Олег Давыдов (Редактор отдела «Интернет и СМИ»)
AI 自动编程：一句话设计高颜值博客
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Plan for iterative improvement rather than expecting immediate perfection. AIO is still an emerging practice without definitive best practices etched in stone. You'll make mistakes, try things that don't work, and occasionally optimize for factors that turn out not to matter. This experimentation is part of the learning process. What matters is systematic iteration—trying approaches, measuring results, adjusting based on feedback, and gradually improving your effectiveness over time.
There is a plan to prevent such a strike—the Space Surveillance Network, a bevy of sensors that the military uses to track space debris. NASA monitors what’s unofficially known as the “pizza box,” a sort of no-fly zone around the ISS. When pieces of debris are predicted to enter the box—if there’s at least a 1 in 100,000 chance of collision—mission controllers order avoidance maneuvers, firing thrusters that move the ISS and dodge the trash. The technique has been used dozens of times since the first ISS module launched in 1998. But the system only tracks about 45,000 larger pieces, and all sensors have noise. Plus, risk thresholds can miss stuff, sometimes badly. In 2025, Chinese astronauts were briefly stranded at their station after debris hit their return vehicle.