fjo3 shares a report from Defense One: A small but growing number of European officials and analysts are saying what four years ago was unthinkable: Ukraine isn't just surviving its grueling war with Russia, it is in some ways thriving and may even be on a path to victory. This isn't yet captured in headlines -- for example, about last weekend's barrage of Russian drones and missiles around Ukraine -- but in the details, like how some 90 percent were intercepted. Several long-term trends have shifted in Ukraine's favor, and the core reason is its fierce focus on AI and robotics. In the crucible of war, Ukraine has developed drones and ground robots that can hold territory -- even take it back. Some are fully controlled by humans, like supply robots and medical-evacuation vehicles. But an increasing number are controlled in at least some aspects by dozens of AI products, from guidance packages on aerial drones to decision aids at the highest levels. [...] Just as important as the tech are the new tactics. Given unusual latitude to experiment, Ukrainian fighters began to develop robot-forward infantry concepts, like combined-arms attacks by airborne and ground systems, "more than a year ago. Right now, we're massively starting to implement this," said Davyd Aloian, deputy secretary of the National Security and Defence Council of Ukraine, the coordinating body on domestic and international security, in an interview. Ukraine and its partners are also steaming ahead on new concepts for highly autonomous defenses against Russian drones, combining ISR sensors and AI to detect and identify enemy drones in less time and with more certainty. "All of the systems are being linked with each other and with people" to create a distributed network with interceptor drones at various locations to be activated when needed, Aloian said. "One day we will have only like 10 guys who are just going to be responsible for approving interception. And it will automatically go direct to the target." The human operators will be dispersed as well. "Everything can be controlled from Kyiv, Lviv, from cities in other countries," he said. "It's not what happened to Ukraine" (referencing Russia's barrage of Shahed drones) that "should scare us in Europe," said Swarmer CEO Serhii Kupriienko. It's how quickly Ukraine's "middling" military evolved to counter Russia's invasion. "We are behind by literally 10 years or 20 years" in some defense-technology areas, such as satellite imagery, Kupriienko said, and yet his country has climbed a capability curve that just two years ago seemed insurmountable. So could others, he said. "The answer is always AI solutions and integrating the AI into even the daily routine work within the bureaucracy," he said. "We have evolved since 2022, the industry has and our defense has as well. Right now we are able to provide not only [large quantities of drone] assets but everything what is needed to build out the ecosystem," including parts and production, training, modification, etc. Aloian said.

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An anonymous reader quotes a report from NPR: The buzz on college campuses is that AI is disrupting the job market for young college graduates. But new research from the Federal Reserve Bank of New York finds that the culprit may be something else: remote work. An analysis of federal employment data, paired with a deep dive into the flexible work arrangements at one unnamed Fortune 500 tech company, reveals that companies are less likely to hire recent college grads into occupations that can be done remotely. Researchers speculate that employers are reluctant to put such workers in a setting where it's harder to absorb lessons from coworkers. The researchers found the unemployment rate among younger college grads -- those under the age of 29 -- rose 20% after the pandemic, while unemployment among older college grads fell slightly. The study compares unemployment rates pre-pandemic, from 2017 to 2019, with unemployment rates after the pandemic, from 2022 to 2024. Unemployment rose as remote work grew fourfold, the researchers write. "Our analysis suggests that these trends are related, with remote work making it more difficult for managers to train and mentor new employees." Regardless of the cause, the New York Fed report warns that a high unemployment rate among young college grads is concerning. "Early-career experiences can have lasting consequences," the researchers write. "Research finds that individuals who began looking for jobs in slacker labor markets tend to have lower earnings and slower career progression relative to comparable peers who began their job search in better market conditions." Further reading: Why Is the US Job Market So Tough, Especially for Recent College Grads?

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A historian-turned-software engineer warns that "so little is ever written down" by professional programmers in a new article for Fast Company: Perhaps there's an early design doc, but then it turns out that everything was substantially revised before work began. Maybe there are a few wiki pages explaining known issues, some of which were solved a long time ago and others that have been left to molder in the codebase. Somebody might have left a comment in the code itself, but typically it's a warning not to change something or else something else will break... Software engineering has an ambivalent relationship with documentation. Everyone agrees documentation matters in theory, but in practice it's inconsistent, outdated, or missing entirely. Part of that is simple inertia. Writing documentation is usually less interesting than writing the code itself. But it's also ideological. The Agile movement emerged in part as a reaction against the heavily documented Waterfall methodology, and one of Agile's core values explicitly prioritizes "working software over comprehensive documentation." In escaping bureaucratic overdocumentation, the industry also normalized underdocumentation. High turnover at software jobs always brings "a constant drain of domain knowledge." And he's he's skeptical that generative AI will be able to fill in those gaps: [H]aving it generate documentation on the codebase itself might sound like a solution to the absence of other written information. LLMs can certainly summarize code back to you. But hold up with that idea. Beyond hallucinations, there's a deeper problem: Writing documentation is itself part of the thinking process. Whether I'm writing history or software, putting an approach into words helps refine it before I sink hours into implementation. Documentation also captures intent. An LLM may be able to summarize what a codebase does, but it cannot reliably explain why a developer chose one approach over another, or what trade-offs shaped that decision... An LLM can read code that I've written. It might even scan a large codebase and accurately summarize what it's doing. But it can't assess authorial intent. Thanks to long-time Slashdot reader smooth wombat for sharing the article.

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