America will be AI DOMINANT!" Get your news from a source that's not owned and controlled by oligarchs. In recent weeks, a fresh crop of people connected to the artificial intelligence industry have emerged to warn that AI is possibly going to kill us all, spreading the word with various degrees of credibility or self-interest. Anthropic chief and co-founder Dario Amodei has also called to slow down the development of AI technology, a recommendation that Sam Altman of OpenAI and even notorious good judgment-haver Elon Musk quickly cosigned. Meanwhile, the Trump administration and the president himself have continued to insist that AI is essential for American technological advancement and military might. As a very strange public debate has ensued, it's become clear that Trump, Defense Secretary Pete Hegseth, and other people connected with the administration view AI as an essentially masculine tool: "dominant," a word they keep using over and over, powerful, and able to be kept in check only by a strong ruler. The Trump administration has become a place where very odd politics around both gender and "wokeness" are constantly on display. Trump issued a garbled executive order immediately upon retaking office that attempted to redefine "male" and "female ." Hegseth is obsessed with testosterone, announcing in July that military members will be screened for low T regardless of their gender. The intense focus on gender and wokeness has also been true of their approach to AI: Last year, the administration promised that it would require AI companies with federal contracts to make sure their large language models match the administration's views on things like climate change; transgender identity; and diversity, equity and inclusion initiatives. Trump has turned "a debate about technology into a debate about who's got the phallus." It's now increasingly obvious that Trump and his administration view AI technology as something akin to a large, dangerous dog that only a masculine owner can control. Trump has repeatedly called warnings that AI could harm human beings "a hoax," writing on TruthSocial that the "only control or'guardrails' that AI needs is a STRONG AND SMART (High IQ!) PRESIDENT, and the U.S.A. has that, in spades!" "The people that say AI is going to destroy the World, and that Data Centers are bad for your neighborhood, are the same people that said, just a short time ago, that the World would be extinguished by'Climate Change,'" the president also posted, with his trademark random capitalization. "That HOAX never worked out for them, and now they're on to the next one.

Current and former artificial intelligence researchers in the United States have issued dire warnings that the technology could soon lead to human extinction, capturing the attention of lawmakers in Washington. The most recent warning came in a lengthy social media post by Jacob Coxon, a San Francisco-based researcher who announced his resignation from Anthropic on Tuesday evening. This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible - but I hear the same people express fear," Coxon said in his post, which prompted a flurry of responses by AI experts also sounding the alarm. Evan Hubinger, a current Alignment Science lead at Anthropic, echoed his remarks, saying, "we really do earnestly believe AI could kill all humans!

We develop a module-based method that having a dictionary of well fitted GPs, one could build ensemble GP models without revisiting any data.

In Figure 1 (left) weseethat Gaussian posteriors (intheabsenceofdata) optimizedwith Eq. (1) convergetotheirpriorN(w|0,1)[7,68]. In CMV -MF-VI, shown in (b.), prunedunitsconvergetospiked Gaussians.

We develop a framework for generalized variational inference in infinitedimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI).

Sophie Turner as Lara Croft generates fan excitement after Prime Video releases first look photos from the upcoming live-action "Tomb Raider" series currently in production.

Sophie Turner reveals intense 8-hour daily training for upcoming "Tomb Raider" film as Lara Croft. The "Game of Thrones" actress discusses her physical preparation since February 2025.

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Although it is, at least according to the Library of Congress, the most-watched movie of all time, The Wizard of Oz was a costly failure at the box office, and only became a perennial favorite thanks to the regular TV airings that began in the 1950s. But in the decades since it's become a metonym for the wonder of the big screen, a movie even people who prefer their content streaming will make the effort to see in a movie theater. Beginning on Labor Day weekend, audiences will get to experience the movie on perhaps the largest screen ever created. But it won't be The Wizard of Oz as we've come to know it for the better part of a century. The version of the movie that will fill Las Vegas' Sphere starting Aug. 28 has been retooled to fit the venue's curved shell, its images enhanced and expanded to fill four football fields' worth of 16K LED screens--the foundation of an immersive presentation that also includes flames, gusts of wind, and inflatable flying monkeys piloted by drone. It is, to quote the title of a CBS news report, "The Wizard of Oz as you've never seen it before."

Large language models (LLMs), inspired by neuroscience, exhibit behaviors that often evoke a sense of personality and intelligence-yet the mechanisms behind these effects remain elusive. Here, we operationalize Conceptual Blending Theory (CBT) as an experimental framework, using prompt-based methods to reveal how LLMs blend and compress meaning. By systematically investigating Prompt-Induced Transitions (PIT) and Prompt-Induced Hallucinations (PIH), we uncover structural parallels and divergences between artificial and biological cognition. Our approach bridges linguistics, neuroscience, and empirical AI research, demonstrating that human-AI collaboration can serve as a living prototype for the future of cognitive science. This work proposes prompt engineering not just as a technical tool, but as a scientific method for probing the deep structure of meaning itself.