Multimodal learning has shown promising performance in content-based recommendation due to the auxiliary user and item information of multiple modalities such as text and images. However, the problem of incomplete and missing modality is rarely explored and most existing methods fail in learning a recommendation model with missing or corrupted modalities. In this paper, we propose LRMM, a novel framework that mitigates not only the problem of missing modalities but also more generally the cold-start problem of recommender systems. We propose modality dropout (m-drop) and a multimodal sequential autoencoder (m-auto) to learn multimodal representations for complementing and imputing missing modalities. Extensive experiments on real-world Amazon data show that LRMM achieves state-of-the-art performance on rating prediction tasks. More importantly, LRMM is more robust to previous methods in alleviating data-sparsity and the cold-start problem.

Donald Trump has intensified his attacks on Google, with a fresh complaint about its home page. The president claimed that the site promoted the State of the Union address while Obama was president, by telling everyone who visited its home page to watch through YouTube. But as soon as Mr Trump became president those promotions stopped. He suggested that the change proves his claim that the search giant is biased against him. He had previously complained the site was failing to show positive enough results when he searched for his name.

Rotten Tomatoes has overhauled its criteria for which critics and outlets get to contribute to its Tomatometer scores, opening the platform up to more voices and points of view. The company said that when it got started, it largely included critics from major publications and broadcasters with a large audience reach, which fit with the media landscape at the time. "In the intervening decades, a lot has changed," said the company, noting that staff positions at major outlets have dwindled and many critics are producing good work elsewhere, through smaller online outlets, podcasts and YouTube, for example. "In revamping our critics criteria, we sought to bring the criteria into better alignment with the way media works today, to promote the inclusion of more voices that reflect the varied groups of people who consume entertainment and to maintain the high standards we've always set for inclusion in the group of Tomatometer-approved critics," said the company. Its new criteria focus on insight, audience, quality and dedication and its updated eligibility guidelines include stipulations for self-published writers and freelancers, vloggers and podcasters.

Artificial intelligence has been the domain of science fiction for decades -- think HAL, the computer in "2001: A Space Odyssey" -- but as many people know, it's actually established well-developed and growing roots in modern-day life. Amazon's Echo, Netflix's recommendation engines, Facebook's facial recognition technology, auto-braking on cars, it's all based on the ability to analyze massive amounts of data in near real-time and being able to mimic human behavior based on the results. AI and its various subsegments -- like machine learning and deep learning -- are also reaching deep into the enterprise, helping to automate many of the tasks that now are done manually, creating greater efficiencies, reducing errors and offering valuable new insights into the massive amounts of data being generated. In a dynamic and fast-changing market like manufacturing, systems that can learn and adapt on their own will be crucial in driving the next-generation flexible environments. According to Accenture, 85 percent of executives plan to invest in AI technologies over the next three years.

Your wrist is about to get a serious upgrade. Google announced on Wednesday that a long-overdue Wear OS redesign will be rolling out to all watches over the next month. It's not the first Wear OS refresh we've gotten--Google has quietly been updating the OS formerly known as Android Wear throughout 2018, including bringing a true dark mode that finally takes advantage of the OLED screens on nearly every smartwatch--but this is the first full-scale redesign it's gotten since Android Wear 2.0 landed back in February 2017. And while it's not quite the revolutionary overhaul some want to see, it does bring a nice visual improvement and a few necessary navigational shortcuts to help us spend less time touching the screen. Of note, watches will now use Google's Products Sans font, bringing them in line with the Pixel phones.

The development of artificial intelligence (AI)-powered assistants has witnessed a massive revolution. What started off as a tech trend has slowly become an indispensable asset to a business enterprise, supporting sales, service and other business functions across multiple industries. We have virtual sales assistants taking in humanistic conversations to customers making sales and generating leads. Powered by AI, these virtual sales assistants enable business enterprises to generate leads than ever before and provide a polite and persistent lead follow-up which often generates to increased sales figures. Virtual sales assistants are a win-win for both the business and the customers as these virtual assistants never get tired or sick or take a day off, leaving salespeople free to do more valuable activities, and customers love them because they are resourceful and provide assistance customised to a customer's requirements.

The leather shoes you've ordered are now out-of-stock. Would you like me to find you another pair?" "Can you get me the brown instead…No, black." Black is easier to pair with other colors." The Chinese e-commerce giant introduced new upgrades to the bot, including 24/7 automated customer support, stronger predictive analytics to forecast what users might ask next, greater scalability for peak demand and small nudges to facilitate shopping decisions, such as reminders about discount vouchers on offer to consumers. Alibaba said the newly upgraded bot can help merchants cut up to half of their previous call-center costs, as well as feature a "warmer touch," allowing the bot to converse more naturally thanks to human-computer interaction technologies.

According to research conducted by Harvard Business School, digital leaders -- enterprises that embraced Digital Transformation -- saw their three-year average gross margins at 55%, compared to only 37% for digital laggards -- the companies that were not prepared to transform their businesses digitally. And when it came to earnings, digital leaders posted an average net income of 11% while digital laggards only had 7% net income. In today's highly competitive business environment, Digital Transformation is no longer optional -- it is an imperative, a necessity in order for enterprises to remain competitive or even just to stay afloat. To keep up with Digital Transformation, enterprises must understand where it is going. In this post, we explore five important trends that will help enterprises discern where the digital revolution is heading this 2018.

Artificial intelligence is presented as the opposite of natural intelligence, which is demonstrated by animals. By that definition, AI would appear to be free from the social neuroses and discriminations that can plague humans. But machine learning originates from human makers, meaning those shortcomings can be passed along via algorithms and data input. AI is increasingly customer-facing: It includes asking Siri details about an upcoming trip or turning on Netflix and seeing recommendations based on viewing habits. AI touches numerous points along the customer journey, meaning its limitations can have organization-wide consequences.

Recommender systems relying on latent factor models often appear as black boxes to their users. Semantic descriptions for the factors might help to mitigate this problem. Achieving this automatically is, however, a non-straightforward task due to the models' statistical nature. We present an output-agreement game that represents factors by means of sample items and motivates players to create such descriptions. A user study shows that the collected output actually reflects real-world characteristics of the factors.