Project Stream promises to deliver the holy grail to video game fans around the globe -- the ability to play the latest AAA games on any laptop or PC via a stable, no-lag streaming service. Google is preparing to publicly test Project Stream with a "limited number of participants" on October 5th, letting them play Assassin's Creed Odyssey for free in the Chrome browser. That's the latest game in the Assassin's Creed series, and it's a massive open-world adventure packed with 4K-capable graphics. In a demo video, Google shows Assassin's Creed Odyssey streaming at 1080p and 60fps. If all goes to plan, the game should work on any laptop or PC, regardless of how recently you've updated the graphics card.

Gil Weinberg, Ph.D. is a professor in Georgia Tech's School of Music and the founding director of the Georgia Tech Center for Music Technology, where he leads the Robotic Musicianship group. His research focuses on developing artificial creativity and musical expression for robots and augmented humans. Among his projects are a marimba-playing robotic musician called Shimon that uses machine learning for jazz improvisation, and a prosthetic robotic arm for amputees that restores and enhances human drumming abilities. Weinberg will discuss this and other robotics projects as an allegory to unlocking our own creative potential. If we can teach a robot to be creative – to improvise, to think on its feet, to draw cues from others for where to head next – surely we can unlock that same potential within ourselves.

Data science and machine learning are powerful technologies innovating the world in ways that sometimes seem straight out of a sci-fi film. Today's machines are not just capable of tedious tasks, but also using complex mathematics to figure out how to chart a path for a rocket to follow or making weather predictions based on historical data. What better platform to explore the magic of data science and machine learning than film? We've rounded up 10 of the best data movies: Ex Machina: The title comes from the Latin phrase "deus ex machina," translated as "god from the machine." In the film, Caleb, a programmer at one of the largest internet companies in the world, is selected to participate in the biggest experiment of the century.

The term "artificial intelligence" has been around since 1956, and yet many journalists are unfamiliar with its history and impact on the world today, even as its influence grows everywhere, including on how we gather and report the news. The next massive open online course (MOOC) in Spanish, and the Knight Center's first in partnership with Microsoft, will familiarize students with the foundations of artificial intelligence (AI) and how it impacts the news industry. "Artificial Intelligence: How to cover AI and understand its impact on journalism," will run from Oct. 22 to Nov. 25, 2018 and will be taught by Sandra Crucianelli, a veteran instructor for Knight Center MOOCs and a member of the International Consortium of Investigative Journalists (ICIJ). "The course will be a wonderful opportunity for those who have not yet become familiar with artificial intelligence technologies," Crucianelli said. "We will be sharing definitions, but also analyzing applications, examples and there also will be online discussions. For example, will robots replace journalists? This is a question that many of us ask and I believe the exchange of opinions will be very interesting."

Welcome to Small Humans, an ongoing series at Mashable that looks at how to take care of – and deal with – the kids in your life. Because Dr. Spock is nice and all, but it's 2018 and we have the entire internet to contend with. During my first pregnancy, I craved a mamaRoo rocker, believing it would alleviate by stress as a new mom. Instead, I did things the old-fashioned way, rocking my baby in my arms and using baby wraps for multitasking. Nearly three years later, I'm thinking about it again as we wait on our second child.

Accenture Introduces Ella and Ethan, AI Bots to Improve a Patient's Health and Care Using the Accenture Intelligent Patient Platform NEW YORK; Sept. 21, 2018 – Accenture (NYSE: ACN) has enhanced the Accenture Intelligent Patient Platform with the addition of Ella and Ethan, two interactive virtual-assistant bots that use artificial intelligence (AI) to constantly learn and make intelligent recommendations for interactions between life sciences companies, patients, health care providers (HCPs) and caregivers. Designed to help improve a patient's health and overall experience, the bots are part of Accenture's Salesforce Fullforce Solutions powered by Salesforce Health Cloud and Einstein AI, as well as Amazon's Alexa. The Ella and Ethan bots are part of the Patient Engagement Support solution in the Accenture Intelligent Patient Platform, a digital health solution that supports patients throughout their healthcare experience, from participation in clinical trials through managing ongoing treatment and wellness. The bots are designed to deliver a more personalized patient experience and better patient support. Ella is a virtual care assistant for patients that provides medication reminders, vitals tracking and appointment scheduling.

Accenture Introduces Ella and Ethan, AI Bots to Improve a Patient's Health and Care Using the Accenture Intelligent Patient Platform NEW YORK; Sept. 21, 2018 – Accenture (NYSE: ACN) has enhanced the Accenture Intelligent Patient Platform with the addition of Ella and Ethan, two interactive virtual-assistant bots that use artificial intelligence (AI) to constantly learn and make intelligent recommendations for interactions between life sciences companies, patients, health care providers (HCPs) and caregivers. Designed to help improve a patient's health and overall experience, the bots are part of Accenture's Salesforce Fullforce Solutions powered by Salesforce Health Cloud and Einstein AI, as well as Amazon's Alexa. The Ella and Ethan bots are part of the Patient Engagement Support solution in the Accenture Intelligent Patient Platform, a digital health solution that supports patients throughout their healthcare experience, from participation in clinical trials through managing ongoing treatment and wellness. The bots are designed to deliver a more personalized patient experience and better patient support. Ella is a virtual care assistant for patients that provides medication reminders, vitals tracking and appointment scheduling.

This is an era of disruption. Technology innovation, the intensifying march of digitization, and the cumulative effect of the "big exponentials" - the laws of accelerating growth governing processing power, storage, and bandwidth - are shattering, reshaping, and redefining economics in and across industries. Companies in the technology, media, and telecommunications (TMT) sectors are in the vanguard, bringing these new opportunities to market - even as their legacy businesses are threatened by them. TMT companies have begun to engage in end-to-end digital transformation by digitizing the value chain in their core businesses and enter new disruptive businesses. Still, they are subject to massive dislocation and attack.

In this paper, we propose a deep, globally normalized topic model that incorporates structural relationships connecting documents in socially generated corpora, such as online forums. Our model (1) captures discursive interactions along observed reply links in addition to traditional topic information, and (2) incorporates latent distributed representations arranged in a deep architecture, which enables a GPU-based mean-field inference procedure that scales efficiently to large data. We apply our model to a new social media dataset consisting of 13M comments mined from the popular internet forum Reddit, a domain that poses significant challenges to models that do not account for relationships connecting user comments. We evaluate against existing methods across multiple metrics including perplexity and metadata prediction, and qualitatively analyze the learned interaction patterns.

We present a study on predicting the factuality of reporting and bias of news media. While previous work has focused on studying the veracity of claims or documents, here we are interested in characterizing entire news media. These are under-studied but arguably important research problems, both in their own right and as a prior for fact-checking systems. We experiment with a large list of news websites and with a rich set of features derived from (i) a sample of articles from the target news medium, (ii) its Wikipedia page, (iii) its Twitter account, (iv) the structure of its URL, and (v) information about the Web traffic it attracts. The experimental results show sizable performance gains over the baselines, and confirm the importance of each feature type.