Mobile apps have been at the center of the technological revolution because of rising consumer demand for instantaneous, on-the-go access to content. With U.S. users spending over 5 hours a day on mobile apps, it's no wonder apps are one of the main sources for how users access the internet. And because mobile apps have become such a fundamental part of our day-to-day technological experience, there's a sense of urgency among tech companies to discover and distribute something that's new and exciting. The biggest trends that are taking shape in app creation involve the integration of artificial intelligence, virtual reality and augmented reality. Consumers first began to see the application of this advanced tech with the introduction of Niantic's hit gaming app, Pokemon Go.

AI-enhanced computer programs able to hold audio or text-based conversations that simulate convincingly how a human would interact… Whatever you want to call these code-based dialoguers, they are taking the enterprise by storm. From marketing, customer service, and e-commerce bots helping people purchase everything from flowers to flights, to workforce productivity'manager' bots delivering reminders, deadlines, and tips tailored to individual employees… companies are deploying bots to serve all manner of objectives. Such initiatives are also a common entry point for enterprise adoption of machine learning, but they are also just the tip of the iceberg when it comes to the opportunities and the risks of and artificial intelligence (AI). What follows are three areas companies often overlook when deploying chatbots. Chatbots are now being used by brands for service interactions, including simple outreach, education, feedback and survey collection, questions and answers (Q&A), tips and advice, etc.

Google Assistant wants to help you get your day started. The search giant said Tuesday it's launching a new'visual snapshot' feature in the Google Assistant app that will give users a rundown of all their important meetings, restaurant or movie suggestions, commute times, upcoming bills and more. It's now available on the app for both Android and iOS devices in all languages supported by the Google Assistant app. Google said it's launching a new'visual snapshot' feature in the Assistant app that will give users a rundown of meetings, movie suggestions, commute times, upcoming bills and more Google says the app will provide'curated, helpful information' depending on what time of day it is, where you are and your recent interactions with Google Assistant. Users are encouraged to check back throughout the day for updates.

An important task for a recommender system to provide interpretable explanations for the user. This is important for the credibility of the system. Current interpretable recommender systems tend to focus on certain features known to be important to the user and offer their explanations in a structured form. It is well known that user generated reviews and feedback from reviewers have strong leverage over the users' decisions. On the other hand, recent text generation works have been shown to generate text of similar quality to human written text, and we aim to show that generated text can be successfully used to explain recommendations. In this paper, we propose a framework consisting of popular review-oriented generation models aiming to create personalised explanations for recommendations. The interpretations are generated at both character and word levels. We build a dataset containing reviewers' feedback from the Amazon books review dataset. Our cross-domain experiments are designed to bridge from natural language processing to the recommender system domain. Besides language model evaluation methods, we employ DeepCoNN, a novel review-oriented recommender system using a deep neural network, to evaluate the recommendation performance of generated reviews by root mean square error (RMSE). We demonstrate that the synthetic personalised reviews have better recommendation performance than human written reviews. To our knowledge, this presents the first machine-generated natural language explanations for rating prediction.

According to CNET, Nest has announced today that Marwan Fawaz will no longer be its CEO. As part of his departure, Nest will now be folded into Google's home and living room products team. In a joint interview with Fawaz, Rishi Chandra, vice president of product management for Google's home and living room products, said that the combination would make it easier for Google to integrate some of its machine learning technology and artificial intelligence into Nest products. This move comes six months after Nest merged with Google's hardware division. Nest co-founder Matt Rogers left soon after as well.

For the past couple of years, financial institutions have explored how AI can help them in several areas, such as reducing costs, enhancing revenue, eliminating fraud and improving the customer experience. One of the most recent AI efforts is Bank of America's Erica, a virtual assistant focused on the customer experience when launched three months ago. The financial services player claims it is the first widely available AI-driven virtual assistant of its kind in the industry. The bank recently announced 1 million mobile banking users have accessed Erica's features to search for transactions, view balance information and bills, get their credit scores and their account numbers. While that figure represents only 4 percent of the bank's 25 million-plus mobile banking clients, at least one industry analyst deemed it as progress from Bank of America.

Artificial intelligence (AI) will be a good thing for the digital workplace. Despite concerns about job redundancies and shifting enterprise priorities, recent research from global auditing company PwC suggests that, far from hindering employees or even making some jobs obsolete, AI will help workers achieve business objectives quicker and more effectively. To do that, however, organizations will need to invest in different types of AI. The research, part of PwC's Economic Outlook for 2018, predicted the main contributor to the UK's economic gains between 2017 and 2030 will come from consumer product enhancements stimulating consumer demand (8.4 percent). The research identified AI as a key factor in this growth, by driving a greater choice of products, increasing personalization and making those products more affordable over time.

There is a pending boom of artificial intelligence (AI) capabilities, and organizations will capitalize on them as AI continues to scale, evolve and mature. Over time, AI adoption at the enterprise level will cause an incremental upending of traditionally known roles, skills and talent composition within every single business function. According to the 2018 Human Capital Trends Report, "The transition to digital business tools is at the top of the strategic agenda for many businesses today." If mobile, social and cloud computing were some of the biggest platform shifts and technological investments that dominated the beginning of the 21st century, AI investments will be considered the next wave of major technological shifts. Forrester predicts that most (if not all) technology functions will be augmented or replaced by AI.

A new study by CapGemini finds that consumers are ready to embrace AI support, and that AI interactions, if properly designed, can enhance the personal connection they feel to brands. The study is comprehensive – it is based on surveys of 10,000 consumers from 10 different markets and covers all ages, income groups and employee status. It is current, as the surveys were conducted this May. These surveys were supplemented with three virtual focus group discussions with 8-10 consumers per focus group in the U.S., France and Germany. Research for the report included interviews with several key industry stakeholders and academics.

In fact, according to a recent Forbes Insights survey of 300-plus executives--63% of whom were in the C-suite--95% believe that AI will play an important role in their responsibilities in the near future. The deep data that AI allows companies to tap into is providing insights to help solve challenges in everything from better neuroscience diagnoses to producing kegs of beer. The power of AI is understood by business leaders regardless of company size: The Forbes Insights survey drew detailed responses from companies with annual revenue over $10 billion to as low at $250 million, with remarkable consensus across business size and sectors. All told, 99% of executives in technical positions say their organizations are going to boost their AI spending in the coming year, a level of funding increases likely unmatched anywhere else in the corporate world. Implementation of AI is just getting started in business, but make no mistake: Change comes quickly.