One of the best ways to diagnose a heart attack is to use an electrocardiograph to measure the electrical output from the heart. A standard ECG records the electrical signal from 12 different leads attached to different parts of the patient's body. These signals reveal the electrical behavior of the heart in various ways. Cardiologists have long known that the signals from some of these leads are more useful diagnostically than others when it comes to heart attacks. But interpreting the data is hard.

Many researchers have co-opted powerful graphics processing units, or GPUs, to run climate models and other scientific programs, while tech and financial giants use large banks of these processors to train machine-learning algorithms. They all have video-game players to thank for the emergence of these workhorse processors: It was gamers who stoked the original demand for chips that could do the massive amounts of parallel number crunching required to produce rich graphics quickly enough to keep up with fast-paced action. By 1995, movies like Pixar's Toy Story, the first full-length digitally animated movie, had demonstrated the potential of high-quality computer animation. But gamers drove the technology in a very specific direction. Pixar had created Toy Story's graphics by slowly rendering each frame individually and then stitching it all together.

NPR-Marist poll finds that almost half of online shoppers go to Amazon first when they look for an item. Other search engines know what customers look for but Amazon knows what they ultimately buy.

Kroger's efforts to play catch-up with Amazon in grocery delivery have taken it to the fringes of the "last mile" and a new partnership with an autonomous-driving startup that was hatched by guys who were involved in getting Google's driverless-car operation off the ground. It's the latest indication that the commercial logistics business is likely to have much more to do with shaping the early days of self-driven automotive transportation than the consumer side is. The Cincinnati-based supermarket chain, largest in the United States, said that it will begin piloting an "on-road, fully autonomous delivery experience" with Nuro, maker of the world's first unmanned road vehicle, in a city that the retailer hasn't yet announced, beginning this fall. The partnership will allow customers to place same-day delivery orders through Kroger's ClickList digital ordering system and Nuro's app. During the test, orders will be delivered by Nuro's fleet of autonomous vehicles, with human safety drivers to start out.

The US is going to start taking rogue drones out of the air… by launching its own drones to smash into them. Attacks using consumer drones are on the rise. In 2017, ISIS forces in Mosul attacked US-backed Iraqi troops with dozens of consumer drones dropping grenades, and earlier this year a swarm of small drones attacked a Russian airbase in Syria. Such attacks are difficult to counter with existing weapons.

Google devices and apps have experienced serious outages that lasted for more than 12 hours and affected millions of users. The issue affected Google Home and Google Home Mini – speakers that respond to voice commands – as well as Chromecast – a device that plugs into a television and allows people to watch video content. Users were angry at both the length of the outage and the lack of information from Google about it, once it had been identified. Google has not given a reason why these devices went down, only apologising for the service problems and identifying a fix for the issues. The bug meant that when some Google Home owners asked a question of their speaker, it responded: "There was a glitch, try again in a few seconds."

Two years ago, Sanjaya Wijeratne--a computer science PhD student at Wright State University--noticed something odd in his research. He was studying the communication of gang members on Twitter. Among the grandstanding about drugs and money, he found gang members repeatedly dropping the emoji in their tweets. Wijeratne had been working on separate research relating to word-sense disambiguation, a field of computational linguistics that looks at how words take on multiple meanings. The use of jumped out as a brand new problem.

Big banks and financial companies have started to offer banking through virtual assistants -- Amazon's Alexa, Apple's Siri, and Google's Assistant -- in a way that will allow customers to check their balances, pay bills and, in the near future, send money just with their voice. And with the rapid adoption of Zelle, a bank-to-bank transfer system, it soon could be possible to send money to friends or family instantly with voice commands. But the potential to do such sensitive tasks through a smart speaker raises security concerns. Virtual assistants and smart speakers are still relatively new technologies, and potentially susceptible to being exploited by cyber criminals. Regional banking giant U.S. Bank is the first bank to be on all three services -- Alexa, Siri and Assistant.

Machine learning has advanced radically over the past 10 years, and machine learning algorithms now achieve human-level performance or better on a number of tasks, including face recognition,31 optical character recognition,8 object recognition,29 and playing the game Go.26 Yet machine learning algorithms that exceed human performance in naturally occurring scenarios are often seen as failing dramatically when an adversary is able to modify their input data even subtly. Machine learning is already used for many highly important applications and will be used in even more of even greater importance in the near future. Search algorithms, automated financial trading algorithms, data analytics, autonomous vehicles, and malware detection are all critically dependent on the underlying machine learning algorithms that interpret their respective domain inputs to provide intelligent outputs that facilitate the decision-making process of users or automated systems. As machine learning is used in more contexts where malicious adversaries have an incentive to interfere with the operation of a given machine learning system, it is increasingly important to provide protections, or "robustness guarantees," against adversarial manipulation. The modern generation of machine learning services is a result of nearly 50 years of research and development in artificial intelligence--the study of computational algorithms and systems that reason about their environment to make predictions.25 A subfield of artificial intelligence, most modern machine learning, as used in production, can essentially be understood as applied function approximation; when there is some mapping from an input x to an output y that is difficult for a programmer to describe through explicit code, a machine learning algorithm can learn an approximation of the mapping by analyzing a dataset containing several examples of inputs and their corresponding outputs. Google's image-classification system, Inception, has been trained with millions of labeled images.28 It can classify images as cats, dogs, airplanes, boats, or more complex concepts on par or improving on human accuracy. Increases in the size of machine learning models and their accuracy is the result of recent advancements in machine learning algorithms,17 particularly to advance deep learning.7 One focus of the machine learning research community has been on developing models that make accurate predictions, as progress was in part measured by results on benchmark datasets. In this context, accuracy denotes the fraction of test inputs that a model processes correctly--the proportion of images that an object-recognition algorithm recognizes as belonging to the correct class, and the proportion of executables that a malware detector correctly designates as benign or malicious. The estimate of a model's accuracy varies greatly with the choice of the dataset used to compute the estimate.