But what if it’s not fine? Even back in 1996, before a single component of the ISS was launched into orbit, NASA foresaw the possibility of an even worse worst-case scenario: an uncontrolled reentry. The crux of this scenario involves multiple systems failing in an improbable but not completely impossible cascade. Cabin depressurization could damage the avionics. The electrical power system could go offline, along with thermal control and data handling. Without these, systems controlling coolant and even propellant could break down. Unmoored, the ISS would edge slowly toward Earth, maybe over a year or two, with no way to control where it is headed or where its debris might land. And no, we could not save ourselves by blowing the station up. This would be extremely dangerous and almost certainly create an enormous amount of space trash—which is how we got into this hypothetical mess in the first place.
Why the FT?See why over a million readers pay to read the Financial Times.
，推荐阅读Line官方版本下载获取更多信息
小鹏发 2026 开工信：自动驾驶、机器人与全球化全面加速
异地过年、私厨上门、外卖配送……其实，年夜饭吃法早就不拘一格，预订餐厅年夜饭更是流行多年，今年却是我家第一次改革。
Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.