What is Artificial Intelligence (AI)? Are you intrigued by the sheer ease with which Facebook tags your friends and family when you post a photo? Or how Apple's Siri, Amazon's Alexa & Microsoft's Cortana help you find information, give you direction and add events to your calendar? How does Outlook know that some emails should go into your Clutter folder when you never marked them as spam? All these are powered by Artificial Intelligence technologies.

WASHINGTON – On his first day at work as a security guard, Steve was greeted warmly, drawing attention from passers-by, including some taking selfies with him at the tony retail-residential complex he patrolled. Then he fell into the fountain. Steve was a security robot employed by the Washington Harbour center in the Georgetown district of the U.S. capital. According to some tech watchers, robots like Steve herald a new era for intelligent machines assisting in crime prevention and law enforcement. Steve's mishap in mid-July set of a flurry of reaction on social media, with some joking that the robot had "drowned" or committed suicide.

Young Instagram users are now spending over half an hour on the photo sharing app every day. The Facebook owned app revealed users under 25 are on the app for 32 minutes on average daily, while older users spend 25 minutes each day using it. The firm released the latest stats a year after it launched Instagram Stories in its ongoing battle with Snapchat. The Facebook owned app revealed users under 25 are on the app for 32 minutes on average daily, while older users spend 25 minutes each day using it. They show that the younger users now spend three percent of their waking hours using the app.

The US Secret Service is going to use drones with infrared cameras to boost security at Donald Trump's Bedminster golf club. President Trump is to enjoy what is being described as an'extended stay' at the property in New Jersey after a chaotic couple of weeks at the White House which has seen some of his head honchos ousted from government. While the agency refused to answer questions on the specifics of the unmanned aircraft, but hinted it could pave the way for them to be used on a more regular basis in security operations involving the President. President Donald Trump and first lady Melania Trump leave the US Women's Open Championship at Trump National Golf Club on July 16, 2017 in Bedminster, New Jersey As well as the cameras to look out for potential threats, the Secret Service said it was working to incorporate several of the airborne vehicles. Officials will have to warn residents in houses surrounding the Trump National Golf Course that drones will be monitoring the area.

Amazon has a problem, and that problem is humans. Amazon needs humans, lots of them. But humans, as we all know, are the most unreasonable part of any business, constantly demanding things like lights and air. So Amazon has turned to robots (over 100,000 of them) for doing tasks like moving things around in a warehouse. But it's proving to be much more difficult to get the robots to do some other tasks.

Wireless systems perform rate adaptation to transmit at highest possible instantaneous rates. Rate adaptation has been increasingly granular over generations of wireless systems. The base-station uses SINR and packet decode feedback called acknowledgement/no acknowledgement (ACK/NACK) to perform rate adaptation. SINR is used for rate anchoring called inner look adaptation and ACK/NACK is used for fine offset adjustments called Outer Loop Link Adaptation (OLLA). We cast the OLLA as a reinforcement learning problem of the class of Multi-Armed Bandits (MAB) where the different offset values are the arms of the bandit. In OLLA, as the offset values increase, the probability of packet error also increase, and every user equipment (UE) has a desired Block Error Rate (BLER) to meet certain Quality of Service (QoS) requirements. For this MAB we propose a binary search based algorithm which achieves a Probably Approximately Correct (PAC) solution making use of bounds from large deviation theory and confidence bounds. In addition to this we also discuss how a Thompson sampling or UCB based method will not help us meet the target objectives. Finally, simulation results are provided on an LTE system simulator and thereby prove the efficacy of our proposed algorithm.

The analysis of data sets arising from multiple sensors has drawn significant research attention over the years. Traditional methods, including kernel-based methods, are typically incapable of capturing nonlinear geometric structures. We introduce a latent common manifold model underlying multiple sensor observations for the purpose of multimodal data fusion. A method based on alternating diffusion is presented and analyzed; we provide theoretical analysis of the method under the latent common manifold model. To exemplify the power of the proposed framework, experimental results in several applications are reported.

Correct inference of genetic regulations inside a cell is one of the greatest challenges in post genomic era for the biologist and researchers. Several intelligent techniques and models were already proposed to identify the regulatory relations among genes from the biological database like time series microarray data. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. In this paper, Bat Algorithm (BA) is applied to optimize the model parameters of RNN model of Gene Regulatory Network (GRN). Initially the proposed method is tested against small artificial network without any noise and the efficiency is observed in term of number of iteration, number of population and BA optimization parameters. The model is also validated in presence of different level of random noise for the small artificial network and that proved its ability to infer the correct inferences in presence of noise like real world dataset. In the next phase of this research, BA based RNN is applied to real world benchmark time series microarray dataset of E. coli. The results prove that it can able to identify the maximum number of true positive regulation but also include some false positive regulations. Therefore, BA is very suitable for identifying biological plausible GRN with the help RNN model.

If you sit and think about it for a moment, a made up string of characters is the only thing keeping the world's criminal population from commandeering all your assets. Every online account you have is secured by nothing but a string of characters that anyone can type in. To make matters even worse, you're not supposed to use the same password for multiple online accounts. Of course all these different passwords you're supposed to memorize have to: There is no way you're going to remember 10 passwords that meet each of the above criteria for the 15-20 websites you log into for various reasons. This means we're all supposed to store a big list of passwords somewhere that we reference every time we login to an online account.

The sea and ocean environment has long been explored using some of the most sophisticated technology tools. Today's technologies make it child's play to explore natural environments under the sea. The American Goddard Space Flight Center, which belongs to NASA, relies on machine learning to track microscopic algal growth in oceans. The microalgae, which float on the water's surface, are largely responsible for producing oxygen, an element essential for supporting life. Many underwater observations rely on advanced detection technologies.