Multivariate time series in domains such as finance, climate science, and healthcare often exhibit long-term trends, seasonal patterns, and short-term fluctuations, complicating causal inference under non-stationarity and autocorrelation. Existing causal discovery methods typically operate on raw observations, making them vulnerable to spurious edges and misattributed temporal dependencies. We introduce a decomposition-based causal discovery framework that separates each time series into trend, seasonal, and residual components and performs component-specific causal analysis. Trend components are assessed using stationarity tests, seasonal components using kernel-based dependence measures, and residual components using constraint-based causal discovery. The resulting component-level graphs are integrated into a unified multi-scale causal structure. This approach isolates long- and short-range causal effects, reduces spurious associations, and improves interpretability. Across extensive synthetic benchmarks and real-world climate data, our framework more accurately recovers ground-truth causal structure than state-of-the-art baselines, particularly under strong non-stationarity and temporal autocorrelation.

It is folklore that reusing training data more than once can improve the statistical efficiency of gradient-based learning. However, beyond linear regression, the theoretical advantage of full-batch gradient descent (GD, which always reuses all the data) over one-pass stochastic gradient descent (online SGD, which uses each data point only once) remains unclear. In this work, we consider learning a $d$-dimensional single-index model with a quadratic activation, for which it is known that one-pass SGD requires $n\gtrsim d\log d$ samples to achieve weak recovery. We first show that this $\log d$ factor in the sample complexity persists for full-batch spherical GD on the correlation loss; however, by simply truncating the activation, full-batch GD exhibits a favorable optimization landscape at $n \simeq d$ samples, thereby outperforming one-pass SGD (with the same activation) in statistical efficiency. We complement this result with a trajectory analysis of full-batch GD on the squared loss from small initialization, showing that $n \gtrsim d$ samples and $T \gtrsim\log d$ gradient steps suffice to achieve strong (exact) recovery.

Elon Musk Is Rolling xAI Into SpaceX--Creating the World's Most Valuable Private Company By fusing SpaceX and xAI--which acquired X last year--Elon Musk tightens his grip over technologies that shape national security, social media, and artificial intelligence. Elon Musk's rocket and satellite company SpaceX is acquiring his AI startup xAI, the centibillionaire announced on Monday. In a blog post, Musk said the acquisition was warranted because global electricity demand for AI cannot be met with "terrestrial solutions," and Silicon Valley will soon need to build data centers in space to power its AI ambitions. "In the long term, space-based AI is obviously the only way to scale," Musk wrote. "The only logical solution therefore is to transport these resource-intensive efforts to a location with vast power and space. I mean, space is called'space' for a reason."

A new Fox News poll finds 60% of registered voters think artificial intelligence use is moving too quickly, while 63% lack confidence in federal government's AI regulation ability.

Last year, Musk's AI company bought his social media company, X. CANADA - 2026/01/31: In this photo illustration, the SpaceX (Space Exploration Technologies Corp - Space X) logo is seen displayed on a smartphone screen. The merger will "form the most ambitious, vertically-integrated innovation engine on (and off) Earth, with AI, rockets, space-based internet, direct-to-mobile device communications and the world's foremost real-time information and free speech platform," Musk wrote in an update. The AI company that right now is best known for its CSAM-generating chatbot might seem like a strange fit for a rocket company. But SpaceX is key to Musk's latest scheme to build AI data centers in space. In his update, Musk wrote that "global electricity demand for AI simply cannot be met with terrestrial solutions" and that moving the resource-intensive operations to space is "the only logical solution."

HHS Is Using AI Tools From Palantir to Target'DEI' and'Gender Ideology' in Grants Since March of 2025, the Trump Administration has used tools from Palantir and the startup Credal AI to weed out "DEI" and "gender ideology from child welfare programs. A view of the Palantir building is seen during the World Economic Forum Annual Meeting 2026 in Davos, Switzerland. Since last March, the Department of Health and Human Services has been using AI tools from Palantir to screen and audit grants, grant applications, and job descriptions for noncompliance with President Donald Trump's executive orders targeting "gender ideology" and anything related to diversity, equity, inclusion (DEI), according to a recently published inventory of all use cases HHS had for AI in 2025. Neither Palantir nor HHS has publicly announced that the company's software was being used for these purposes. During the first year of Trump's second term, Palantir earned more than $35 million in payments and obligations ...

Like practically every other tech company under the sun, Mozilla has been jamming generative AI features into its products . The organization has now acknowledged that not everyone wants things like chatbots in the Firefox sidebar, so it's giving you the option to turn off all of that. On February 24 (or earlier in Firefox Nightly builds), Mozilla will roll out Firefox 148, which will include an AI controls section in the desktop browser settings. From here, you'll be able to block current and future generative AI features, or only enable select tools. At the jump, you'll have the option to disable (or enable) chatbots in the sidebar, automated translations and alt text generation for PDFs.

Before the EPA, Utah saw 100 times more lead exposure. Breakthroughs, discoveries, and DIY tips sent six days a week. The evidence is clear--and in your hair. Americans were exposed to as much as 100 times more lead in their daily lives than they are today before the Environmental Protection Agency was established in 1970. In an effort to examine the dramatic reduction in toxic heavy metal exposure, researchers turned to human hair samples dating back a century.

Science Dinosaurs Teen discovers Australia's oldest dinosaur fossil--almost 70 years ago An early sauropodomorph likely made the 230-million-year-old footprint. Breakthroughs, discoveries, and DIY tips sent six days a week. In 1958, an Australian teenager named Bruce Runnegar uncovered a mysterious dinosaur footprint during a visit to a quarry with school friends. He kept the fossil for years, eventually becoming a paleontologist himself. Over six decades later, the prehistoric print is now ready for its close-up.

Codex can now manage several AI assistants to complete complex tasks. Since last spring, OpenAI has offered Codex . What started life as the company's response to Claude Code is becoming something more sophisticated with the release of a new dedicated macOS app. At its most basic form, Codex is a programming agent capable of writing code for users, but now it can also manage multiple AI assistants that can work together to complete more complex tasks. OpenAI gives an example of how this could work in practice.