Earlier this month, Bill Gates took the stage at the Recode conference to talk about philanthropy with his wife, Melinda. They discussed mobile payments, contraception and billionaires giving away their fortunes. Then the conversation turned to artificial intelligence, and Gates grinned and swiveled in his giant red leather chair. "Certainly, it's the most exciting thing going on," he said. It's the big dream that anybody who's ever been in computer science has been thinking about."

Editor's Note: This article is part of a special report on the Top 10 Emerging Technologies of 2016 produced by the World Economic Forum. The list, compiled by the Forum's Meta-Council on Emerging Technologies, highlights technological advances its members, including Scientific American Editor in Chief Mariette DiChristina, believe have the power to improve lives, transform industries and safeguard the planet. It also provides an opportunity to debate any human, societal, economic or environmental risks and concerns that the technologies may pose prior to widespread adoption. One of the advantages that CEOs and celebrities have over most people is that they don't need to spend much time handling the uninteresting, time-consuming aspects of daily life: scheduling appointments, making travel plans, searching for the information they want. They have personal assistants, or PAs, who handle such things.

Cozmo is a 179 artificially intelligent robot that can recognize faces and react to human gestures. SAN FRANCISCO – At first glance, the palm-sized toy on the table looks unexceptional, an odd cross between a bulldozer and a forklift. Except that the toy is snoring. Suddenly, it wakes up, motors over to its human inquisitor and lets out a happy squawk as its digital eyes go wide. Made by Anki, the start-up that has found success with its self-driving Anki Drive racing cars, Cozmo goes on sale today for 179 with orders shipping this fall.

The world, and financial markets in particular, were stunned by Britain's vote to exit the EU. The markets were quite confident that Britain would stay in the EU. The S&P 500 rose sharply towards the end of the trading day before the Brexit vote, which some analysts claimed as a vote by investors against the Brexit. In the meanwhile, a unique model that we developed using media sentiment data made the opposite prediction and expected a sharp decline in markets that we saw overnight. During my graduate work at Stanford University, I learned how modern machine learning algorithms can be used to identify complex and deep patterns in noisy datasets – patterns that may be very difficult to detect with less sophisticated algorithms or human intuition.

AI and Machine Learning have emerged as a central aspect of analytics which is applied to multiple domains. AI and Machine Learning, Pattern classifiers and natural language processing (NLP) underpin Sentiment Analysis (SA); SA is a technology that makes rapid assessment of the sentiments expressed in news releases as well as other media sources such as Twitter and blogs. This conference addresses and explains how to extract sentiment from these multiple sources of information and showcases the advances that have taken place in the field of financial innovation. This conference builds on the findings of the six previous highly-regarded conferences on this topic. It highlights the recent developments in the application of AI and machine learning to trading strategies including automatic and algorithmic trading, quantitative fund management.

Due to the recent achievements of artificial neural networks across many different tasks (such as face recognition, object detection and Go), deep learning has become extremely popular. This post aims to be a starting point for those interested in learning more about it. If you already have a basic understanding of linear algebra, calculus, probability and programming: I recommend starting with Stanford's CS231n. The course notes are comprehensive and written well. The slides for each lesson are also available, and even though the accompanying videos were removed from the official site, re-uploads are quite easy to find online.

Now that we have that out of our system, let's take a look at what some well-trained RNNs came up with, when actually trying to create playable magic cards. A simple, evocative, colorshifted Lightning Bolt, into the color that makes the most sense. There's just something enjoyable about the RNN coming up with a Political Tyrant whose main ability is exploit. This A.I. knows its topical humor.

The X Prize Foundation and IBM have officially launched a global artificial intelligence competition that provides participants with the chance to compete for 5 million. The contest, dubbed "IBM Watson A.I. XPRIZE: A Cognitive Computing Competition," was announced this morning at TED2016. The competition invites teams from around the world to harness the power of artificial intelligence (AI) in order to brainstorm a solution to some of the planet's most pressing problems. "X Prize believes that artificial intelligence is the best tool in our toolkit to address the world's grand challenges and biggest problems," said Stephanie Wander, X Prize development associate and lead prize designer, to IFLScience. Which grand problem will the developers have to tackle?

It uses artificial intelligence (AI) to automatically convert data into semantic knowledge. Diffbot uses deep-learning technology to categorize webpage data according to its meaning. Essentially, it provides users with structured knowledge sorted in human-like categories. The web-scrapping company can suck up content from homepages, articles, products, and social network profiles, which can aid both, app developers as well as enterprises, to do competitive analysis and gain insights into consumers. With the use of AI, Diffbot has already surpassed the data bank of Google's Knowledge Graph.

Artificial intelligence (AI) developed by a University of Cincinnati doctoral graduate was recently assessed by subject-matter expert and retired United States Air Force Colonel Gene Lee - who holds extensive aerial combat experience as an instructor and Air Battle Manager with considerable fighter aircraft expertise - in a high-fidelity air combat simulator. The artificial intelligence, dubbed ALPHA, was the victor in that simulated scenario, and according to Lee, is "the most aggressive, responsive, dynamic and credible AI I've seen to date." Details on ALPHA - a significant breakthrough in the application of what's called genetic-fuzzy systems are published in the most-recent issue of the Journal of Defense Management, as this application is specifically designed for use with Unmanned Combat Aerial Vehicles (UCAVs) in simulated air-combat missions for research purposes. The tools used to create ALPHA as well as the ALPHA project have been developed by Psibernetix, Inc., recently founded by UC College of Engineering and Applied Science 2015 doctoral graduate Nick Ernest, now president and CEO of the firm; as well as David Carroll, programming lead, Psibernetix, Inc.; with supporting technologies and research from Gene Lee; Kelly Cohen, UC aerospace professor; Tim Arnett, UC aerospace doctoral student; and Air Force Research Laboratory sponsors. ALPHA is currently viewed as a research tool for manned and unmanned teaming in a simulation environment.