Washington: Scientists have developed a new artificial intelligence (AI) system to monitor people for cardiac arrest while they are asleep without touching them. People experiencing cardiac arrest will suddenly become unresponsive and either stop breathing or gasp for air, a sign known as agonal breathing, said rese-archers at the University of Washington (UW) in the US. A new skill for a smart speaker -- like Google Home and Amazon Alexa -- or smartphone lets the device detect the gasping sound of agonal breathing and call for help. Immediate Cardiop-ulmonary resuscitation (CPR) can double or triple someone's chance of survival, but that requires a bystander to be present. CPR is an emergency procedure that combines chest compressions often with artificial ventilation in an effort to manually preserve intact brain function. Recent research suggests that one of the most common locations for an out-of-hospital cardiac arrest is in a patient's bedroom, where no one is likely around or awake to respond and provide care.

Kurt'The Cyber Guy' Knutsson breaks down how to keep Alexa from listening in. Think of all the things a microphone can pick up: voices, noises, whispers, conversations, arguments, confessions – even people alone, in a room, mumbling to themselves. Think of all the things you say in a private space, all the weird things you do. Once those sounds have been saved, that data can be stored, edited, and manipulated and shared. Now, think of all the things a camera can see, record, save, and share with who knows who.

The term artificial intelligence (AI) refers to computing systems that perform tasks normally considered within the realm of human decision making. These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications. AI systems leverage this knowledge repository to make decisions and take actions that approximate cognitive functions, including learning and problem solving. AI, which was introduced as an area of science in the mid 1950s, has evolved rapidly in recent years. It has become a valuable and essential tool for orchestrating digital technologies and managing business operations.

With AI's enormous potentials and amidst the growing demand for high-tech banking services from tech-savvy customers, a number of financial institutions are leaving no stones unturned in their quest for market leadership in the era of automation. Take for instance the highly important area of enhanced customer experience. Financial institutions have been harnessing the power of AI to deliver efficient and personalized services to achieve higher client satisfaction level and, more importantly, win customer loyalty. Banks are now more empowered to predict customer behavioural patterns by leveraging innovative AI tools-- a capability that allows for the delivery of customized products and services. In terms of customer interaction, financial institutions are utilizing'chatbots' applications acting as customer service agents.

In the new'Child's Play' film, the wicked Chucky doll is reconceived as an A.I. assistant.

With people examining further into the universe of innovation, artificial intelligence or AI is presently ubiquitous. Interestingly, albeit artificial intelligence is an innovation of interest at this moment, the idea has been around for over seven-plus decades now. With increased awareness about the transformative intensity of AI, the adoption of AI is presently being seen across numerous enterprises. From enormous banks like HDFC Bank to e-commerce business players like Pepperfry, AI is being utilized for a large variety of use cases. Eyeballing is of fundamental significance in the credit decision procedure, and the bot emulates a human by eyeballing the client demographics for the individuals who have applied for advances against the already existing base.

This paper studies recommender systems with knowledge graphs, which can effectively address the problems of data sparsity and cold start. Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations. Though these methods have been shown quite effective, they lack good explanations, which are critical to recommender systems. In this paper, we take a different path and propose generating recommendations by finding meaningful paths from users to items. Specifically, we formulate the problem as a sequential decision process, where the target user is defined as the initial state, and the walks on the graphs are defined as actions. We shape the rewards according to existing state-of-the-art methods and then train a policy function with policy gradient methods. Experimental results on three real-world datasets show that our proposed method not only provides effective recommendations but also offers good explanations .

Building multi-domain AI agents is a challenging task and an open problem in the area of AI. Within the domain of dialog, the ability to orchestrate multiple independently trained dialog agents, or skills, to create a unified system is of particular significance. In this work, we study the task of online posterior dialog orchestration, where we define posterior orchestration as the task of selecting a subset of skills which most appropriately answer a user input using features extracted from both the user input and the individual skills. To account for the various costs associated with extracting skill features, we consider online posterior orchestration under a skill execution budget. We formalize this setting as Context Attentive Bandit with Observations (CABO), a variant of context attentive bandits, and evaluate it on simulated non-conversational and proprietary conversational datasets.

Appliances, even large ones, are getting in on the action. But that doesn't mean you need to toss your old "dumb" stuff and buy brand new smart devices. Air conditioners are certainly one type of appliance that is heading down the smart path, but if you have a window or wall unit you already love (or can't afford to replace), you might consider turning your dumb unit into a smart A/C. With a few tweaks, you can convert the unit you have into a cooling solution you can turn on and off remotely with an app or through your favorite smart home ecosystems, such as Google Assistant or Alexa. A window or wall unit (or a portable A/C) works just fine when you manually turn it on with buttons, so why is it even necessary to make it smart?

We trust smart assistants like Alexa, Siri, and Google Assistant to control so many things in our homes--door locks, lighting, security cameras--but should we allow them to light real-flame candles with a simple command? That's the question I found myself pondering while I was testing the Ludela Perfect Pillar smart candle, and the answer I settled on was, "mostly, no." The Ludela Perfect Pillar is a remote-controlled candle designed with safety in mind. It ignites using a canister of liquid paraffin, but only when a specific sequence of buttons is pressed on the remote. The sequence is simple to remember but hard to guess, so I didn't feel uncomfortable leaving the remote within my children's reach.