Widely available earbuds equipped with sensors (also known as earables) can be combined with a sleep event detection algorithm to offer a convenient alternative to laborious clinical tests for individuals suffering from sleep disorders. Although various solutions utilizing such devices have been proposed to detect sleep events, they ignore the fact that individuals often share sleeping spaces with roommates or couples. To address this issue, we introduce DreamCatcher, the first publicly available dataset for wearer-aware sleep event algorithm development on earables.

Google search queries and social media posts provide a means of peering into the ideas, concerns, and expectations of millions of people around the world. Using the right web-scraping bots and big data analytics, everyone from marketers to social scientists can analyze this information and use it to draw conclusions about what's on the mind of massive populations of users. Could A.I. analysis of our dreams help do the same thing? That's a bold, albeit intriguing, concept -- and it's one that researchers from Nokia Bell Labs in Cambridge, U.K., have been busy exploring. They've created a tool called "Dreamcatcher" that can, so they claim, use the latest Natural Language Processing (NLP) algorithms to identify themes from thousands of written dream reports.

At Callaway, the high-end golf-equipment stalwart, the process of making clubs has always been quite labor-intensive--from grinding and polishing clubheads to crafting wood-and-steel-shafted irons and wedges. The company has also long combined such artisanal handwork with technological innovation, even partnering with aerospace titan Boeing recently to codesign several aerodynamic clubs. So when the company set out about four years ago to make its latest club line, called Epic Flash, it took the next evolutionary technological step, turning to artificial intelligence and machine learning for help. A typical club-design process might involve five to seven physical prototypes; for Epic Flash, Callaway created 15,000 virtual ones. From those, an algorithm determined the best design, selecting for peak performance--i.e., ball speed--while also conforming to the rules set forth by the U.S. Golf Association.

We're living in a world where computers can do our taxes, drive our cars, and book our holidays. Back in 2013, a study by researchers at University of Oxford has given architects a mere 1.8% chance of being automated. This is because'creative tasks' which involve a high degree of human manipulation and human perception are difficult to automate. However, just because certain types of creative occupations can't easily be replaced, doesn't mean that their industries won't see disruption. With the advent of BIM, mixed reality, 3D printing, and other emerging technologies, architects are uniquely placed in the entire digital transformation of construction ecosystem.

Artificial intelligence (AI) is a powerful and robust collection of technologies. While most consumers may see it as the future of personal assistants and self-driving cars, AI has the potential to greatly improve a range of other industries as well. It's not just about the latest technology trends, but rather how artificial intelligence applications can increase profit. At present, AI is improving the financial sector, from big banks to private wealth managers. The technology can assess mass amounts of important financial data such as statements, social media posts, and news articles, and turn it into easily digestible and useful data for humans. It is a process that could take human workers days or weeks, it is significantly sped-up to hours or even minutes.

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"Let us consider an augmented architect at work. He sits at a working station that has a visual display screen some three feet on a side, this is his working surface, controlled by a computer with which he can communicate by means of small keyboards and various other devices." This vision of the future architect was imagined by engineer and inventor Douglas Engelbart during his research into emerging computer systems at Stanford in 1962. At the dawn of personal computing he imagined the creative mind overlapping symbiotically with the intelligent machine to co-create designs. This dual mode of production, he envisaged, would hold the potential to generate new realities which could not be realized by either entity operating alone.

Artificial intelligence is set to take a key role in the design and engineering of new cars, dreaming up lighter, stronger and more complex structures than humans can envision. Just as computing power exceeds the mathematical capability of the human mind, smart software capable of innovation and problem solving is set to push product development into new territory. Hack Rod, a team of designers, engineers, geeks, Hollywood insiders and stunt drivers is working on a way to harness the power of artificial intelligence in tandem with powerful design software produced by Autodesk. Experimenting with connectivity surrounding the emerging "internet of things", the Hack Rod crew built a basic sports car, fitted it with dozens of race car-like sensors, and set about testing, racing and crashing the vehicle. They then fed millions of data points into a computer powered by NVidia processors capable of machine learning, and asked Autodesk's "Dreamcatcher" software to take that information and use it to design a better car.

Artificial intelligence is set to take a key role in the design and engineering of new cars, dreaming up lighter, stronger and more complex structures than humans can envision. Just as computing power exceeds the mathematical capability of the human mind, smart software capable of innovation and problem solving is set to push product development into new territory. Hack Rod, a team of designers, engineers, geeks, Hollywood insiders and stunt drivers is working on a way to harness the power of artificial intelligence in tandem with powerful design software produced by Autodesk. Experimenting with connectivity surrounding the emerging "internet of things", the Hack Rod crew built a basic sports car, fitted it with dozens of race car-like sensors, and set about testing, racing and crashing the vehicle. They then fed millions of data points into a computer powered by NVidia processors capable of machine learning, and asked Autodesk's "Dreamcatcher" software to take that information and use it to design a better car.