To play this video you need to enable JavaScript in your browser. As Russia's attacks on Ukraine's cities intensify and autumn's cooler temperatures hint at another tough winter to come, Ukrainians are wrestling with how to meet the twin challenges ahead: Russian drone and missile strikes and the biting cold. It was a very difficult winter last year in Kyiv, says mother of two Mariia Shostak, who is now packing her bags and leaving her small flat. With prolonged periods of sub-zero temperatures and frequent power cuts brought about by Russia's attack on the country's power grid, last winter was one of the hardest so far. There were some days and weeks that were unbearable.

Fuel particles embedded in the dirt aren't changing much, and that's actually a good thing. 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 general view shows the current state of the 18.6-mile Chernobyl Exclusion Zone. Established in the aftermath of the 1986 nuclear disaster at the Chernobyl Nuclear Power Plant, the 1,003-square-mile restricted area remains under strict state control. Just over 40 years ago, what began as a routine safety test at the Chernobyl nuclear power plant (or Chornobyl in Ukranian) in Soviet Ukraine spiraled into one of the most recognizable disasters of the 20th century.

As AI takes on more autonomous roles in industrial settings, organizations need new approaches to data, governance, and human oversight, says Arti Garg, chief technologist at AVEVA. Industrial AI is entering a new phase. After decades of predictive analytics and other specialized applications, advances in foundation models, physical AI, and agentic AI are making it possible to automate more complex tasks across industrial environments. But unlike AI that operates purely in the digital world, industrial AI can interact directly with physical systems, where an unexpected decision can have consequences for safety, reliability, and critical infrastructure. That makes responsible deployment central to the next wave of industrial automation. "How do we leverage these technologies while maintaining safety, while maintaining reliable operations, while still being able to deliver on the promises of the new capabilities?" asks Arti Garg, chief technologist at AVEVA. The challenge is particularly acute as newer AI systems become more capable but also harder to predict and explain. One foundation for making that transition work is data. Industrial systems often contain information across telemetry, service logs, engineering documents, and other disparate sources.

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Another OpenAI employee tasked with ensuring the safety of its models has left. Following his departure, David Robinson, who used to lead the writing of safety reports that were published with model launches, wrote an article for The Atlantic that warned of a "broken" company culture. Among the many points warning of the dangers associated with the trajectory that AI development is on, the former safety lead explained that "as the company springs from one launch to the next, it is failing to achieve the level of care that I believe is needed." Instead of sprinting ahead with more advanced frontier AI models, Robinson argued that these companies should be modeled after nuclear power plants or busy airports that have "layers of redundancy and careful, time-consuming planning, so that the occasional and inevitable human error does not open a door to disaster." Comparing AI misalignment incidents to a nuclear meltdown, Robinson said that OpenAI and its competitors don't have as much redundancy and rigor as power plants with multiple layers of protection.