The significant advancements made over the last decade in the abilities and cost of parallel computing, algorithms, big data and the transfer to the cloud is expected to bring artificial intelligence (AI) out of laboratories and into the mainstream world. AI is broadly defined as any intelligence demonstrated by machines or software. If a machine is capable of doing more than processing data, for example deriving knowledge from it, and augmenting human decision making, it can be considered as AI. According to data published by Grand View Research, the global artificial intelligence market is projected to reach USD 35.87 billion by 2025, while growing at a CAGR of 57.2 percent. A report by Goldman Sachs emphasized the sweeping changes AI is already causing across a variety of sectors, including advertising (programmatic ad buying), retail (customized recommendations) and investing.

The most exciting thing about smart speakers is that they are all so utterly imperfect. Each of the mainstream examples – Amazon's Echos, the Google Home, Sonos's wide range and the new Apple HomePod – packs within it stunning technology that would have been unimaginable just a couple of years ago. But they're also full of downsides, making choosing one a matter of deciding what you want, not simply settling on the best. Deciding is a matter of picking which things you want – and which things you definitely don't. Some sound good, but are terrible at talking back to you.

Salesforce software computationally qualifies and ranks leads. Calendar managers visually and acoustically suggest scheduling options and priorities. Practically everything a digitally-dependent knowledge worker sees, hears, or swipes can become a recommendation. That makes simple and engaging user experience design for management key. For Chief Marketing Officers to brand managers alike, the experience of identifying actionable analytic insight will come to resemble binge-watching on Netflix, shopping on Amazon, or swiping left (or right) on Tinder -- an exercise in selecting customized and contextualized options determined by data-enriched algorithms. Analytics-oriented marketing leaderships must recognize that their best people, just like their best customers, want intelligent exposure to meaningful choice.

And for soccer (er, football) fans in the US, Fox Sports will be the TV network responsible for bringing them all 64 games from Russia, at least if they want to watch them in English. But, beyond its broadcast offerings, Fox Sports wants to keep people engaged in the competition in different ways. Aside from its partnership with Twitter, which comes in the form of a show that'll stream live from Russia, Fox Sports has teamed up with IBM to build the ultimate World Cup highlight machine. Powered by Watson artificial intelligence, this video hub lets you create on-demand clips from every FIFA World Cup tournament dating back to 1958. Fox Sports says there are 300 archived matches that Watson is capable of analyzing, which you can filter out by World Cup year, team, player, game, play type or any combination of these.

All three a virtual tie, but each had questions they couldn't answer. Tune in to find out where Apple, Google and Amazon fell down. And it doesn't even once say, "Here's what I found on the Web," to make you read the information on websites. But is it really smarter when it comes to responding to our music-related commands than its rivals Amazon Echo and Google Home, which dominate the smart speaker market? We decided to find out, posing 40 music questions to all three, and then played a bonus round with 10 requests to play a song based on sample lyrics from the tune. That last challenge proved to be the tie breaker.

In this April 12, 2018, photo, a visitor watches a Chinese company displaying a Chinese-made industrial robot demonstration on processing soybean at the International soybean exhibition in Shanghai. China says it will narrow its trade surplus with the United States but rejects pressure to change technology development tactics seen as a path to prosperity and its rightful place as a global leader. Beijing highlighted the sensitivity of the issue with its threat to scrap deals aimed at settling a sprawling trade dispute with Washington if President Donald Trump's threatened tariff hike on $50 billion of Chinese technology goes ahead.

Machine learning is currently dominated by largely experimental work focused on improvements in a few key tasks. However, the impressive accuracy numbers of the best performing models are questionable because the same test sets have been used to select these models for multiple years now. To understand the danger of overfitting, we measure the accuracy of CIFAR-10 classifiers by creating a new test set of truly unseen images. Although we ensure that the new test set is as close to the original data distribution as possible, we find a large drop in accuracy (4% to 10%) for a broad range of deep learning models. Yet more recent models with higher original accuracy show a smaller drop and better overall performance, indicating that this drop is likely not due to overfitting based on adaptivity. Instead, we view our results as evidence that current accuracy numbers are brittle and susceptible to even minute natural variations in the data distribution.

Once upon a time Elon Musk was our era's real-life Tony Stark, a billionaire Iron Man streaking across the sky with technology to save the planet and take us to Mars. Reusable rockets, electric cars, solar power, he did them all, taking time out to advise Robert Downey Jr on how to play the Marvel superhero on a trajectory seemingly forever up, up, up. Now Musk, 46, is literally and figuratively in a long, dark hole. He is tunneling beneath Los Angeles to create a prototype underground transit network which, he says, can save the city from traffic congestion. But a recently released video of the tunnel plus a map of potential lines coincided with a dark turn in Musk's fortunes and reputation, creating the impression of a man in a labyrinth of his own making.

An attacker just needs to play ultrasonic sounds through a built-in speaker of a target computer or by using a speaker in its proximity. The principle is simple, the technique leverages specially crafted acoustic signals to cause significant vibrations in the HDDs components that could cause severe damage. Modern HDDs use shock sensors to prevent the head crash, but the team of researchers has demonstrated that sonic and ultrasonic sounds could cause false positives in the shock sensor, causing a drive to park the head in a wrong position. "We created and modeled a new feedback controller that could be deployed as a firmware update to attenuate the intentional acoustic interference. Our sensor fusion method prevents unnecessary head parking by detecting ultrasonic triggering of the shock sensor" reads the paper published by the experts.

Is Facebook pumping up the volume on what AI can mean to the future of music? You can decide after having a look at what Facebook AI Research scientists have been up to. A number of sites including The Next Web have reported that they unveiled a neural network capable of translating music from one style, genre, and set of instruments to another. You can check out their paper, "A Universal Music Translation Network" by authors Noam Mor, Lior Wolf, Adam Polyak, Yaniv Taigman, Facebook AI Research. The paper is on arXiv.