A privately owned company plans to use robotic spacecraft to launch a series of commercial missions to the moon, some 45 years after NASA s last lunar landing, officials said on Wednesday. Cape Canaveral, Florida-based Moon Express is developing a fleet of low-cost robotic spacecraft that can be assembled like Legos to handle increasingly complex missions, founder and Chief Executive Officer Bob Richards said in an interview. Ultimately the company plans to establish a lunar outpost in 2020 and set up commercial operations on the Moon, mining material and returning it to Earth to sell. The initial spacecraft, known as MX-1E,is a similar size and shape to the R2D2 droid from Star Wars, and is slated to fly before the end of the year aboard a Rocket Lab Electron booster, which launches from New Zealand. Google is offering a top prize of $20 million for the first privately funded team to land a spacecraft on the moon; have it fly, drive or hop at least 1,640 feet (500 meters) and relay pictures and video back to Earth.

The data for your sequence prediction problem probably needs to be scaled when training a neural network, such as a Long Short-Term Memory recurrent neural network. When a network is fit on unscaled data that has a range of values (e.g. In this tutorial, you will discover how to normalize and standardize your sequence prediction data and how to decide which to use for your input and output variables. How to Scale Data for Long Short-Term Memory Networks in Python Photo by Mathias Appel, some rights reserved. There are two types of scaling of your series that you may want to consider: normalization and standardization.

Sure, there are lots of tutorials and overviews on gaining the insight you need into picking up machine learning, but many (most?) of them take the long view: get a foundation first, learn the basics next, then learn a bit of complementary theory before getting too far ahead of yourself in practical terms, take a step back, try your hand at a few examples, undertake a project on your own... This is all great advice, and a great approach to learning... well, almost anything. But let's say you're not starting from scratch. Or you don't have the patience to go through all of the motions. Let's say you want to hit the ground running and scramble under pressure to learn everything right now.

"The eyes are the window to the soul," the adage goes, but these days our eyes could be better compared to our ethernet connection to the world. According to a 2006 study conducted by the University of Pennsylvania, the human retina is capable of transmitting 10 million bits of information per second. But for as potent as our visual capabilities are, there's a whole lot that can go wrong with the human eye. Cataracts, glaucoma and age-related macular degeneration (AMD) are three of the leading causes of blindness the world over. Though we may not have robotic ocular prosthetics just yet, a number of recent ophthalmological advancements will help keep the blinds over those windows from being lowered.

Artificial intelligence software could generate highly realistic fake videos of former president Barack Obama using existing audio and video clips of him, a new study [PDF] finds. Such work could one day help generate digital models of a person for virtual reality or augmented reality applications, researchers say. Computer scientists at the University of Washington previously revealed they could generate digital doppelgängers of anyone by analyzing images of them collected from the Internet, from celebrities such as Tom Hanks and Arnold Schwarzenegger to public figures such as George W. Bush and Barack Obama. Such work suggested it could one day be relatively easy to create such models of anybody, when there are untold numbers of digital photos of everyone on the Internet. The researchers chose Obama for their latest work because there were hours of high-definition video of him available online in the public domain.

Siri remains the most popular virtual assistant with 41.4 million monthly active users in the U.S., according to a new report from measurement firm Verto Analytics out this morning, but it has seen a 15 percent decline since last year – or 7.3 million monthly users. In addition, the study found that engagement with Siri has also dropped by nearly half during this period, from 21 percent to 11 percent. Meanwhile, Amazon Alexa usage has been skyrocketing – jumping 325 percent in monthly active users – that is, from 0.8 million to 2.6 million monthly users, as its user engagement also increased from 10 percent to 22 percent during the same time frame. Cortana has seen an increase as well, growing from 0.2 million monthly users in the U.S. to 0.7 million, or a 350 percent increase. Its user engagement tripled, from 19 percent to 60 percent.

American Institute of A.I. offers 12 executive courses and 7 certification programs. Click the courses below to read the course descriptions.

Robots and artificial intelligence will'break the social ladder' and could cost up to 15 million jobs, new research has found. A study found that the increasing automation of jobs will hit poorer workers hardest and will further set back social mobility unless urgent action is taken. The research warns that automation could create a society in which an elite, high-skilled group dominates the higher echelon of society while a lower-skilled, low-income group is left with little opportunity to climb the social ladder. Robots and artificial intelligence will'break the social ladder' and could cost up to 15 million jobs, new research has found (stock image) Robots could take jobs from human workers and potentially spark an employment crisis, the boss of John Lewis warned last month. Sir Charlie Mayfield, 50, said new technologies, such as robots, would create massive changes across industry, with British businesses potentially among the hardest hit.

With just two months to go before Apple is expected to reveal its next smartphone, sources claim that the firm may have hit some problems. The claims suggest that Apple is working'feverishly' to fix software problems with its wireless charging and 3D face recognition systems. If these issues aren't resolved, the flagship iPhone could even launch with these major features disabled, according to the source. New claims suggest that Apple is working'feverishly' to fix software problems with its wireless charging and 3D face recognition systems. A report by Fast Company explains that a'a source with knowledge of the situation' has claimed that engineers and designers at Apple are working with a'sense of panic in the air.'

This course created by Data Weekends, Jose Portilla, and Francesco Mosconi is designed to provide a complete introduction to Deep Learning. It is aimed at beginners and intermediate programmers and data scientists who are familiar with Python and want to understand and apply Deep Learning techniques to a variety of problems. We start with a review of Deep Learning applications and a recap of Machine Learning tools and techniques. Then we introduce Artificial Neural Networks and explain how they are trained to solve Regression and Classification problems. Over the rest of the course we introduce and explain several architectures including Fully Connected, Convolutional and Recurrent Neural Networks, and for each of these we explain both the theory and give plenty of example applications.