For short-term solar irradiance forecasting, the traditional point forecasting methods are rendered less useful due to the non-stationary characteristic of solar power. The amount of operating reserves required to maintain reliable operation of the electric grid rises due to the variability of solar energy. The higher the uncertainty in the generation, the greater the operating-reserve requirements, which translates to an increased cost of operation. In this research work, we propose a unified architecture for multi-time-scale predictions for intra-day solar irradiance forecasting using recurrent neural networks (RNN) and long-short-term memory networks (LSTMs). This paper also lays out a framework for extending this modeling approach to intra-hour forecasting horizons thus, making it a multi-time-horizon forecasting approach, capable of predicting intra-hour as well as intra-day solar irradiance. We develop an end-to-end pipeline to effectuate the proposed architecture. The performance of the prediction model is tested and validated by the methodical implementation. The robustness of the approach is demonstrated with case studies conducted for geographically scattered sites across the United States. The predictions demonstrate that our proposed unified architecture-based approach is effective for multi-time-scale solar forecasts and achieves a lower root-mean-square prediction error when benchmarked against the best-performing methods documented in the literature that use separate models for each time-scale during the day. Our proposed method results in a 71.5% reduction in the mean RMSE averaged across all the test sites compared to the ML-based best-performing method reported in the literature. Additionally, the proposed method enables multi-time-horizon forecasts with real-time inputs, which have a significant potential for practical industry applications in the evolving grid.

The wave of Utah's transportation future has debuted in Farmington. The Utah Department of Transportation, in partnership with the Utah Transit Authority, has launched their new "Autonomous Shuttle Pilot Project" -- a program that features a robotic vehicle that will travel to different communities throughout the state over the next year. The vehicle began serving Station Park, Farmington's large retail hub, on June 13. Anne Williams, a consultant for UDOT, said the shuttle will operate from noon to 6 p.m. on weekdays and Saturdays through July 6. After Station Park, the shuttle will move to different communities throughout Utah for the next year.

The Army will begin equipping combat units next year with remote-controlled robotic vehicles designed to carry ammunition, water and other heavy combat necessities for soldiers, if officials at Fort Benning, Georgia, get their way. The Army has been experimenting with the concept of robotic mules for more than a decade. But the performance of four competing prototypes of a Small Multipurpose Equipment Transport (SMET) during a recent operational test demonstration with units from the 10th Mountain and 101st Airborne divisions has made believers out of officials from Benning's Maneuver Capabilities Development and Integration Directorate (MCDID). "The operational test demonstration really showed that the capability is ready," Col. Tom Nelson, director for Robotics Requirements Division at MCDID, told reporters Tuesday. The SMET is capable of hauling 1,000 pounds of soldier gear for 60 miles within 72 hours, and will also generate three kilowatts of power to charge the growing number of tactical electronic devices soldiers carry, according to officials at MCDID, the organization that has the lead for developing and testing robotics and autonomous systems designed for Army brigade combat teams (BCTs).

NPR's Michel Martin speaks with San Francisco district attorney George Gascon about his plan to use artificial intelligence to combat racial bias in criminal sentencing.

This article originally appeared on VICE US. On Tuesday, Motherboard reported that a group of artists and machine learning engineers posted a deepfake of Mark Zuckerberg to Instagram, making it look like he gave an ominous speech about the power the social network gets from collecting user data. According to Facebook, the video was flagged by two of its fact checking partners, which prompted Facebook to limit its distribution on its platforms. This process suggests that Facebook has the ability to mitigate the virality of a doctored video that aims to spread misinformation, at least once it's highlighted by a news publication. But the Zuckerberg deepfake is not part of a malicious misinformation campaign.

Autonomous vehicles are continuing to cause a stir within the parking industry, and barely a day goes by without another hypothesis of the impact they will have on traditional parking. But how realistic are these visions of an autonomous future? Stanley Robotics is already providing autonomous valet parking at several airports in Europe, and during Parking Talks, Stéphane Evanno shared his insight into what the future might hold. "So I don't think they play a big role today. They are visible and people can hear a lot about self-driving cars and find a lot of information about more robots coming. But they are not here today, they are not running real businesses today, at least not in the airport industry. But they are here enough to make people think differently and plan differently. "For instance, as you know, airports are very regularly conducting master planning exercises.

Autonomous vehicles are continuing to cause a stir within the parking industry, and barely a day goes by without another hypothesis of the impact they will have on traditional parking. But how realistic are these visions of an autonomous future? Stanley Robotics is already providing autonomous valet parking at several airports in Europe, and during Parking Talks, Stéphane Evanno shared his insight into what the future might hold. "So I don't think they play a big role today. They are visible and people can hear a lot about self-driving cars and find a lot of information about more robots coming. But they are not here today, they are not running real businesses today, at least not in the airport industry. But they are here enough to make people think differently and plan differently. "For instance, as you know, airports are very regularly conducting master planning exercises.

Whether that's the everyday life of improbably rich young millionaires like Jake Paul, a high school dropout from Westlake, Ohio, or PewDiePie, a skinny, fast-talking Swede whose real name is Felix Arvid Ulf Kjellberg, YouTube seeks to serve a need. It does so through "the algorithm" -- YouTube's recommendation engine. It's a black box that YouTube introduced to keep us watching, but which has become a thorn in its side as the platform grows at an astronomically grand scale. YouTube's recommendation algorithm is a set of rules followed by cold, hard computer logic. It was designed by human engineers, but is then programmed into and run automatically by computers, which return recommendations, telling viewers which videos they should watch.

Biopharmas are warming up to artificial intelligence (AI), but a series of challenges will need to be addressed before it becomes widely used by drug developers, a panel of industry executives agreed. Speaking at the 2019 Annual Meeting of NewYorkBIO in New York City yesterday, panelists identified those challenges as finding more and better data, integrating data from multiple sources, and creating partnerships to gather and analyze that data. The panel also cited challenges that go beyond data, such as attracting a new generation of professionals capable of applying AI and related technologies such as machine learning--and adapting biopharmas to the new technologies. Those observations are in line with a study released today by The Pistoia Alliance, a global not-for-profit organization of more than 150 members established by executives from AstraZeneca, GlaxoSmithKline (GSK), Novartis, and Pfizer. The Alliance surveyed 190 life sciences professionals in the US and Europe, with 52% citing access to data, and 44% a lack of skills, as the two key barriers of adoption of AI and machine learning.

U of Alberta created the first Computing Science department in Canada in 1964. It has a long tradition of research in AI (is rated 3rd in the world in machine learning). It has also led in the development of AI for strategy games. The results can be commercialized in non-game applications as well. Among these are Checkers, Chess, Go and Poker, The evening's talks were by Jonathan Schaeffer (computer chess) and Ryan Hayward (the strategy game Hex).