Pattern-based, modular ontologies have several beneficial properties that lend themselves to FAIR data practices, especially as it pertains to Interoperability and Reusability. However, developing such ontologies has a high upfront cost, e.g. reusing a pattern is predicated upon being aware of its existence in the first place. Thus, to help overcome these barriers, we have developed MODL: a modular ontology design library. MODL is a curated collection of well-documented ontology design patterns, drawn from a wide variety of interdisciplinary use-cases. In this paper we present MODL as a resource, discuss its use, and provide some examples of its contents.

Question Answering has recently received high attention from artificial intelligence communities due to the advancements in learning technologies. Early question answering models used rule-based approaches and moved to the statistical approach to address the vastly available information. However, statistical approaches are shown to underperform in handling the dynamic nature and the variation of language. Therefore, learning models have shown the capability of handling the dynamic nature and variations in language. Many deep learning methods have been introduced to question answering. Most of the deep learning approaches have shown to achieve higher results compared to machine learning and statistical methods. The dynamic nature of language has profited from the nonlinear learning in deep learning. This has created prominent success and a spike in work on question answering. This paper discusses the successes and challenges in question answering question answering systems and techniques that are used in these challenges.

A common strategy today to generate efficient locomotion movements is to split the problem into two consecutive steps: the first one generates the contact sequence together with the centroidal trajectory, while the second one computes the whole-body trajectory that follows the centroidal pattern. Yet the second step is generally handled by a simple program such as an inverse kinematics solver. In contrast, we propose to compute the whole-body trajectory by using a local optimal control solver, namely Differential Dynamic Programming (DDP). Our method produces more efficient motions, with lower forces and smaller impacts, by exploiting the Angular Momentum (AM). With this aim, we propose an original DDP formulation exploiting the Karush-Kuhn-Tucker constraint of the rigid contact model. We experimentally show the importance of this approach by executing large steps walking on the real HRP-2 robot, and by solving the problem of attitude control under the absence of external forces.

It was a hot February morning at Wish Farms, a large strawberry-growing operation outside Plant City, Florida. Gary Wishnatzki, the proprietor, met me at one of the farm offices. In the high season, Wish Farms picks, chills, and ships some twenty million berries--all handpicked by a seasonal workforce of six hundred and fifty farm laborers. Wishnatzki is a genial sixty-three-year-old third-generation berry man, who wears a white goatee and speaks softly, with a Southern drawl. His grandfather Harris Wishnatzki was a penniless Russian immigrant who started out peddling fruits and vegetables from a pushcart in New York's Washington Street Market in 1904.

Forbes' Jillian D'Onfro leads a panel of AI industry experts (left to right) Marco Casalaina, Salesforce, Chuck Ganapathi, Tact.ai, and Lorrissa Horton, Cisco. Today's voice-powered AI assistant has many names--Siri, Alexa, Cortana--but as this developing technology becomes ubiquitous in both consumer and enterprise environments, Chuck Ganapathi has a suggestion for his industry colleagues: "Let's not pretend it's a human," the founder and CEO of Tact said Monday during the Voice AI in the Enterprise panel at the Forbes CIO Summit in Half Moon Bay, California, taking a jab at Google's eerily lifelike Duplex AI system. What's more, he said, the enterprise must be careful not to hark back to the secretary pools of old: Voice assistants at work shouldn't automatically sound like they're women. His company intentionally gave its AI-based customer-relationship management system a gender-free name and gives users multiple voice options at setup. He also commended the work of a European agency called Virtue that launched the first "genderless" digital assistant voice this spring.

It began, late last year, with Silver boasting about the success of his election models and Taleb shooting back that Silver doesn't "know how math works." Silver said Taleb was "consumed by anger" and hadn't had any new ideas since 2001. The argument has gotten personal, with Silver calling Taleb an "intellectual-yet-idiot" (an insult taken from Taleb's own book) and Taleb calling Silver "klueless" and "butthurt." Here is a recap of what they're fighting about so you can know who's right (Silver, mostly) and who's wrong (Taleb). The origin of Taleb's ire can be found in Silver's success since 2008--and his some-time failures. As I described in Nautilus last month, evaluating probabilistic election forecasts can be conceptually slippery, made especially difficult by the counterintuitive properties of mathematical probability.

GameStop's Spring Sale is loaded with savings on games, consoles, and more. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. Video games are an expensive hobby, but they're so fun and only getting better and better. So we keep playing and pre-ordering new releases and waiting for Hideo Kojima to finally announce the release date for Death Stranding (Please tell us, Mr. Kojima! And every now and then, we manage to get the games we've been dying to play for a discount.

Traffic crawls through the wind and snow on the RFK Bridge on Friday in the Queens borough of New York. So reports the Wall Street Journal which reviewed an internal email sent by the Metropolitan Transportation Authority, the state agency which manages all the traffic crossing the area's bridges and tunnels. The MTA email was sent to the office of New York Governor Andrew Cuomo. According to the email, the "initial period for the proof of concept testing at the (Robert F. Kennedy Bridge connecting Manhattan, the Bronx and Queens) for facial recognition has been completed and failed with no faces (0%) being detected within acceptable parameters." Besides the RFK Bridge, the MTA is testing the technology at the Throgs Neck and Whitestone bridges, as well as at the Midtown and Hugh L. Carey tunnels.

MOSCOW - The Russian Defense Ministry has deployed a surveillance drone to an artillery division stationed on a group of islands controlled by Russia but claimed by Japan, a Russian newspaper reported Monday. The drone will be used for patrolling coastal areas and surrounding waters, as well as for rescue operations, according to the newspaper, Izvestia. The artillery unit is stationed on two of the four Russian-controlled islands off the coast of Hokkaido, known in Japan as Etorofu and Kunashiri. The Orlan-10 drone, the same type as those sent by Russia to Syria, is able to operate within a 120-kilometer radius for up to 14 hours while transmitting images from a mounted camera, the Russian paper said.

If you work at IBM or a company equipped with their artificially intelligent employee retention software, your planned two-week's notice may already be old news. According to a recent panel discussion with IBM's CEO, Ginni Rometty, at a Work Talent and Human Resources Summit in New York, the company's'predictive attrition' software is now 95 percent accurate in determining when an employee is ready to quit. Using their predicative software, Rometty says that IBM has been able to preempt employees on the cusp of quitting, bolstering their retention rates, which has reportedly saved them $300 million. Human resources may need a new name as a host of new software has begun to disrupt jobs and efficiency. Among the many AI-powered tools being developed by IBM for human resources is'predictive attrition.'