Nate Soares doesn't set aside money for his 401(k). "I just don't expect the world to be around," he told me earlier this summer from his office at the Machine Intelligence Research Institute, where he is the president. A few weeks earlier, I'd heard a similar rationale from Dan Hendrycks, the director of the Center for AI Safety. By the time he could tap into any retirement funds, Hendrycks anticipates a world in which "everything is fully automated," he told me. That is, "if we're around."

In recent years, machine learning (ML) has offered new modeling approaches for natural and engineering sciences.

Fox News anchor Bret Baier has the latest on the Murdoch Children's Research Institute's partnership with the Gladstone Institutes for the'Decoding Broken Hearts' initiative on'Special Report.' The benefits of artificial intelligence (AI) in the medical space are ever-growing, but evidence suggests it can also come with risks. A new study by European researchers investigated how AI can change the behavior of endoscopists when conducting a colonoscopy, and how their performance dips when not using AI. The research followed clinicians at four endoscopy centers in Poland participating in the ACCEPT (Artificial Intelligence in Colonoscopy for Cancer Prevention) trial, where AI tools for polyp detection were introduced at the end of 2021. Colonoscopies at these centers were randomly selected to be administered with or without AI assistance.

Starlink is absolutely critical to Ukraine's ability to continue in the fight against Russia. It's how troops in battle zones stay connected with faraway HQs; it's how many of the drones essential to Ukraine's survival hit their targets; it's even how soldiers stay in touch with spouses and children back home. However, Donald Trump's fickle foreign policy and reports suggesting Elon Musk might remove Ukraine's access to the services have cast the technology's future in the country into doubt. For now Starlink access largely comes down to the unofficial community of users and engineers, including the expert "Dr. Starlink"--famous for his creative ways of customizing the systems--who have kept Ukraine in the fight, both on and off the front line.

The latest addition to China's Tiangong space station is an AI chatbot with expertise in navigation and tactical planning. Named Wukong AI--after the protagonist of the "Monkey King" legend in Chinese mythology, Sun Wukong--the chatbot was introduced on the space station in mid-July, and has already completed its first mission: supporting three taikonauts during a spacewalk. Information about Wukong AI remains limited. Chinese authorities have said that they developed it from a domestic open-source AI model; according to Xinhua, China's state-run news agency, engineers designed it to meet the requirements of manned space missions, and focused its knowledge-base on aerospace flight data. "This system can provide rapid and effective information support for complex operations and fault handling by crew members, improving work efficiency, in-orbit psychological support, and coordination between space and ground teams," Zou Pengfei of the taikonaut training center, told Xinhua.

At least one person has been killed and 18 others wounded in a Russian drone and missile attack on Ukraine, officials said, as Moscow launched its largest attack on its neighbour in weeks amid an ongoing diplomatic push for a ceasefire. Russian forces launched 574 drones and 40 missiles overnight, Ukraine's Air Force said on Thursday, adding that its air defence units had downed most of the attacks. But a number of the attacks struck targets in several locations across Ukraine, resulting in casualties and damage to buildings. In the western city of Lviv, about 70km (43 miles) from the border with Poland, a drone and missile attack killed one person, injured three and damaged 26 residential buildings, Governor Maksym Kozytskyi said. In Mukachevo, near the border with Hungary and Slovakia, 15 people were wounded in Russian attacks, local authorities said.

This phenomenon is especially prominent in high-noise settings.

Surprisingly, applying over 20 established estimators to the dataset produces inconsistent results in evaluating the nonprofit's efficacy.

Precise and comprehensive situational awareness is a critical capability of modern autonomous systems. Deep neural networks that perceive task-critical details from rich sensory signals have become ubiquitous; however, their black-box behavior and sensitivity to environmental uncertainty and distribution shifts make them challenging to verify formally. Abstraction-based verification techniques for vision-based autonomy produce safety guarantees contingent on rigid assumptions, such as bounded errors or known unique distributions. Such overly restrictive and inflexible assumptions limit the validity of the guarantees, especially in diverse and uncertain test-time environments. We propose a methodology that unifies the verification models of perception with their offline validation. Our methodology leverages interval MDPs and provides a flexible end-to-end guarantee that adapts directly to the out-of-distribution test-time conditions. We evaluate our methodology on a synthetic perception Markov chain with well-defined state estimation distributions and a mountain car benchmark. Our findings reveal that we can guarantee tight yet rigorous bounds on overall system safety.