"The programmability and flexibility of hybrid FPGAs that host firmware and software has made them one of the best choices for machine learning and …

One of the major concerns in healthcare industry of developing countries is inadequate doctors' population. According to the World Health Organization (WHO), nearly 57 countries globally are facing a shortage of 2.3 million nurses and physicians. Therefore, the demand for improvising healthcare accessibility is currently at its peak. Healthcare facility automation is not only helpful to patients but also to the doctors, as it enables them with extra time to concentrate on critical cases. AI analysis helps in providing generalized advice to patients.

When it comes to the realm of artificial intelligence (AI), the sky's the limit. As we impart our "natural intelligence" as humans to machines, they can now …

"Artificial intelligence is a super powerful tool, and like any really powerful tool, it can be used to do a lot of things – some of which are good and some …

Chooch AI has released a new computer vision service that allows users to detect and categorize events in any kind of local video stream.

This paper provides statistical theory and intuition for Personalized PageRank (PPR), a popular technique that samples a small community from a massive network. We study a setting where the entire network is expensive to thoroughly obtain or maintain, but we can start from a seed node of interest and "crawl" the network to find other nodes through their connections. By crawling the graph in a designed way, the PPR vector can be approximated without querying the entire massive graph, making it an alternative to snowball sampling. Using the Degree-Corrected Stochastic Blockmodel, we study whether the PPR vector can select nodes that belong to the same block as the seed node. We provide a simple and interpretable form for the PPR vector, highlighting its biases towards high degree nodes outside of the target block. We examine a simple adjustment based on node degrees and establish consistency results for PPR clustering that allows for directed graphs. We illustrate the method with the Twitter friendship graph and find that (i) the adjusted and unadjusted PPR techniques are complementary approaches, where the adjustment makes the results particularly localized around the seed node and (ii) the bias adjustment greatly benefits from degree regularization.

A Global Navigation Satellite System (GNSS) uses a constellation of satellites around the earth for accurate navigation, timing, and positioning. Natural phenomena like space weather introduce irregularities in the Earth's ionosphere, disrupting the propagation of the radio signals that GNSS relies upon. Such disruptions affect both the amplitude and the phase of the propagated waves. No physics-based model currently exists to predict the time and location of these disruptions with sufficient accuracy and at relevant scales. In this paper, we focus on predicting the phase fluctuations of GNSS radio waves, known as phase scintillations. We propose a novel architecture and loss function to predict 1 hour in advance the magnitude of phase scintillations within a time window of plus-minus 5 minutes with state-of-the-art performance.

The Internet of Things is changing so many aspects of our daily lives that's it's almost hard to keep up. While many of these changes seem small, when you take them all together, it becomes clear that we are on the verge of a monumental shift in how we work, play, and manage simple, everyday tasks. In fact, thanks to technology and the IoT, it won't be long before many of the items that we use on a regular basis will become obsolete. Consider these items that are not too far away from going the way of the dinosaur. In fact, according to a Gallup poll, only about 24 percent of Americans use cash to make most or all of their purchases.

Businesses will reap more success from artificial intelligence projects by setting short-term, achievable goals instead of pursuing extremely ambitious ones, industry executives advise. Clive Swan is Oracle's senior vice president of applications development. The hype around AI, the set of statistical techniques that teaches software to make decisions based on past data, pushes many companies to rush adoption and launch "moon shots" that are hard to bring to fruition, said Clive Swan, Oracle senior vice president of applications development, at the Oracle OpenWorld conference in September. Typical mistakes include not adequately preparing corporate data or failing to augment it with third-party information sources such as news stories, press releases, and financial or corporate information, Swan said. Bill Briggs, chief technology officer at Deloitte Consulting, used a baseball metaphor, saying during another discussion at Oracle OpenWorld that businesses can do better playing "small ball."