Humans are able to conceive physical reality by jointly learning different facets thereof. To every pair of notions related to a perceived reality may correspond a mutual relation, which is a notion on its own, but one-level higher. Thus, we may have a description of perceived reality on at least two levels and the translation map between them is in general, due to their different content corpus, one-to-many. Following success of the unsupervised neural machine translation models, which are essentially one-to-one mappings trained separately on monolingual corpora, we examine further capabilities of unsupervised deep learning methods used there and apply these methods to sets of notions of different level and measure. Using the graph and word embedding-like techniques, we build one-to-many map without parallel data in order to establish a unified latent mental representation of the outer world, by combining notions of different kind into a unique conceptual framework. Due to latent similarity, by aligning two embedding spaces in purely unsupervised way, one obtains a geometric relation between objects of cognition on the two levels, making it possible to express a natural knowledge using one description in the context of the other.

If you're like the majority of humans on the planet, going to the dentist isn't on the top of your list of things to do for fun. But with artificial intelligence (AI) and new tech and innovative design, it might start to be a bit more intriguing. AI might not be able to do the actual brushing and flossing for you (yet), but it will certainly change your experience the next time you're sitting in the dentist's chair. From analyzing X-rays to documenting the results of your visit, artificial intelligence will be relied upon to make your dental appointment more efficient and to enhance your care. Dentem created a platform that integrates machine learning APIs, including the ability to auto-populate tooth charting.

Gary Marcus has emerged as one of deep learning's chief skeptics. In a recent interview, and a slightly less recent medium post, he discusses his feud with deep learning pioneer Yann LeCun and some of his views on how deep learning is overhyped. I find the whole thing entertaining, but at many times LeCun and Marcus are talking past each other more than with each other. Marcus seems to me to be either unaware of or ignoring certain truths about machine learning and LeCun seems to basically agree with Marcus' ideas in a way that's unsatisfying for Marcus. The temptation for me to brush 10 years of dust off of my professor hat is too much to ignore.

Fear, uncertainty and doubt are tainting the banking industry's views of artificial intelligence. There's so much noise about AI, it's reminiscent of irrational fears about electricity or even the microwave -- it's going to take away our jobs, is more dangerous than nuclear weapons and will have a negative impact on our cities. From my perspective, it's important to be cautious when we evaluate new technologies, but I'm an optimist at heart. I believe in the power of technology to create value and transform lives. The individuals who are responsible for AI have the capacity to create guardrails and ensure that these new approaches to data science do not have a negative impact.

Artificial intelligence doesn't need any extra fuel for the myths and misconceptions that surround it. Consider the phrase "black box" – its connotations are equal parts mysterious and ominous, the stuff of "The X Files" more than the day-to-day business of IT. Yet it's true that AI systems, such as machine learning or deep learning, take inputs and then produce outputs (or make decisions) with no decipherable explanation or context. The system makes a decision or takes some action, and we don't necessarily know why or how it arrived at that outcome. The system just does it.

Surveillance video is everywhere these days, and researchers are working on making it smarter and smarter. The latest advance is in the problem of constructing -- or "hallucinating" in machine learning ML parlance -- a complete image of a person from a partial or occluded photo. Occlusion occurs when the object, or body, you want to see is partially covered by an intervening object or body. In a crowded public area, say Times Square in New York, surveillance cameras would rarely get an unobstructed view of a person of interest. What is artificial general intelligence? That's where the paper Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect? by researchers from the University of Modena comes in.

While governments around the world are wrestling with the potential for massive on-rushing technological disruption of work and the jobs market, few are extending the telescope to explore what the knock-on impacts might be for the planet. Here we explore some dimensions of the issue. Although replacing humans with robots has a dystopian flavor, what, if any positives are there from successive waves of artificial intelligence (AI) and other exponentially developing technologies displacing jobs ranging from banker to construction worker? Clearly, the number of people working and the implications for commuting, conduct of their role and their resulting income-related domestic lifestyle all have a direct bearing on their consumption of resources and emissions footprint. However, while everyone wants to know the impact of smart automation, the reality is that we are all clueless as to the outcome over the next twenty years, as this fourth industrial revolution has only just started.

Last year, after breaking the Guinness World Record for the Key West to Cuba run, we wondered what was next for the #77 Lucas Oil SilverHook ocean racing powerboat? We found the answer in the 50th anniversary of the Trinidad & Tobago Great Race, one of the most grueling races in the world. The 115-mile endurance course starts in Trinidad's Port of Spain, where you head north and then east near the island before popping into the Atlantic Ocean for a 50-mile sprint to the finish in Store Bay, Tobago. Because of the logistical difficulties of racing on foreign shores, we were the first American entry in 29 years. We knew we would face stiff competition from Jumbie, Cat Killer, Mr. Solo and other local rivals that know the course well.

Email is the foundation of most marketing programs -- and for good reason. Plus, as Ann Handley, chief content officer for MarketingProfs, pointed out, email is the only digital channel where people (not algorithms) are in control of when and where your content is exposed and to whom. But B2B marketers must rethink how to stand out in today's crowded inboxes. At the most basic level, rising to the top of the inbox is a matter of establishing trust. The 2018 Edelman Trust Barometer survey found global mistrust in business, with the sharpest decline in the U.S., where 42 percent of buyers reported not knowing which brands they could trust.

Combining big data with artificial intelligence has allowed University of Copenhagen researchers to determine whether you wrote your assignment or whether a ghostwriter penned it for you--with nearly 90 percent accuracy. Several studies have shown that cheating on assignments is widespread and becoming increasingly prevalent among high school students. At the University of Copenhagen's Department of Computer Science, efforts to detect cheating on assignments through writing analysis by way of artificial intelligence have been underway for a few years. Now, based on analyses of 130,000 written Danish assignments, scientists can, with nearly 90 percent accuracy, detect whether a student has written an assignment on their own or if a ghostwriter composed it. Danish high schools currently use the Lectio platform to check if a student has handed in plagiarized work with passages copied directly from a previously submitted assignment.