Researchers froze mayfly couples in the middle of mating--for science. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. The female is on top, the male below. Breakthroughs, discoveries, and DIY tips sent six days a week. Researchers studying copulation in mayflies pulled off a stunt worthy of the naughtiest ancient Greek myths.

Near the Kremlin several dozen people are queuing outside the presidential administration office. They've come to submit petitions calling on President Vladimir Putin to end a crackdown on the internet. Russian authorities have been tightening control of the country's cyber space. Access to global messaging apps has been restricted and there are widespread disruptions to, even shutdowns of, mobile internet. Petitioning the president is legal.

We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be miscalibrated. A standard approach in this setting is augmented inverse-probability weighting (AIPW) [Robins et al., 1994], which protects against prediction-model misspecification but can be inefficient when the prediction score is poorly aligned with the outcome scale. We introduce Calibrated Prediction-Powered Inference, which post-hoc calibrates the prediction score on the labeled sample before using it for semisupervised estimation. This simple step requires no retraining and can improve the original score both as a predictor of the outcome and as a regression adjustment for semisupervised inference. We study both linear and isotonic calibration. For isotonic calibration, we establish first-order optimality guarantees: isotonic post-processing can improve predictive accuracy and estimator efficiency relative to the original score and simpler post-processing rules, while no further post-processing of the fitted isotonic score yields additional first-order gains. For linear calibration, we show first-order equivalence to PPI++. We also clarify the relationship among existing estimators, showing that the original PPI estimator is a special case of AIPW and can be inefficient when the prediction model is accurate, while PPI++ is AIPW with empirical efficiency maximization [Rubin et al., 2008]. In simulations and real-data experiments, our calibrated estimators often outperform PPI and are competitive with, or outperform, AIPW and PPI++. We provide an accompanying Python package, ppi_aipw, at https://larsvanderlaan.github.io/ppi-aipw/.

The kraken-like apex predators were smart, too. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. The fossils prove octopuses existed at least 5 million years earlier than originally thought. Breakthroughs, discoveries, and DIY tips sent six days a week. Around 100 million years ago, real kraken-like creatures stalked Earth's prehistoric oceans.

Drone incursions over U.S. military bases reveal critical vulnerabilities in civilian infrastructure, from airports to energy grids, that experts say remain dangerously exposed.

In feat hailed as milestone in robotics, Sony AI's Ace wins three out of five matches played under official rules An AI-powered robot has beaten elite players at table tennis in a significant achievement for a machine faced with human athletes in a real-world competitive sport. Named Ace, the robotic system developed by Sony AI, won three out of five matches against elite players, but lost the two it played against professionals, clawing back only one game in the seven contests. The feat has been hailed as a milestone for robotics, a field that has long seen table tennis - and the lightning-fast reactions, perception and skill it demands - as one of the toughest tests of how far the technology has advanced. In the matches, played under official competition rules, Ace displayed a mastery of spin, handled difficult shots, such as balls catching on the net, and pulled off one rapid backspin shot that a professional had thought impossible. A research paper on the robot was published in Nature on Wednesday, but scientists working on the project said Ace had improved since the report was submitted.

'She had big googly eyes and was wearing a red hat knitted by one of the careworkers' Emma the Social Robot by Paula Hornickel. 'She had big googly eyes and was wearing a red hat knitted by one of the careworkers' Emma the Social Robot by Paula Hornickel. 'The first resident that Emma - a social robot - was introduced to was called Peter. After that, Emma assumed they were all called Peter, which everyone found hilarious. O ne morning in July 2025, I arrived in the small, quiet town of Albershausen in south-west Germany.

Driver who hit and killed jogger father-of-two sues victim's estate claiming incident left him with severe PTSD Sydney Sweeney's role is cut from The Devil Wears Prada 2 New'Hollywood dose' pill: A-listers hooked on'youth elixir' that dermatologists say is anti-aging, shrinks pores, smooths wrinkles... and even banishes rosacea Alarm over popular new coffee chain invading the US... as experts warn of chilling secret behind its $1.99 brew Ark of the Covenant's final resting place pinpointed by archaeologists as fresh search begins Truth about your Mounjaro injection site: Our expert doctors reveal exactly where you should inject yourself for the best results, what to do if your weight loss has slowed down... and the areas you should NEVER jab America's scariest hospital where patient and multiple staffers have been attacked in weeks since pepper spray and batons were banned Jordon Hudson extends her control over Bill Belichick's empire with secret move that is set to leave his family and friends furious Beloved Republican mayor of small Great Plains town could be deported over'mistake' he insists was an innocent one Humiliating moment runner celebrates winning marathon... only to be pipped at the line by rival in brutal finish Life-threatening cantaloupe recall in four states upgraded to FDA's highest risk level... 'reasonable probability of death' A parade of US Air Force jets has been detected flying near the Middle East on Tuesday, as President Donald Trump's ceasefire with Iran hangs in the balance. Flight tracking websites show at least five C-17 Globemaster III aircraft moving toward Saudi Arabia after leaving a key Nato installation in Germany . Trump announced a 14-day ceasefire with Iran on April 7, with the pause in hostilities expected to expire on Wednesday evening, April 22 . On Tuesday, Trump signaled that US forces are prepared to resume military operations if negotiations fail to produce an agreement. Trump told reporters the military is'raring to go,' adding that he expects bombing could resume if no deal is reached before the deadline, while expressing confidence that talks could still result in what he described as a'great deal.'

How do you go about integrating causal knowledge into decision systems or agents? We sat down with Matteo Ceriscioli to find out about his research in this space. This interview is the latest in our series featuring the AAAI/SIGAI Doctoral Consortium participants. Could you start by telling us a bit about your PhD - where are you studying, and what's the broad topic of your research? The idea is to integrate causal knowledge into agents or decision systems to make them more reliable.

Generative modeling within constrained sets is essential for scientific and engineering applications involving physical, geometric, or safety requirements (e.g., molecular generation, robotics). We present a unified framework for constrained diffusion models on generic nonconvex feasible sets $Σ$ that simultaneously enforces equality and inequality constraints throughout the diffusion process. Our framework incorporates both overdamped and underdamped dynamics for forward and backward sampling. A key algorithmic innovation is a computationally efficient landing mechanism that replaces costly and often ill-defined projections onto $Σ$, ensuring feasibility without iterative Newton solves or projection failures. By leveraging underdamped dynamics, we accelerate mixing toward the prior distribution, effectively alleviating the high simulation costs typically associated with constrained diffusion. Empirically, this approach reduces function evaluations and memory usage during both training and inference while preserving sample quality. On benchmarks featuring equality and mixed constraints, our method achieves comparable sample quality to state-of-the-art baselines while significantly reducing computational cost, providing a practical and scalable solution for diffusion on nonconvex feasible sets.