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.
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And many US firms, especially in tech, still have on their payrolls a glut of workers who were brought on during the pandemic, when there was a small hiring boom. That could also help explain the lack of new vacancies.
GlyphNet’s own results support this: their best CNN (VGG16 fine-tuned on rendered glyphs) achieved 63-67% accuracy on domain-level binary classification. Learned features do not dramatically outperform structural similarity for glyph comparison, and they introduce model versioning concerns and training corpus dependencies. For a dataset intended to feed into security policy, determinism and auditability matter more than marginal accuracy gains.