The quest for algorithms that enable cognitive abilities is an important part of machine learning. A common trait in many recently investigated cognitive-like tasks is that they take into account different data modalities, such as visual and textual input. In this paper we propose a novel and generally applicable form of attention mechanism that learns high-order correlations between various data modalities. We show that high-order correlations effectively direct the appropriate attention to the relevant elements in the different data modalities that are required to solve the joint task. We demonstrate the effectiveness of our high-order attention mechanism on the task of visual question answering (VQA), where we achieve state-of-the-art performance on the standard VQA dataset.

As the growing temptation for automated processes covers the varied industrial spectrum, Machine Learning is emerging into an ocean of possibilities while IBM's Watson leads the marathon. From acting as a virtual chef of 65 recipes to embracing space programs, there's a swathe of applications being ideated, built and rolled out to the public. Pulling large volumes of data and producing the most relevant possible results to user's quest stays the flag bearer, Watson is amazing in churning higher revenues and upscaling business presence. Treatment for many of the world's deadliest diseases is entirely dependent upon reference to past records. While browsing through them all using traditional analytics applications is unvaried, IBM Watson takes a giant leap with instant derivations from years of clinical research and patient data.

This demo shows how to control a Smart Home using IBM Watson and Augmented Reality technologies.

We've all heard or read about how robots are going to take away our jobs. Saudi Arabia even went as far as granting citizenship to "Sophia the robot" back in October (See the video below). With crytocurrency at the top of daily headlines, 2017 may be remembered as the year artificial intelligence (AI, pronounced AYE-EYE) goes mainstream with more organizations adopting AI than ever. Two weeks ago, we wrote about Professor Geoffrey Hinton, known worldwide as the Godfather of AI, and how his research work in the area of Neuro Net was used in speech recognition and Android voice search. Yes, we've made a lot of progress since AI started as an academic discipline in 1956.

Last week, hundreds of digital health entrepreneurs, investors, and executives met in Boston for the annual Digital Healthcare Innovation Summit. Among the more frequently discussed trends and technologies was artificial intelligence -- its promise, its stumbles, and how it should be implemented to best serve healthcare. "I started marketing Watson for Oncology in January of 2016. I'm almost approaching two years," Deborah DiSanzo, general manager at IBM Watson Health, said during a session. "By the end of this year, I will have over 20,000 patients [and] over 120 hospitals using it, and really seeing helping oncologists all over the world. Nothing that I have done in my life in healthcare technology has gone as fast as that, and that is not hype."

Since its creation, artificial intelligence (AI) has found use in many different industries, including healthcare. The amount of medical data is astronomically huge and the problem of systematizing, storing, and, above all, using such data is of the utmost importance. People have long hoped that someday, computers will make accurate diagnoses and eliminate medical errors. But no one has created an effective AI doctor yet. The Skychain project promises to revolutionize the healthcare industry, using AI and blockchain technology.

Before scientists can effectively capture and deploy fusion energy, they must learn to predict major disruptions that can halt fusion reactions and damage the walls of doughnut-shaped fusion devices called tokamaks. Today, researchers at the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL) and Princeton University are employing artificial intelligence to improve predictive capability....

A handheld device that performs tasks upon voice command used to be a figment of science fiction. Today, however, voice-search enabled digital assistants have entered the consumer market one by one. Each tech brand, in turn, continues to develop more voice-activated personal devices like Google Home, Amazon Echo, as well as a variety of tablets and smartphones. According to Google, more than 50% of search queries around the world are done using mobile devices. Of that statistic, 20% are voice searches.

Open any business publication or digital journal today, and you will read about the promise of AI, known as artificial or augmented intelligence, and how it will transform your business. The fact is: AI will not only transform your entire business -- whether you are in healthcare, finance, retail, or manufacturing -- but it will also transform technology itself. The essential task of information technology (IT) -- and how we measure its value -- has reached an inflection point. Instead, insight is the new currency. The speed with which we can scale that insight and the knowledge it brings is the basis for value creation and the key to competitive advantage.

Powered by artificial intelligence and voice-ready services and devices, voice searches are bound to rise on a massive scale. Users are right in the middle of changing the way, they search for content and information and buy products and services online. Customer service and support will follow the same trend. With AI understanding natural language, voice searches will result in longer and advanced search queries. Long tail will be the SEO industry's big thing for years to come.