In the U.S., 15,498 of the more than 88,000 dams in the country are categorized as having high hazard potential--meaning that if they fail, they could kill people. As of 2015, some 2,000 of these high hazard dams are in need of repair. With a hefty price tag estimated at around $20 billion, those repairs aren't going to happen overnight. A project out of the Columbia Water Center aims to help guide the process of repairing or decommissioning these dams. The team is pinpointing the riskiest dams, using climate models, GIS data, and artificial intelligence to predict the likelihood that rainfall will overtop a dam and cause significant downstream damages to population and critical infrastructure.

Even as STEM toys become more popular, Lego's construction sets remain the gold standard, with more recent products like Mindstorms and Boost expanding into the fields of robotics and coding. Now bread-and-butter sets like Lego city and licensed products like DC Superheroes get nifty additions like motorized parts and app connectivity, starting with Batman's iconic vehicle. This is the Batmobile from the current slate of DCEU films, complete with tiny cannons and a scowling Batman minifig. For the most part it's a pretty normal Lego set where you follow the instructions and snap it together with your hands. But maybe it was a little too normal: I still had to rely on a paper manual for help, as there are no instructions in the app. Maybe I'm a little spoiled at this point by products like Kamigami and Labo, but one of the advantages of making something app connected is the ability to have interactive diagrams that animate where to place each piece and even allow you to rotate the image for a better look.

In the U.S., 15,498 of the more than 88,000 dams in the country are categorized as having high hazard potential--meaning that if they fail, they could kill people. As of 2015, some 2,000 of these high hazard dams are in need of repair. With a hefty price tag estimated at around $20 billion, those repairs aren't going to happen overnight. A project out of the Columbia Water Center aims to help guide the process of repairing or decommissioning these dams. The team is pinpointing the riskiest dams, using climate models, GIS data, and artificial intelligence to predict the likelihood that rainfall will overtop a dam and cause significant downstream damages to population and critical infrastructure.

Plants, factories, and manufacturers in general are embracing IoT, which in turn is driving the use of artificial intelligence at the edge of corporate networks as a way to streamline industrial processes, improve efficiency and detect maintenance issues before they become problems – perhaps even big problems that could force plant shutdowns. At the same time, incumbents such as AWS, Dell, and Cisco are pouring billions into IoT and edge computing. HPE recently invested $4 billion on its "intelligent edge," while Microsoft pumped $6.5 billion into its IoT efforts. The competition in this sector is brutal, but the opportunity is big enough that the 10 startups highlighted here still have room to maneuver and time to scale up. Keep an eye on them because one or more could well be the next unicorn in this hot market.

We consider a scenario where an agent has multiple available strategies to explore an unknown environment. For each new interaction with the environment, the agent must select which exploration strategy to use. We provide a new strategy-agnostic method that treat the situation as a Multi-Armed Bandits problem where the reward signal is the diversity of effects that each strategy produces. We test the method empirically on a simulated planar robotic arm, and establish that the method is both able discriminate between strategies of dissimilar quality, even when the differences are tenuous, and that the resulting performance is competitive with the best fixed mixture of strategies.

The Ring Video Doorbell Pro is a smaller and smarter member of Ring's popular video doorbell family. It's $50 more expensive than Ring's second-generation battery-powered device, but this additional investment could considerably cut down on the number of false alerts you receive and leave you a much more satisfied owner. That's what happened to me when I swapped out the Ring Video Doorbell 2 for the Pro version. The secret to the Pro's porch success at my house is its more complex detection zone setup. The Ring Video Doorbell 2's motion detection is based on passive infrared sensors that look for moving heat sources, such as humans, animals, and cars.

Deep Learning (DL) provides a methodology to predict extreme loads observed in energy grids. Forecasting energy loads and prices is challenging due to sharp peaks and troughs that arise from intraday system constraints due to supply and demand fluctuations. We propose deep spatio-temporal models and extreme value theory (DL-EVT) to capture the tail behavior of load spikes. Deep architectures, such as ReLU and LSTM can model generation trends and temporal dependencies while EVT captures highly volatile load spikes. To illustrate our methodology, we use hourly price and demand data from the PJM interconnection for 4719 nodes and we develop a deep predictor. DL-EVT outperforms traditional Fourier and time series methods, both in-and out-of-sample, by capturing the nonlinearities in prices. Finally, we conclude with directions for future research.

Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. In this paper, we consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we propose a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We present the new model, its induced likelihood function, and a fitting algorithm which can be applied in the presence of missing data. We demonstrate how to use XPCA to produce an estimated full conditional distribution for each data point, and use this to produce to provide estimates for missing data that are automatically range respecting. We compare the methods as applied to simulated and real-world data sets that have a mixture of discrete and continuous variables.

Nvidia revealed the boundary-pushing GeForce RTX 20-series on Monday, unleashing GeForce RTX 2070, RTX 2080, and RTX 2080 Ti graphics cards brimming with fancy new tech that promises to support fancy new gaming capabilities. Foremost among those feats is real-time ray tracing, the ultra-difficult realistic lighting technology that gives Nvidia's new cards their "RTX" moniker. The RTX cards also support Deep Learning Super-Sampling (DLSS), a fresh Nvidia super-sampling method that puts the AI tensors cores embedded within the GPUs to work. Now, we know which PC games will support them--a crucial step, since all the luxurious tech in the world means nothing if games don't actually tap into it. Both real-time ray tracing and DLSS will debut with a solid backing, as made clear by Nvidia's games partner announcement.