There's no doubt that 2017 was an exciting year for Intelligent Virtual Assistants (IVAs) and artificial intelligence. We conducted research showing that consumers' comfort with automated technology is increasing, and most are willing to try out new methods for resolving customer service issues. We also saw how the introduction and growth of new customer care channels such as social media have led to new challenges for enterprises looking to provide a consistent, omnichannel experience for their customers. And, finally, the integration of technology such as voice biometrics has increased the overall security of IVAs and expanded what they can be used to accomplish. Now that we're into a new year, we want to look ahead to what 2018 has in store for IVAs.

Jefferson Graham previews the 2018 Consumer Electronics Show in Las Vegas, where new smart home products using technology from Google, Amazon and Apple will be unveiled. The annual consumer electronics show has been dominated by Asian tech giants Samsung, LG and Sony in recent years, along with a trade show floor featuring thousands of startups hoping lightning strikes with some Las Vegas-style luck. What you historically don't see at CES are the U.S.-based tech giants Apple, Amazon or Google, which tend to show off their new products at their own heavily produced media events later in the year. Google looks to make a big splash at the 2018 Consumer Electronics Show, touting the Google Assistant. But CES 2018, which kicks off with events Sunday, will have a big presence from Google as it continues its push to take on Amazon's Echo connected speaker.

Apple TV has grown up a lot since its iTV days. It's not just for iTunes rentals anymore--Apple TV handles just about anything we watch, from House of Cards to Game of Thrones and Major League Baseball games, and now that includes 4K content. Since Apple opened up its tiny streaming box to developers, it's gone from fun to indispensable. With an extensive library of apps, Siri support, and a drop-dead simple interface, Apple TV is one of the underrated players in Apple's lineup. Just like all those years ago, it's still the device that "completes the story" of Apple's entertainment ecosystem, and even without some of the bells and whistles of its competitors, Apple TV is still one of the best streaming boxes you can buy--from SD to HD to brilliant 4K.

The judge said 16 of Taylor's two dozen victims from New York to Atlanta lost from several hundred dollars to more than $50,000 after encountering his "quest for money, respect, admiration and control." She said some victims, who lost a total of more than $290,000, were left financially ruined while others had credit ratings ruined or were left suffering from fear, depression, anxiety and concern for their personal safety.

Artificial intelligence (AI) frequently made tech headlines in 2017, often for innovative new products and growth in the workplace. Multiple reports examined the technology's future and implications. An October Gartner report predicted that AI will create 2.3 million jobs by 2020. And China is now racing to AI world dominance, which may mean a global power shift. Experts predicted AI's growth and potential moral issues for business users and consumers.

If you drive an electric car and would rather not venture into the garage (or wade through a phone app) to start charging, you can now rest easy. ChargePoint has introduced Alexa support to its Home system, giving you voice control over your EV charging. You can start charging, stop charging or find out whether you're plugged in just by talking to a device like an Echo speaker. If you have Nest hardware, you can link charging to multiple parts of your home. And if you top up at ChargePoint stations away from home, you can check your balance or see how much you've spent on electricity so far.

Poisson matrix factorization (PF) is a nonnegative matrix factorization (NMF) model (Lee and Seung, 1999) often used for recommender systems (Ma et al., 2011; Gopalan et al., 2015), text information retrieval (Canny, 2004; Buntine and Jakulin, 2006) or dictionary learning for image processing (Cemgil, 2009). The data is assumed to be drawn from the Poisson distribution making it specially well suited for count/integer-valued data. Since the Netflix Prize (Bennett et al., 2007), collaborative filtering (CF) has been giving the state-of-the-art results for recommender systems. CF exploits data relating users to items, like historical data. These data can either be explicit (ratings given by users to items) or implicit (count data from users listening to songs, clicking on web pages, watching videos, etc).

Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional recommender systems consider the recommendation procedure as a static process and make recommendations following a fixed strategy. In this paper, we propose a novel recommender system with the capability of continuously improving its strategies during the interactions with users. We model the sequential interactions between users and a recommender system as a Markov Decision Process (MDP) and leverage Reinforcement Learning (RL) to automatically learn the optimal strategies via recommending trial-and-error items and receiving reinforcements of these items from users' feedbacks. In particular, we introduce an online user-agent interacting environment simulator, which can pre-train and evaluate model parameters offline before applying the model online. Moreover, we validate the importance of list-wise recommendations during the interactions between users and agent, and develop a novel approach to incorporate them into the proposed framework LIRD for list-wide recommendations. The experimental results based on a real-world e-commerce dataset demonstrate the effectiveness of the proposed framework.

Build it and they will come. Those were the good ole days. It used to be good enough to design a great app. Add to that an engaging user experience (UX), positive feedback, a high ranking and word of mouth, and your app was ensured continued success. Nowadays however, mobile consumers are simply overwhelmed by choice.

It's been six years since Apple added Siri to iOS and voice became a key way users could interact with technology. In the years since, Google Assistant and Alexa have also established strong footholds as central players in the way we manage myriad services and smart-home devices -- and Cortana has become an integral part of the PC. As much as voice-activated virtual assistants have begun to transform the consumer landscape on devices from smartphones and smartwatches to smart speakers, they have yet to truly break through in the enterprise. That isn't to say we don't already accomplish business tasks using these virtual assistants. Many of us rely on them for quick tasks such as getting directions, scheduling appointments and responding to messages.