The global healthcare virtual assistant market is expected to grow at a CAGR of 24.7% from 2018 to reach $1.76 billion by 2025, according to market research published by Meticulous Research. Virtual assistants are AI and rule-based systems that interact with humans to perform various tasks. These assistants use cognitive technologies such as machine learning, natural language processing, and neural networks to enable interactive communications with the end-users. Virtual assistant technology in the healthcare industry can assist in transforming various health processes and improve healthcare delivery, worldwide. It helps in improving healthcare quality, patient care, and patient outcome at lower costs.

Hey, Google, enough is enough already. Google was caught having contractors listening in to our conversations from its personal assistant, which sounds bad until you realize Google wasn't alone in this. Apple and Facebook were doing the same thing. And this week, Microsoft got stung by Vice's Motherboard, and now admits it, too, listens. The companies, which also include Amazon, have said they do this on a limited basis to learn and make their assistants better.

Over the last few years, Artificial Intelligence (AI), has spread beyond the realm of IBM's super-computer Watson, into the houses and pockets of billions around the globe courtesy of the likes of Apple's Siri & Amazon's Alexa. While AI may have evolved from a rather abstract, sci-fi concept, to a real-life, practical part of our conscious everyday lives, there are many around the globe who question its relevancy & impact to the small-medium business (SMB) community -- a community that is still so important to the economic prosperity of almost every country around the globe. One of the first & most obvious challenges to the SMB space is the associated cost. Fortunately, for businesses on a budget, AI investment & deployment doesn't need to break the bank. While developing your own AI is undoubtedly a complex and time-consuming process requiring a considerable amount of investment, fortunately, several tech companies have open-sourced their AI efforts in a bid to make AI more accessible to greater sections of society (including SMBs).

Now is the best time to buy a laptop--even if you're not a student. Here's what you need to know to find the best deals! 'Tis the season for heading off to school for another year of higher learning. But at the very least, there are some cool back-to-school gadgets to get excited about – including high-tech devices to keep you organized, productive and entertained while in a dorm room. And the good news is you don't have to blow your budget to get some great gear.

Though conversational AI has been around since the 1960s, it's experiencing a renewed focus in recent years. While we're still in the early days of the design and development of intelligent conversational AI, Google quite rightly announced that we were moving from a mobile-first to an AI-first world, where we expect technology to be naturally conversational, thoughtfully contextual, and evolutionarily competent. In other words, we expect technology to learn and evolve. Most chatbots today can handle simple questions and respond with prebuilt responses based on rule-based conversation processing. For instance, if user says X, respond with Y; if user says Z, call a REST API, and so forth.

For the business leader or entrepreneur, every day can seem like a battle. Phone calls, text messages, setting appointments, taking notes of conversations, attending meetings. Even prioritizing your email inbox seems like a daunting task. Wouldn't it be great if you could have a personal assistant who would take care of all that for you? Well, that is the promise of Artificial Intelligence Apps.

"Our AI takes about 20 moves, most of the time solving it in the minimum number of steps," Baldi says. "Right there, you can see the strategy is different, so my best guess is that the AI's form of reasoning is completely different from a human's." The ultimate goal of projects such as this one is to build the next generation of AI systems, Baldi says. Whether they know it or not, artificial intelligence touches people every day through apps such as Siri and Alexa and recommendation engines working behind the scenes of their favorite online services. "But these systems are not really intelligent; they're brittle, and you can easily break or fool them," Baldi says.

The financial services industry has seen a great deal of disruption from digital-based alternatives. Many of these challengers use advanced technology and expanded data sets to offer apps that provide financial solutions at a lower cost, with less friction and greater personalization than traditional bank or credit union offerings. Toronto-based startup Flybits believes that the best way to compete in the future is not just by developing innovative products and services, but by becoming the repository of choice for data in addition to money. "I definitely see that banks are in a perfect position, if they innovate right, to be the perfect data vaults for the future – managing the privacy and also the data of their customers," says Hossein Rahnama, CEO and Co-Founder of Flybits, in an exclusive interview for Banking Transformed, a new podcast from Jim Marous and The Financial Brand. "Using AI and machine learning, there is the potential to build a'data marketplace' for banks, fintechs and other data providers to partner and build more services together."

Microsoft's listening program continues to grow in scope after a new report reveals that contractors harvested unintentional audio from Xbox users through Cortana and the Kinect. Motherboard reports that Xbox users were recorded by Microsoft as part of a program to analyze users' voice-commands for accuracy and that those recordings were assessed by human contractors. While the program was designed to only scrape audio uttered after a wake-word, contractors hired by Microsoft report that some recordings were taken accidentally without provocation. The practice, reports Motherboard, has been ongoing for several years since the early days of Xbox One and predates Xbox's integration with its voice assistant, Cortana. Xbox users were being recorded by Microsoft in a listening program that scraped audio from Cortana and its augmented reality hardware, Kinect. The company analyzed commands given to the Xbox's increasingly unpopular augmented reality hardware called the Kinect.

Given a sparse rating matrix and an auxiliary matrix of users or items, how can we accurately predict missing ratings considering different data contexts of entities? Many previous studies proved that utilizing the additional information with rating data is helpful to improve the performance. However, existing methods are limited in that 1) they ignore the fact that data contexts of rating and auxiliary matrices are different, 2) they have restricted capability of expressing independence information of users or items, and 3) they assume the relation between a user and an item is linear. We propose DaConA, a neural network based method for recommendation with a rating matrix and an auxiliary matrix. DaConA is designed with the following three main ideas. First, we propose a data context adaptation layer to extract pertinent features for different data contexts. Second, DaConA represents each entity with latent interaction vector and latent independence vector. Unlike previous methods, both of the two vectors are not limited in size. Lastly, while previous matrix factorization based methods predict missing values through the inner-product of latent vectors, DaConA learns a non-linear function of them via a neural network. We show that DaConA is a generalized algorithm including the standard matrix factorization and the collective matrix factorization as special cases. Through comprehensive experiments on real-world datasets, we show that DaConA provides the state-of-the-art accuracy.