Whether you're trying to lose weight, eat healthier, or track your diet for other reasons, there's no truly easy and automatic way to log your food intake. Today's best options are apps that require you to pick the food items you're consuming or manually enter that information. But what if the app knew, without your help, that you'd just spent a half hour crunching on cookies? That's the idea behind the "Diet Eyeglasses" revealed earlier this month at the IEEE Body Sensor Networks conference in San Francisco. The smart glasses have built-in sensors that detect muscle activity related to chewing, which could enable the continuous and unobtrusive monitoring of every morsel users chow down on.

In the era of artificial intelligence (AI), strong computer vision dominates many research efforts in academic labs, tech giants, and startups. We strive to enhance object and image recognition algorithms so that AI systems can accurately recognize people and objects in images and videos, and in more advanced stages, understand what is going on in a scene. Currently, even state-of-the-art object and image recognition algorithms struggle to perfect this--something that comes so effortlessly to humans. Perhaps the problem lies in the way that machines learn to recognize images. What if another type of sensory data (audio in this case) were incorporated into machine learning to enhance its recognition rate?

There is a global trend in the adoption of artificial intelligence in business, highlighting just how important this new technology for business growth is. Still, businesses are faced with the same old dilemmas – security, access and controls. Those are the results of a new survey conducted by Freeform Dynamics, and released by Ipswitch, about the state of artificial intelligence in business. As one might have expected, customer engagement systems is the top application deployment area with 55 per cent of answers (hello, chatbots), followed by process automation and workflow systems (52 per cent), and automated monitoring and management solutions (50 per cent). On the other hand, this new technology brings with it some old pain spots – IT experts seem to be having a tough time trying to assess the full extent of risks automation can bring.

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.