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. A fan can help you feel cooler, but won't lower the temperature of a room. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy . Want to spend less on energy?

Even wild animals enjoy a good wheel. 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. Turns out, that midnight "workout" might not be boredom or restlessness after all. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

Former Giants manager's daughter consulted ChatGPT before reporting altercation The 18-year-old daughter of former Yomiuri Giants manager Shinnosuke Abe said she consulted ChatGPT before reporting an alleged altercation with her father to a child guidance center. The 18-year-old daughter of former Yomiuri Giants manager Shinnosuke Abe said in a letter released on Tuesday that she had consulted ChatGPT before reporting an alleged physical altercation with her father to the child guidance center. Abe resigned from his position on Tuesday following his arrest on suspicion of physically assaulting his daughter . He has been released from police custody. According to reports, two of his daughters had been involved in an argument the previous day.

Causal discovery in time series is increasingly performed using nonlinear machine-learning models, yet the resulting causal relationships are almost always summarized by scalar edge scores. We argue that this practice obscures the true object learned by nonlinear autoregressive models: a state-dependent function whose effect varies across regimes, magnitudes, and contexts. We formalize function-valued causal influence for additive, contribution-decomposable architectures and show that scalar causal scores constitute a severe information bottleneck, conflating between-state variation with within-state residual noise. Using Neural Additive Vector Autoregression as a representative architecture, we introduce a practical framework based on Individual Conditional Expectation for estimating causal response functions directly from trained models. Through controlled synthetic experiments, we demonstrate that edges with indistinguishable scalar scores can exhibit qualitatively different functional behaviors, including monotonic, thresholded, saturating, and sign-changing effects. An applied case study on democratic development further shows that function-valued analysis reveals regime-specific and asymmetric causal structure systematically missed by score-centric approaches.

Collaborative analysis of decentralized confidential datasets is important, but direct sharing of original datasets is often restricted by privacy and institutional constraints. Data collaboration (DC) analysis transforms each dataset into privacy-preserving intermediate representations via party-specific obfuscation functions and integrates them into common collaboration representations using an anchor dataset. However, many existing DC analysis methods rely on linear transformations for data obfuscation and integration, which may increase reconstruction risk. Although nonlinear dimensionality reduction can mitigate this risk, conventional linear integration methods cannot accurately align intermediate representations produced by nonlinear transformations. Moreover, existing integration methods mainly minimize discrepancies among parties and do not explicitly incorporate geometric or target-variable information useful for downstream analysis. To overcome these limitations, we first formulate linear kernel integration (LKI) as a linear integration method and then kernelize it to obtain nonlinear kernel integration (NKI). NKI admits a globally optimal solution via kernel ridge regression and an eigenvalue problem. We also introduce graph regularization and a centering constraint so that the target representation can capture geometric and target-variable information useful for downstream analysis. Experiments on image classification tasks demonstrate that NKI improves classification accuracy over existing linear integration methods under nonlinear dimensionality reduction, with further gains from target-variable-aware graph regularization and centering. The results also show that dimensionality reduction choices substantially affect both classification accuracy and reconstruction risk.

The Holy Father referenced in his encyclical about AI--an expert (if unintentional) troll of tech billionaires who keep misinterpreting the series. Nobody was surprised that Pope Leo XIV cited well-known saints and previous pontiffs in his first encyclical, or papal letter of spiritual guidance,, released Monday. But the name that immediately jumped out to many readers is one synonymous with high fantasy literature: J.R.R. Tolkien, the Catholic author of . Leo's letter is concerned with "safeguarding the human person in the time of artificial intelligence," a major theme of his first year as leader of the Catholic Church. Drawing from his predecessor, Pope Francis, he warns of "the growing dominance of a technocratic paradigm," one capable of "reducing creation to an object of exploitation and human beings to mere cogs in a system driven toward ever greater efficiency."

No one wants a bald eagle talon to the eye at 3am. 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. Sandy and Luna now sleep alone in the nest bowl, but mama Jackie stays nearby. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

AI Tools Are Transforming Muslim Worship. Tarique Kazi used to recite the Quran to his mother. Kazi is a 32-year-old Houston-based Muslim and teacher of hifdh--the Islamic practice of memorizing the Quran in order to deepen faith. For Kazi, the hours he spent with his mother studying the sacred text were among his most cherished. "It was the most beautiful thing that I always looked forward to my mom giving me feedback, telling me how I did," he tells TIME.

Charles Darwin's daughter once hunted the putrid'devil's dipstick.' 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. Also called devil's dipstick, this native fungi are found in most of eastern North America. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

Plus: The Pope has called for governments to regulate AI. Despite the growing hysteria over AI's threat to white-collar jobs, there's still scant evidence that the technology has had a large-scale impact on the labor market. Analysis of US labor data shows that unemployment in occupations most exposed to AI is actually lower than in less-exposed jobs. There are also no signs that large numbers of workers are shifting from AI-threatened professions into supposedly safer manual-labor jobs. It's true that things aren't great in the job market--but the question is why. Here's what the data really says about AI and jobs .