On this week's If Then, Slate's April Glaser and Will Oremus discuss the outrage at the largest TV-station owner in the country--Sinclair Broadcasting--after the media conglomerate forced its local-news anchors to read a script that echoes Trumpian talking points. They also unpack Trump's beef about Jeff Bezos owning what he calls the #AmazonWashingtonPost. Meanwhile, music streaming site Spotify went public this week in a totally new kind of way. The hosts take a look at its unorthodox move and what it means for the company's future.
Abstract: Human pose estimation and action recognition are related tasks since both problems are strongly dependent on the human body representation and analysis. Nonetheless, most recent methods in the literature handle the two problems separately. In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences. We show that a single architecture can be used to solve both problems in an efficient way and still achieves state-of-the-art or comparable results at each task while running at more than 100 frames per second. The proposed method benefits from high parameters sharing between the two tasks by unifying still images and video clips processing in a single pipeline, allowing the model to be trained with data from different categories simultaneously and in a seamlessly way.
The biggest hardware and software arrival since the iPad in 2010 has been Amazon's Echo voice-controlled intelligent speaker, powered by its Alexa software assistant. But just because you're not seeing amazing new consumer tech products on Amazon, in the app stores, or at the Apple Store or Best Buy, that doesn't mean the tech revolution is stuck or stopped. They are: Artificial intelligence / machine learning, augmented reality, virtual reality, robotics and drones, smart homes, self-driving cars, and digital health / wearables. Google has changed its entire corporate mission to be "AI first" and, with Google Home and Google Assistant, to perform tasks via voice commands and eventually hold real, unstructured conversations.
Hua, Ting (Virginia Polytechnic Institute and State University) | Ning, Yue (Virginia Polytechnic Institute and State University) | Chen, Feng (State University of New York at Albany) | Lu, Chang-Tien (Virginia Polytechnic Institute and State University) | Ramakrishnan, Naren (Virginia Polytechnic Institute and State University)
The analysis of interactions between social media and traditional news streams is becoming increasingly relevant for a variety of applications, including: understanding the underlying factors that drive the evolution of data sources, tracking the triggers behind events, and discovering emerging trends.Researchers have explored such interactions by examining volume changes or information diffusions,however, most of them ignore the semantical and topical relationships between news and social media data.Our work is the first attempt to study how news influences social media, or inversely, based on topical knowledge.We propose a hierarchical Bayesian model that jointly models the news and social media topics and their interactions.We show that our proposed model can capture distinct topics for individual datasets as well as discover the topic influences among multiple datasets.By applying our model to large sets of news and tweets, we demonstrate its significant improvement over baseline methods and explore its power in the discovery of interesting patterns for real world cases.
How's it gone so far? Microsoft's big annual conference kicks off today, and we've sniffed out what you can expect. We also get the full reveal of Amazon's Echo-with-a-screen. It's not pretty, but it does sound pretty smart. What to expect at Microsoft's Build 2017 conference While it's a mobile computing world, Microsoft has no shortage of projects we need to be updated on.