Prediction-powered inference (PPI) is a rapidly growing framework for combining machine learning predictions with a small set of gold-standard labels to conduct valid statistical inference. In this article, I argue that the core estimators underlying PPI are equivalent to well-established estimators from the survey sampling literature dating back to the 1970s. Specifically, the PPI estimator for a population mean is algebraically equivalent to the difference estimator of Cassel et al. (1976), and PPI plus corresponds to the generalized regression (GREG) estimator of Sarndal et al. (2003). Recognizing this equivalence, I consider what part of PPI is inherited from a long-standing literature in statistics, what part is genuinely new, and where inferential claims require care. After introducing the two frameworks and establishing their equivalence, I break down where PPI diverges from model-assisted estimation, including differences in the mode of inference, the role of the unlabeled data pool, and the consequences of differential prediction error for subgroup estimands such as the average treatment effect. I then identify what each framework offers the other: PPI researchers can draw on the survey sampling literature's well-developed theory of calibration, optimal allocation, and design-based diagnostics, while survey sampling researchers can benefit from PPI's extensions to non-standard estimands and its accessible software ecosystem. The article closes with a call for integration between these two communities, motivated by the growing use of large language models as measurement instruments in applied research.

Global flash floods, exacerbated by climate change, pose severe threats to humanlife, infrastructure, and the environment. Recent catastrophic events in Pakistan andNew Zealand underscore the urgent need for precise flood mapping to guide restoration efforts, understand vulnerabilities, and prepare for future occurrences. While Synthetic Aperture Radar (SAR) remote sensing offers day-and-night, all-weatherimaging capabilities, its application in deep learning for flood segmentation is limited by the lack of large annotated datasets. To address this, we introduce KuroSiwo, a manually annotated multi-temporal dataset, spanning 43 flood events globally. Our dataset maps more than 338 billion $m^2$ of land, with 33 billion designatedas either flooded areas or permanent water bodies. Kuro Siwo includes a highlyprocessed product optimized for flash flood mapping based on SAR Ground RangeDetected, and a primal SAR Single Look Complex product with minimal preprocessing, designed to promote research on the exploitation of both the phase and amplitude information and to offer maximum flexibility for downstream task preprocessing. To leverage advances in large scale self-supervised pretraining methodsfor remote sensing data, we augment Kuro Siwo with a large unlabeled set of SARsamples. Finally, we provide an extensive benchmark, namely BlackBench, offering strong baselines for a diverse set of flood events globally.

This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG .

The app reads your email inbox and your meeting calendar, then gives you a short audio summary. It can help you spend less time scrolling, but of course, there are privacy drawbacks to consider.

Its march toward automation continues. Amazon has acquired Rivr, a startup focused on autonomous robotics. Rivr is based in Zurich and was valued at $110 million in a funding round from August 2024, which both Amazon and its CEO's Bezos Expeditions participated in. Financial details of the acquisition were not disclosed. Rivr's robots have four legs and wheels that allow it to maneuver on stairs and other potentially uneven surfaces.

Ros Atkins on... Trump's mixed messages on the war For every day of this war, President Trump has been sharing his perspective and his thinking - whether in press conferences, in video statements or in posts on social media. In the last week, that's continued - as strikes have been exchanged - and pressure has built on the supply of oil and gas from the region. The BBC's Analysis Editor Ros Atkins has looked at what the President's been saying. Watch: Sean Penn receives'Oscar' in Ukraine after skipping US ceremony The Academy Award winning US actor won his third Oscar on Sunday, but skipped the ceremony to visit Ukraine. Voiced by Domhnall Gleeson and directed by John Kelly, Retirement Plan is nominated for Best Animated Short Film at the 98th Academy Awards.

Technology Internet Social Media'Dune' tried to warn us against AI'Thou shalt not make a machine in the likeness of a human mind.' AI is illegal in the'Dune' universe, but not for the reasons you may think. Breakthroughs, discoveries, and DIY tips sent six days a week. Even the biggest fans of know that Frank Herbert's classic sci-fi epic quickly veers into the fantastical. Giant subterranean sandworms measuring 1,500 feet long; a narcotic that fuels interstellar travel and bends a user's perception of space-time; a mystical cabal of eugenicist witches--the list goes on.

'Project Hail Mary' may be fiction, but this list could still come in handy. An artist's impression of a theoretical planet orbiting a redder star, which could cause microbes and plants on the planet's surface to reflect very different colors from Earth's green forests. Breakthroughs, discoveries, and DIY tips sent six days a week. Life on Earth is a precious thing, especially given what astronomers know about the visible universe. Although researchers have so far identified over 6,000 exoplanets beyond our solar system, only a handful of them be suitable for human visitors.

Stay up to date with the Fox News AI Newsletter as the U.S. Navy plans to adopt robots that climb wall of warships and Dell announces plans to shrink its workforce.

The company says humans will play a key role in important decisions. A little more than a year after ditching third-party fact checkers and rolling back much of its proactive content moderation, the company says it will further transform its approach by drastically reducing the number of human moderators in favor of AI-based systems. The company says the change will happen over the next few years, and will allow the company to catch more issues faster than its current approach. Meta didn't say how much of its contract workforce might be cut as it makes this transition. The company employs thousands of contractors around the world to review content flagged by its AI systems and user reports among other tasks.