Pacific Ocean
Mass power outages affect 130,000 in San Francisco and disrupt traffic
A widespread power failure plunged San Francisco into darkness on Saturday night, disrupting traffic citywide and forcing numerous self-driving Waymo taxis to stop abruptly in the middle of streets and intersections. As electricity went out across large portions of the city, traffic signals failed, leaving autonomous vehicles unable to operate as normal. Photos and videos shared by users on X showed Waymo robotaxis frozen in place, backing up traffic and creating hazardous conditions for other drivers. Waymo confirmed on Saturday evening that it had shut down its driverless ride-hailing service throughout San Francisco after footage circulated online showing its vehicles blocking roads during the blackout. "We have temporarily suspended our ride-hailing services in the San Francisco Bay Area due to the widespread power outage," Waymo spokesperson Suzanne Philion said in a statement to several news outlets.
More than 20,000 still without power after massive San Francisco blackout
Things to Do in L.A. Tap to enable a layout that focuses on the article. This is read by an automated voice. Please report any issues or inconsistencies here . After Saturday's blackout, roughly 110,000 San Francisco residents have power again. About 21,000 are still in the dark as extensive repairs continue after a substation fire.
A San Francisco power outage left Waymo's self-driving cars stranded at intersections
LG TVs add'delete' option for Copilot A San Francisco power outage left Waymo's self-driving cars stranded at intersections Waymo halted its autonomous ride-hailing services in the city in response. Several of Waymo's autonomous vehicles were seen stuck in the middle of San Francisco streets following a significant power outage that took out the city's traffic lights. Waymo responded to the power outage by suspending its ride-hailing services in the city, but images and videos on social media showed the self-driving taxis stopped at intersections with hazard lights on. We have temporarily suspended our ride-hailing services in the San Francisco Bay Area due to the widespread power outage, Suzanne Philion, a spokesperson for Waymo, told Engadget in an email. Our teams are working diligently and in close coordination with city officials, and we are hopeful to bring our services back online soon.
Would You Trust a 22-Year-Old AI Billionaire With the Global Economy?
B rendan Foody is 22 years old and runs a company worth billions. This August, I met the young CEO in a glass conference room overlooking the San Francisco Bay. While his peers are searching for their first jobs, Foody is pursuing a " master plan," as he calls it, to upend the global labor market. His start-up, Mercor, offers an AI-powered hiring platform: Bots weed through rรฉsumรฉs, and even conduct interviews. In the next five years, Foody told me, AI could automate 50 percent of the tasks that people do today.
Multivariate Uncertainty Quantification with Tomographic Quantile Forests
Quantifying predictive uncertainty is essential for safe and trustworthy real-world AI deployment. Yet, fully nonparametric estimation of conditional distributions remains challenging for multivariate targets. We propose Tomographic Quantile Forests (TQF), a nonparametric, uncertainty-aware, tree-based regression model for multivariate targets. TQF learns conditional quantiles of directional projections $\mathbf{n}^{\top}\mathbf{y}$ as functions of the input $\mathbf{x}$ and the unit direction $\mathbf{n}$. At inference, it aggregates quantiles across many directions and reconstructs the multivariate conditional distribution by minimizing the sliced Wasserstein distance via an efficient alternating scheme with convex subproblems. Unlike classical directional-quantile approaches that typically produce only convex quantile regions and require training separate models for different directions, TQF covers all directions with a single model without imposing convexity restrictions. We evaluate TQF on synthetic and real-world datasets, and release the source code on GitHub.
A Statistical Framework for Spatial Boundary Estimation and Change Detection: Application to the Sahel Sahara Climate Transition
Tivenan, Stephen, Sahoo, Indranil, Qian, Yanjun
Spatial boundaries, such as ecological transitions or climatic regime interfaces, capture steep environmental gradients, and shifts in their structure can signal emerging environmental changes. Quantifying uncertainty in spatial boundary locations and formally testing for temporal shifts remains challenging, especially when boundaries are derived from noisy, gridded environmental data. We present a unified framework that combines heteroskedastic Gaussian process (GP) regression with a scaled Maximum Absolute Difference (MAD) Global Envelope Test (GET) to estimate spatial boundary curves and assess whether they evolve over time. The heteroskedastic GP provides a flexible probabilistic reconstruction of boundary lines, capturing spatially varying mean structure and location specific variability, while the test offers a rigorous hypothesis testing tool for detecting departures from expected boundary behaviors. Simulation studies show that the proposed method achieves the correct size under the null and high power for detecting local boundary shifts. Applying our framework to the Sahel Sahara transition zone, using annual Koppen Trewartha climate classifications from 1960 to 1989, we find no statistically significant decade scale changes in the arid and semi arid or semi arid and non arid interfaces. However, the method successfully identifies localized boundary shifts during the extreme drought years of 1983 and 1984, consistent with climate studies documenting regional anomalies in these interfaces during that period.
Rare, deep-sea encounter: California scientists observe 'extraordinary' seven-arm octopus
Things to Do in L.A. Tap to enable a layout that focuses on the article. Rare, deep-sea encounter: California scientists observe'extraordinary' seven-arm octopus On November 6, 2025, MBARI Senior Scientist Steven Haddock and researchers in MBARI's Biodiversity and Biooptics Team observed a seven-arm octopus (Haliphron atlanticus) during an expedition in Monterey Bay with MBARI's remotely operated vehicle at a depth of approximately 700 meters. This is read by an automated voice. Please report any issues or inconsistencies here . California scientists captured rare footage of a seven-arm octopus eating a jellyfish.