Things to Do in L.A. Tap to enable a layout that focuses on the article. Ex-Trump DOJ lawyers say'fraudulent' UC antisemitism probes led them to quit Data centers for AI could nearly triple San José's energy use. This is read by an automated voice. Please report any issues or inconsistencies here . The county seat of Santa Clara is touting its partnership with Pacific Gas & Electric, claiming the city is "the West Coast's premier destination for data center development."

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Wind energy resource quantification, air pollution monitoring, and weather forecasting all rely on rapid, accurate measurement of local wind conditions.

To evaluate the fidelity of synthetic tabular data, numerous metrics have been proposed to assess accuracy and diversity, including both low-order statistics (e.g., Density Estimation and Correlation Score (Zhang et al., 2023), Average Coverage Scores (Zein & Urvoy, 2022)) and high-order statistics (e.g., α-Precision and β-Recall (Alaa et al., 2022)). However, these metrics operate at a high level and fail to evaluate whether synthetic data preserves logical relationships, such as hierarchical or semantic dependencies between features. This highlights the need for a more fine-grained, context-aware evaluation of multivariate dependencies. To address this, we propose three evaluation metrics: Hierarchical Consistency Score (HCS), Multivariate Dependency Index (MDI), and Distributional Similarity Index (DSI). To assess the effectiveness of these metrics in quantifying inter-column relationships, we select five representative tabular data generation methods from different categories for evaluation. Their performance is measured using both existing and our proposed metrics on a real-world dataset rich in logical consistency and dependency constraints. Experimental results validate the effectiveness of our proposed metrics and reveal the limitations of existing approaches in preserving logical relationships in synthetic tabular data. Additionally, we discuss potential pathways to better capture logical constraints within joint distributions, paying the way for future advancements in synthetic tabular data generation.

WIRE)-- Simulations Plus, Inc. (Nasdaq: SLP), a leading provider of modeling and simulation software and services for pharmaceutical safety and efficacy, today announced it has entered a new collaboration with a large pharmaceutical company to extend the industry's top-rated machine learning models for the prediction of ionization constants (pKa) in the ADMET Predictor platform. In this collaboration, the partner company will contribute tens of thousands of proprietary pKa measurements. The team at Simulations Plus will aim to leverage the expansive databases to improve the accuracy of predictions, and extend the chemical coverage space, using its novel machine learning and atomic descriptor calculation methods. Dr. Robert Fraczkiewicz, Research Fellow and project lead, said: "The ionization of molecules in water impacts nearly all properties driving the absorption, distribution, metabolism, and elimination processes which occur in vivo and determine whether a molecule can be turned into a drug. We identified early the importance of accurately, and rapidly, predicting this information using machine learning approaches and were fortunate to benefit from government grants and other collaborations over the years to develop novel 2D pKa models which have consistently outperformed other software and are on par with the accuracy of the best computationally intensive ab initio methods. This new partnership will enhance our current approaches and further distinguish ADMET Predictor as the preeminent property prediction platform in the drug discovery space. We value the trust and confidence our partner has in the people and technologies at Simulations Plus, and our team is looking forward to working with them to achieve our mutual goals."

SPRINGFIELD, MASSACHUSETTS – Police departments around the U.S. are asking citizens to trust them to use facial recognition software as another handy tool in their crime-fighting toolbox. But some lawmakers -- and even some technology giants -- are hitting the brakes. Are fears of an all-seeing, artificially intelligent security apparatus overblown? Not if you look at China, where advancements in computer vision applied to vast networks of street cameras have enabled authorities to track members of ethnic minority groups for signs of subversive behavior. American police officials and their video surveillance industry partners contend that won't happen here.

Products/Services Visa agreed to acquire the token and electronic ticketing business of Rambus for $75 million in cash. The business involved is part of the Smart Card Software subsidiary of Rambus. It includes the former Bell ID mobile-payment businesses and the Ecebs smart-ticketing systems for transit providers. Meanwhile, Rambus expanded its CryptoManager Root of Trust product line. "Security is a mission-critical imperative for SoC designs serving virtually every application space," Neeraj Paliwal, vice president of products, cryptography at Rambus, said in a statement.

Wind energy resource quantification, air pollution monitoring, and weather forecasting all rely on rapid, accurate measurement of local wind conditions. Visual observations of the effects of wind---the swaying of trees and flapping of flags, for example---encode information regarding local wind conditions that can potentially be leveraged for visual anemometry that is inexpensive and ubiquitous. Here, we demonstrate a coupled convolutional neural network and recurrent neural network architecture that extracts the wind speed encoded in visually recorded flow-structure interactions of a flag in naturally occurring wind. Predictions for wind speeds ranging from 0.75-11 m/s showed agreement with measurements from a cup anemometer on site, with a root-mean-square error approaching the natural wind speed variability due to atmospheric turbulence. Generalizability of the network was demonstrated by successful prediction of wind speed based on recordings of other flags in the field and in a controlled in wind tunnel test. Furthermore, physics-based scaling of the flapping dynamics accurately predicts the dependence of the network performance on the video frame rate and duration.

The Robot Show at the Museum of Art and History in Lancaster, Calif., is comprised of eight exhibitions exploring the place robots, and other forms of artificial intelligence, have in a contemporary social landscape – from popular culture to nature and spirituality. Featured in the Main Gallery at MOAH is a retrospective of Emmy-nominated artist and animator, Dave Pressler. The exhibition is on view through September 26, 2018. Robert Nelson is encouraging viewers' Awakening in his new exhibition, a part of The Robot Show. Using a vivid palette, mixing pop and surrealist styles, Nelson juxtaposes images that play with deep, edgy ideas of technology.

Last week, on September 8th, the Los Angeles County Sheriff's department successfully used a remote-controlled bomb squad robot to snatch a rifle out from under an armed and violent suspect. The standoff between the suspect and an armored SWAT team lasted for more than six hours, but concluded without a single shot fired. "The robot was a game changer here," Capt. Jack Ewell told the LA Times. "We didn't have to risk a deputy's life to disarm a very violent man."