed part of the category (and quite often very large markets onto themselves), the Internet of Things (which we define as any "connected hardware" other than desktops, laptops and smartphones) is a much broader, and deeper, trend that cuts across both the consumer, enterprise and industrial spaces.

Artificial intelligence (AI) isn't new but the rise of mobile and cloud computing, combined with big data and cheap computing power, is driving a resurgence. Convergent technologies mean AI is finding new uses in financial services. AI will be used in "every single segment of financial services", predicts Christophe Chazot, group head of innovation, HSBC. "The software is getting more intelligent in a human sense, mimicking human reasoning." The technology can help wealth advisors, back office staff and operations, traders and corporate finance teams.

This reference is a part of a new series of DSC articles, offering selected tutorials on subjects such as deep learning, machine learning, data science, deep data science, artificial intelligence, Internet of Things, algorithms, and related topics. It is designed for the busy reader who does not have a lot of time digging into long lists of advanced publications.

But if, as they say in this electoral season, you're looking to "grow your base," exercising emotional intelligence -- expressing empathy, checking your emotions in a bid to avoid conflict, and investing in personal relationships -- is a strategy that beats narcissism over the long term. A new exploration of how we make friends and influence people rigorously measured the emergence of popularity in small groups -- first-year college students organized into 15 study groups of about 20 in Poland. In the first week of their assignment to a group and then again three months later, 170 of the freshmen named the person or people they most liked in their group. Upon recruitment into the study, each participant completed standard inventories assessing their narcissistic personality traits and gauging their emotional intelligence. The findings: When a group of strangers is thrown together, individuals who score high on narcissism enjoy an early surge of admiration, recognition and friendship among their peers.

We consider a supervised machine learning scenario where labels are provided by a heterogeneous set of teachers, some of which are mediocre, incompetent, or perhaps even malicious. We present an algorithm, built on the SVM framework, that explicitly attempts to cope with low-quality and malicious teachers by decreasing their influence on the learning process. Our algorithm does not receive any prior information on the teachers, nor does it resort to repeated labeling (where each example is labeled by multiple teachers). We provide a theoretical analysis of our algorithm and demonstrate its merits empirically. Finally, we present a second algorithm with promising empirical results but without a formal analysis.

Last March, a computer built by a team of Google engineers beat one of the world's top players at the ancient game of Go. The match between AlphaGo and Korean grandmaster Lee Sedol was so exhilarating, so upsetting, and so unexpectedly powerful, we turned it into a cover story for the magazine. On a Friday in late April, we were about an hour away from sending this story to the printer when I got an email. According to the email, Lee had won all five matches--and all against top competition--since his loss to AlphaGo. Even as it surpasses human talents, AI can also pull humans to new heights--a theme that ran through our magazine story.

While Google Allo is still fresh off the starting block, it could become the most significant chatbot messaging platform ever. Of course, for now, it does not even allow third-party participation. It's fairly limited, and it has an uphill climb if it is going to replace WhatsApp or Messenger on your phone. Yet, there are hopeful signs. The app already uses a Smart Reply feature that can parse out requests.

Artificial intelligence (AI) has made its way into many aspects of our lives – even into toys for kids like Anki's Cozmo, which resembles a roboticized Ewok. But as things go, AI isn't just for devices, it's made and continues to make it's way into e-commerce and is out there working to determine what to sell to you, how you shop and ensure you have a good shopping experience. According to Gartner by 2020, 85% of customer interactions will be managed without a human and at the close of 2018, customer digital assistants will recognize customers by face and voice across channels. Investment-wise, in 2014 there were more than 300 million in venture capital invested in AI startups according to Bloomberg. Brands are on board and are using AI to build smarter platforms they hope will create a better online shopping experience for the consumer.