It's fun to buy a drone from a store, but perhaps more satisfying to build one from scratch. Intel in December will start shipping a fully loaded drone kit to let you do just that, with all the parts including the rotors, software, 3D camera and flight controller. Intel's Aero Ready to Fly Drone kit will go on sale on the company's website. An Intel spokeperson couldn't immediately provide a price. But it won't be cheap -- likely more than $600.

In the previous blog post Using Keras and Deep Q-Network to Play FlappyBird we demonstrate using Deep Q-Network to play FlappyBird. However, a big limitation of Deep Q-Network is that the outputs/actions are discrete while the action like steering are continuous in car racing. An obvious approach to adapt DQN to continuous domains is to simply discretize the action space. However, we encounter the "curse of dimensionality" problem. For example, if you discretize the steering wheel from -90 to 90 degrees in 5 degrees each and acceleration from 0km to 300km in 5km each, your output combinations will be 36 steering states times 60 velocity states which equals to 2160 possible combinations. The situation will be worse when you want to build robots to perform something very specialized, such as brain surgery that requires fine control of actions and naive discretization will not able to achieve the required precision to do the operations.

Artificial intelligence has become more of a philosophy than a programming tool at Facebook. Laced across the company's products, it holds the power to analyze data at the massive scale required by a social network connecting a quarter of the world's population. In a speech today at Web Summit, Facebook CTO Mike Schroepfer laid out a vision for the role artificial intelligence and machine learning will play in the company's ambitions to improve global connectivity, technology accessibility, and human computer interaction. "People want to stay connected and close to other people, so whatever is the best current technology to deploy that is the business we want to be in," said Schroepfer. Large companies like Facebook play an incredibly important role in the artificial intelligence and machine learning ecosystem.

In this blog post I will delve into the brain and explain its basic information processing machinery and compare it to deep learning. I do this by moving step-by-step along with the brains electrochemical and biological information processing pipeline and relating it directly to the architecture of convolutional nets. Thereby we will see that a neuron and a convolutional net are very similar information processing machines. While performing this comparison, I will also discuss the computational complexity of these processes and thus derive an estimate for the brains overall computational power. I will use these estimates, along with knowledge from high performance computing, to show that it is unlikely that there will be a technological singularity in this century. This blog post is complex as it arcs over multiple topics in order to unify them into a coherent framework of thought. I have tried to make this article as readable as possible, but I might have not succeeded in all places.

Jean Brillat-Savarin was a 19th-century French lawyer famed for his writings on gastronomy. In his most famous work, he said: "Dis-moi ce que tu manges, je te dirai ce que tu es." Or "Tell me what you eat and I will tell you what you are." This idea--that you are what you eat--has become increasingly popular. Since Brillat-Savarin's time it has been used as the title of various cookbooks and health guides; for some it is a way of life.

They say what happens in Vegas stays in Vegas, but I keep telling everyone I know about the remarkable innovations I saw at IBM World of Watson 2016 conference, held from Oct. 24 to 27 at beautiful Mandalay Bay, where I was among the 17,000 attendees. As I was "welcomed to the World of Watson," I learned that Watson (yes, the computer that was on Jeopardy) is IBM's researchers' vision "to design an intelligent system that brings man and machine together to create a better world." If that sounds like a utopian fantasy, prepare to be amazed at how real that vision has become: Watson is changing how doctors cure disease, how companies analyze their social media footprints, and how financial services firms adapt to ever-changing regulations. I could write an entire book on all that Watson has to offer, but my focus here is on Watson's ability to help financial services firms meet compliance demands more efficiently and with less cost – a much needed innovation as firms spend $99 billion on addressing compliance, thus limiting their ability to invest in growth, according to Marc Andrews, VP of Industry Analytics Solutions for IBM. If you're scratching your head at why regulatory compliance costs are so high, picture this: Linda, a trader at a high-profile brokerage firm, receives a bad performance review from her supervisor.

The idiom "never judge a book by its cover" warns against evaluating something purely by the way it looks. And yet book covers are designed to give readers an idea of the content, to make them want to pick up a book and read it. Good book covers are designed to be judged. And humans are quite good at it. It's relatively straightforward to pick out a cookery book or a biography or a travel guide just by looking at the cover.

You might expect the operating theatre to be one of the last places you'd find robotics in action but, increasingly, you'd be wrong. The OT is typically the most labour-intensive and expensive part of a hospital -- which, in this age of spiraling health costs, makes it a priority for any cost-savings that can be achieved through systemisation and standardisation. Robotic surgery, or robot-assisted surgery, has the advantage that it allows doctors to perform many types of complex procedures with more precision, flexibility and control than they could with conventional techniques. Given the speed at which robotics is advancing, how long will it be before robots start making all the decisions on surgery without the need for human control or intervention? OK, you say, that's fine where standard and predictable procedures are required.

Baidu has launched Melody, an AI-powered conversational bot designed to provide relevant information to doctors to assist with recommendations and treatment options. Melody incorporates advanced deep learning and natural language processing (NLP) technologies developed by Baidu. Melody integrates with Baidu Doctor, an app that Baidu launched in China in 2015. Andrew Ng, chief scientist, Baidu, said: "Melody is designed to help both doctors and patients. By focusing on the medical-assistant vertical, we've built a conversational bot that can give highly-customized and situation-appropriate responses to a patient's query."

Why job security won't exist in the age of'superintelligence' and that's OK Artificial intelligence (AI) is a repeatedly misused term. Coined in 1956 by John McCarthy, it was originally intended to define an independent machine agent that can take actions to maximize success toward a particular goal, with human-like functions such as learning and problem solving. AI can be broadly categorized as ANI (artificial narrow intelligence), AGI (artificial general intelligence) and ASI (artificial superintelligence). Almost all of the AI systems we see today align under ANI -- e.g., IBM Watson, Deep Blue, a calculator, even the device you're reading this from all fall into that category. All are built to perform specific functions, but are not quite at a human level.