The command module was the home of all three astronauts during most of the mission, and the only part to return intact to Earth. It sits atop the service module, which is accessible by a dock shown in the 3D model. The astronauts can then traverse the service module and access the lunar module via a docking tunnel. "The command module had many, many hidden nooks and crannies that are really hard to see," says Vincent Rossi, the senior 3D program officer. It's also composed of reflective surfaces that make scanning tough.

Microsoft has a brand-new conference, exclusively for data scientists, big data engineers, and machine learning practitioners. The Microsoft Data Science Summit, to be held in Atlanta GA, September 26-27, will feature talks and lab sessions from Microsoft engineers and thought leaders on using data science techniques and Microsoft technology, applied to real-world problems. Other topics of interest include building with bot frameworks, deep learning, Internet of Things applications, and in-depth Data Science topics. To register for the conference, follow the link below. Discounted day passes to Microsoft Ignite on September 28-29 are also available to Microsoft Data Summit registrants.

When you first heard of the term convolutional neural networks, you may have thought of something related to neuroscience or biology, and you would be right.

Expert publishing blog opinions are solely those of the blogger and not necessarily endorsed by DBW. Last month, Mike Shatzkin wrote a blog post titled "Full text examination by computer is very unlikely to predict bestsellers," in which he described how the claims of the creation of an algorithm that predicts bestsellers, as outlined in a new book The Bestseller Code: Anatomy of the Blockbuster Novel, are impossible. While I agree in theory with Shatzkin that an algorithm alone cannot predict whether a book will be a bestseller or not, that isn't precisely what The Bestseller Code claims, nor what our experience working with machine learning at Intellogo defines. What we aim to do is identify similar tones, moods, topics and writing styles to those books that are topping bestseller lists--as we can only do through algorithms--and, in this way, better understand the reading audiences' desires. Machine learning allows us to do just that.

Get a quick introduction to data science from Data Science for Beginners in five short videos. This video series is helpful if you're interested in doing data science - or work with people who do data science - and you want to start with some basic concepts. This first video is about the kinds of questions that data science can answer. Data science predicts answers to questions using a number or category. To get the most out of the series, watch them in order.

It's being dubbed the Fourth Industrial Revolution: the explosion of robots, machines, algorithms and artificial intelligence (AI) in the workplace is coming. There's been a lot of recent speculation about how robotics and automation will change the landscape of employment, and the professions that could become obsolete as a result. We're all familiar with those annoying "unexpected item in the bagging area" self-service supermarket checkouts, or the big robots used on the production line in factories making cars and other complex products. In the supermarket, now just one checkout assistant can manage 6 or more tills, or cars and machines can be assembled safely, with every one being turned out to the same standard. So what jobs will be next on the chopping block in this technological revolution? By and large, the main professions under threat are ones that involve repetitive tasks – that could be inputting data, preparing spreadsheets and reports and other administrative duties, retail jobs, manufacturing and even some more complex analytical roles that could be better served by an algorithm doing all the hard work.

Move over, social media and mobility: Silicon Valley has a next big thing, John Markoff writes, and it's A.I. and robots. It is useful to think of them as part of the same thing, since many robots are autonomous machines programmed for decision making based on A.I. The movement can be thought of as a spread of computing intelligence everywhere, on wheels and wings, in your pocket and all through your house. That's a big enough idea to fund scores of companies, and quite possibly set up the next Silicon Valley boom. Yet it's worth asking how much of this is reality and how much is wishful thinking.

The world is going through a new wave of automation: across organisations areas are identified to apply machine intelligence to automate tasks. This means not only cost savings and increasing efficiency for companies, but an opportunity to learn over time and make an organisation sustainably smarter. While we're far away from real Artificial Intelligence (AI) the speed of innovation in the areas of Machine Learning, Deep Learning and Natural Language Processing is very high. As outlined in this quarter's McKinsey review after predictable physical work, data collection and processing are most susceptible to be automated next by adapting currently demonstrated technology. The recruitment space is prime for automation; the hiring process necessitates the screening of a high volume of candidates.

I look forward to the Sandbox Summit every year. Hosted in Boston at MIT, this two day conference is smaller, focused and connects a great blend of experts across kids TV and digital media, emerging technology, education and toy manufacturing. This year was no different! With so many interesting talks and panel, I thought I'd share my takeaways from three of the talks. RJ Mical is a game pioneer who helped invent the Amiga Computer, was a co-creator of the Atari Lynx and currently holds one of the most awesome job titles in the world: Director of Gaming at Google. Mical's talk focused on his vision for the future of Machine Intelligence.

Is Honda's walking robot Asimo marrying Pepper, the chattering robot from SoftBank? Automaker Honda Motor Co. and internet company SoftBank said Thursday they will work together on artificial intelligence to develop products with sensors and cameras that can converse with drivers. Asimo, first shown in 1996, walks, runs, dances and grips things. Pepper, which went on sale last year, doesn't have legs but is programmed to recognize mood swings in people it interacts with. Major automakers and technology companies are interested in robotics to improve driving safety and comfort.