How TIME Re-created the 1963 March on Washington in Virtual Reality

TIME - Tech

Tucked away in an office on a quiet Los Angeles street, past hallways chockablock with miniature props and movie posters, is a cavernous motion-capture studio. And in that studio is the National Mall in Washington, D.C., in 1963, on the day Martin Luther King Jr. delivered his "I Have a Dream" speech. Or rather, it was inside that room that the visual-effects studio Digital Domain captured the expressions, movements and spirit of King, so that he could appear digitally in The March, a virtual reality experience that TIME has produced in partnership with the civil rights leader's estate. The experience, which is executive–produced and narrated by actor Viola Davis, draws on more than a decade of research in machine learning and human anatomy to create a visually striking re-creation of the country's National Mall circa 1963--and of King himself. When work on the project began more than three years ago, a big question needed answering.

There's No Homunculus In Our Brain Who Guides Us - Issue 81: Maps


In the early 1980s, the psychologist Harry Heft put a 16 mm camera in the back of a sports car and made a movie. It consisted of a continuous shot of a residential neighborhood in Granville, Ohio, where Heft was a professor at Denison University. It didn't have a plot or actors, but it did have a simple narrative: The car started moving at 5 miles per hour and made nine turns from one street to another and then came to a stop after traveling just under a mile. One showed just the vistas along the route, the expansive layout of environmental features, such as a group of houses or trees seen from a distance. The second film showed the transitions of the route, the parts between each vista where the view is occluded by, say, a turn in the road or the crest of a hill.

New Iranian Missiles Pose Threat to U.S. Aircraft in Yemen, Pentagon Says

NYT > Middle East

According to an American military official, the 358 missile in flight is about nine feet long and can run on kerosene or diesel fuel contained in flexible containers that do not require a separate fuel pump. A dozen infrared lenses arranged in a ring around the missile are believed to be able to defeat heat-seeking countermeasures that coalition helicopters typically use. Another United States military official said that the 358 missiles from Iran had been fired against American drones flying in Yemeni airspace, but they had not yet succeeded in hitting any. Three of the 358 missiles were captured in November by the Forrest Sherman, a Navy destroyer, and five more were recovered this month in an operation by the Normandy, a Navy cruiser. Those shipments also included more than 170 antitank guided missiles made in Iran, as well as 13,000 blasting caps, which are critical to making modern roadside bombs.

Google removes nearly 600 apps for spam-like ads after they were downloaded 4.5 BILLION times

Daily Mail - Science & tech

In a large scale effort to insulate users from disruptive spam and ads Google removed nearly 600 apps from its Play store that had been downloaded an astonishing 4.5 billion times. According to Google, the apps violated its rules on disruptive ad policies, meaning they show advertisements that were'displayed to users in unexpected ways, including impairing or interfering with the usability of device functions.' This can include plastering a device's screen with full-screen ads even when the application isn't being used or even when a user is trying to make a phone call. 'This is an invasive maneuver that results in poor user experiences that often disrupt key device functions and this approach can lead to unintentional ad clicks that waste advertiser spend,' wrote Google in a blog post. Advertisers scammed by those apps will be refunded according to Google.

Machine Learning in Communication Market : Quantitative Machine Learning in Communication Market Analysis, Current and Future Trends, 2019-2033 – Instant Tech Market News


With bottom-up and top-down approaches, the report predicts the viewpoint of various domestic vendors in the whole market and offers the market size of the Machine Learning in Communication market. The analysts of the report have performed in-depth primary and secondary research to analyze the key players and their market share. Further, different trusted sources were roped in to gather numbers, subdivisions, revenue and shares. The research study encompasses fundamental points of the global Machine Learning in Communication market, from future prospects to the competitive scenario, extensively. The DROT and Porter's Five Forces analyses provides a deep explanation of the factors affecting the growth of Machine Learning in Communication market.

The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place


This is a carefully curated compendium of articles & tutorials covering all things AI, Data Science & Machine Learning for the beginner to advanced practitioner. I will be periodically updating this document with popular topics from time to time. My hope is that you find something of use and/or the content will generate ideas for you to pursue.

How To: Make Your Own AI


Please join us this evening as we discuss how to make your own AI and AI apps. Following is a brief agenda for the evening: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:00 PM: Presentation by Suren and Mohamed 7:00 - 7:30 PM: Presentation by Cody 7:30 - 8:00 PM - Q&A and Networking Forward-thinking businesses are using AI to gain greater insights, make more accurate predictions and use AI to create new and compelling products and services. Across industries, AI is having a positive impact including drug discovery in pharmaceutical to cure diseases, sepsis detection in healthcare to save lives, supply chain transportation optimization to take costs out in manufacturing, fraud detection in banking to save money, subscriber churn predictions in telecoms to retain customers and personalized policies in insurance to delight consumers. Every industry stands to benefit from AI in their business. In this meetup, we will discuss how domain experts and advanced data scientists can make their own AI by writing their own recipes and seamlessly extending H2O Driverless AI with their favorite tools from the rich ecosystem of open-source data science and machine learning libraries.

Seeing Further Down the Visual Cloud Road - IT Peer Network


Almost three years ago, Carnegie Mellon University Prof. Dave Andersen and I announced the Intel Science and Technology Center for Visual Cloud Systems (ISTC-VCS) at the 2016 NAB Show. Along with Prof. Kayvon Fatahalian at Stanford, Dave has led the center and collaborated closely with other academic and Intel Labs researchers to push the boundaries in visual cloud systems. We set out to study and find solutions for some of the key problems with gathering, storing and analyzing video data in large scale distributed environments. With the completion of the center now drawing near, it's time to take stock of the results and to talk of work yet to be done. The center's approach has been to bring together systems researchers and computer vision, AI and graphics researchers to create prototype systems that allow investigation of these topics.

Powerful antibiotic discovered using machine learning for first time


A powerful antibiotic that kills some of the most dangerous drug-resistant bacteria in the world has been discovered using artificial intelligence. The drug works in a different way to existing antibacterials and is the first of its kind to be found by setting AI loose on vast digital libraries of pharmaceutical compounds. Tests showed that the drug wiped out a range of antibiotic-resistant strains of bacteria, including Acinetobacter baumannii and Enterobacteriaceae, two of the three high-priority pathogens that the World Health Organization ranks as "critical" for new antibiotics to target. "In terms of antibiotic discovery, this is absolutely a first," said Regina Barzilay, a senior researcher on the project and specialist in machine learning at Massachusetts Institute of Technology (MIT). "I think this is one of the more powerful antibiotics that has been discovered to date," added James Collins, a bioengineer on the team at MIT. "It has remarkable activity against a broad range of antibiotic-resistant pathogens."