IBM is hoping to create a new voice assistant for the business world -- and before Amazon can create one first. At its Think conference in Las Vegas, IBM on Tuesday took the wraps off Watson Assistant, a virtual helper it's been developing with its customers for over a year. Don't expect to start saying, "Watson, what's the weather?" or "Watson, play They Might be Giants" to an IBM-branded speaker anytime soon. Instead, Watson Assistant will function as the behind-the-scenes brains for a variety of new digital helpers made by a variety of businesses for your home and in stores, airports, hotels and cars. For example, Watson Assistant is already in use at Munich Airport to power a robot that can tell you directions and gate information.

Recommender systems (RSs) provide an effective way of alleviating the information overload problem by selecting personalized items for different users. Latent factors based collaborative filtering (CF) has become the popular approaches for RSs due to its accuracy and scalability. Recently, online social networks and user-generated content provide diverse sources for recommendation beyond ratings. Although {\em social matrix factorization} (Social MF) and {\em topic matrix factorization} (Topic MF) successfully exploit social relations and item reviews, respectively, both of them ignore some useful information. In this paper, we investigate the effective data fusion by combining the aforementioned approaches. First, we propose a novel model {\em \mbox{MR3}} to jointly model three sources of information (i.e., ratings, item reviews, and social relations) effectively for rating prediction by aligning the latent factors and hidden topics. Second, we incorporate the implicit feedback from ratings into the proposed model to enhance its capability and to demonstrate its flexibility. We achieve more accurate rating prediction on real-life datasets over various state-of-the-art methods. Furthermore, we measure the contribution from each of the three data sources and the impact of implicit feedback from ratings, followed by the sensitivity analysis of hyperparameters. Empirical studies demonstrate the effectiveness and efficacy of our proposed model and its extension.

As we move into another new year there are once again a new set of predictions, hopes and concerns as to the direction of digital marketing over the next twelve months and beyond. There are so many exciting developments set to take place and I'm really looking forward to seeing how these take hold in 2018. One of the interesting areas I've observed across many trends is the recurrence of two themes: artificial intelligence (AI) and machine learning. These two closely related subjects seem to be taking hold across a number of areas, including marketing automation, digital creative, personalization and marketing technology. However, it's the influence of AI and machine learning on the future of search that I'd like to explore in some detail in this article and the potential implications on business and marketing.

It's another step in the march toward advice that erodes investors' needs for human help: A robo advisor focused on serving the high-net-worth client, powered by artificial intelligence and designed to automate their specific tax management concerns. Meeting the complicated needs of the wealthy requires a deep knowledge of tax rules and regulations says Hedgeable CEO Mike Kane. "Technology and AI systems can interpret and learn from these rules better than humans can, without our emotional biases." Doubling down on its embrace of Asian themes, Hedgeable's newest offering in its robo platform is a feature called'Tax Samurai,' run by an AI bot called'Katana.' For 30 basis points, it will work for client accounts with a minimum of $1 million to analyze their securities, aggregate all of their financial data, create tax efficient transfers, apply automated downside protection on any current holdings, and perform tax efficient trading and tax-loss harvesting.

Since Apple developed Siri there have been great strides made in the science of voice recognition. Will we soon be throwing away our mice and keyboards and simply talking to our computers? Or will the problems I have with Alexa continue to haunt voice recognition? My wife and I are like all married couples at breakfast. We do not speak to each other.

That's fine, as far as it goes. But it doesn't rule out the possibility that digital assistants think human beings are a joke. Nor that Alexa is laughing at jokes other digital assistants may have just cracked. In a society as technologically out of control as this one, anything is possible. In recent months, thousands of people have written to me (mostly by postcards, often filled to their edges) about an epidemic of belly laughs directed at them by their household appliances.

Mike Chen was working on a health care start-up, he and his colleagues had one of those light bulb moments regarding digital assistance. "There should be something where you can just text it, and it just, like, does it for you," he said. Three years later, his remote personal-assistant company, Magic, has employees in the United States and the Philippines. Its promise is bold: to do "anything" for customers who send requests over text or email, Mr. Chen said, 24 hours a day and 365 days a year. Fin, another new virtual personal-assistant company, is the brainchild of Sam Lessin and Andrew Kortina, a founder of the popular mobile payment service Venmo.

Integrating a voice or chatbot interface into a product used to require a Natural Language Understanding (NLU) cloud service. Today, we are open sourcing Snips NLU, a Private by Design, GDPR compliant NLU engine. It can run on the Edge or on a server, with minimal footprint, while performing as good or better than cloud solutions. From the 60 million messages Facebook bots process every day, to the tens of millions of users now talking to an Alexa or Google-powered device, natural language has become a preferred mode of interaction between people and machines. A new skill is being added to the Amazon Alexa skill store every 90 minutes, making voice assistants grow faster than smartphone app stores did.

Supply chains are hugely important in our world of physical goods. Companies invest a lot of money and effort to continually optimize and improve them, and that's not likely to ever stop. Save 5% on transportation costs? As artificial intelligence begins to reshape our digital world via AI-infused goods, services, and processes, it will require its own supply chain: mind-boggling quantities of data. Mountains of information must be continually gathered, processed, refined, and reassembled to produce the desired intelligence and decision-making.

Super portability and easy access to AI assistants make these wireless headphones must-haves on your next trip. And the design is kooky. But you won't find better Bluetooth chops. The W1 wireless chip maintains a rock-solid connection to minimize dropouts, and the battery delivers five hours of listening before you have to pop them into the case for a charge. Want to hear some SZA? Double-tap either bud and ask Siri to cue it up.