Just over fifty years ago, a French journalist, Jean-Jacques Servan-Schreiber, published his book, Le Défi Américain (aka The American Challenge, 1967). It presented the United States and Europe as engaged in a silent economic war. In that war, he wrote, Europe was being completely outclassed on all fronts in dealing with the Third Industrial Revolution (electronics, information technology, and automation). The invading industrial armies of the day--1960s giants such as General Motors and IBM--were becoming dominant in Europe because of stronger and more flexible management techniques, technological tools, and research capacity. The book became an international hit, selling an unprecedented 600,000 copies in France alone.

A data scientist has designed an algorithm that predicts which Game of Thrones characters are most likely to die in season 8. The final season of Game of Thrones may be a year away, but a lot of fans are left wondering what to expect and more specifically, which characters are going to die. Leave it up to a numbers and science guy to figure that one out. Taylor Larkin, a data scientist at Boston-based DataRoot, went through an extensive Thrones wiki database to analyze the traits of nearly 2,000 characters. Using automated machine learning, Larkin didn't cut any corners and factored in everything from gender, age, house, family lineage and more.

A transparent skull allows people to literally peer into the head of Sophia, one of the most sophisticated humanoid robots yet built. Hong Kong firm Hanson Robotics created Sophia with an advanced neural network and delicate motor controls that allow the machine to emulate human social interactions. Rubberized faces stretch into familiar shapes, driven by tiny motors and a distant version of artificial intelligence--is this the future? Meet Sophia, a social robot created by former Disney Imagineer David Hanson. Modeled in part after Audrey Hepburn and Hanson's wife, the robot was built to mimic social behaviors and inspire feelings of love and compassion in humans.

The inputs were 96x96 images, and the target outputs were 30-value vectors indicating x,y pairs for 15 facial keypoints. We had to design a CNN from scratch to perform the task. My architecture was three convolutional layers, each followed by a max pooling layer with dropout, then a two-layer dense regression network at the end. Training was done on an EC2 p2xlarge GPU instance, and took around 10 minutes to perform 250 epochs (though there was a lot of trial and error so all told I spent a few hours on training different architectures). The dataset came from this Kaggle competition!

My initial uncharitable take was: College profs need to understand product development is harder than they think. A number of points here indicate a lack of progress on general AI by pointing to product decisions that would be present no matter the implementation. He seems to then use this as a rallying call to encourage going back to knowledge engineering circa late 80's early 90's? I'm going to guess i'm missing something. Yes general ai is far away.

When Prince Harry and Meghan Markle say "I do" at their royal wedding, online viewers tuning into the Sky News stream will not have to guess the names of international celebrities and British nobility in attendance. Instead, the U.K. broadcaster will use artificial intelligence to identify famous guests as they make their grand entrances at St. George's Chapel at Windsor Castle -- displaying the invitees' names and details about how they are connected to the royal couple. Dubbed "Who's Who Live," Sky News announced the livestream service last week in partnership with Amazon.com and several data and engineering firms. As the 600 guests enter the chapel, Sky News will highlight notable attendees using Amazon Rekognition, a cloud-based technology that can recognize and compare faces in images and video using artificial intelligence. Along with identifying the wedding guests, the livestream service will also show facts about them, Sky News said, using captions and on-screen graphics through the company's app.

For its updated news application, Google is doubling down on the use of artificial intelligence as part of an effort to weed our disinformation and help users get viewpoints beyond their own "filter bubble." Google chief Sundar Pichai, who unveiled the updated Google News earlier this month, said the app now "surfaces the news you care about from trusted sources while still giving you a full range of perspectives on events." It marks Google's latest effort to be at the center of online news and includes a new push to help publishers get paid subscribers through the tech giant's platform. According to product chief Trystan Upstill, the news app "uses the best of artificial intelligence to find the best of human intelligence -- the great reporting done by journalists around the globe." While the app will enable users to get "personalized" news, it will also include top stories for all readers, aiming to break the so-called filter bubble of information designed to reinforce people's biases.

It's a lot more involved, but the Easy21 assignment from David Silver's RL course is a very thorough intro to RL - it does require going through requisite material in the course though. This is in opposition to putting a cross-entropy loss on a CNN and training it on MNIST - courses/practicals will vary on how practically they deal with this task vs. how much they go into the underlying theory.

In this episode we are reaching out to our community to come up with a use case so we can show Nigel off TOKEN SALE IS NOW LIVE: https://kimera.ai/ Kimera Systems is an advanced artificial intelligence company that has developed the world's first Artificial General Intelligence. AGI is different from other artificial intelligence, because it can think and reason the way humans do. During Kimeras travel around the world, we will promote our Initial Coin Offering (ICO) to help bring this technology to the world. To learn more visit http://kimera.ai