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My assumption is that only part of those $1 tn will go specifically into generative applications. The Goldman Sachs' paper in most instances mentions AI in general.

But one can also argue that actively seeking and choosing targets is a generative task, given a proper encoding of a battlefield situation and current mission.

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Except that in spite of enormous investments and engineering efforts we still have problems with fully autonomous vehicles and it's unclear it would really happen anytime soon, and here the classification problem is whether you're going to bomb an enemy or your own people. I'm not saying it's not gonna happen but it's terribly hard and 80% accuracy can wreak havoc on innocent people.

Russian air force has already destroyed numerous civilian buildings, in many cases killing dozens of people far behind the frontlines[0]. In at least one case, when 59 people attending a soldier's funeral were killed, there are "reasonable grounds to believe that the reception was the intended target of an attack, using a precision weapon"[1]. I think it shows that the military will be happy with much lower quality of classification than e.g. acceptable for driving in downtown San Francisco.

[0] https://en.wikipedia.org/wiki/Attacks_on_civilians_in_the_Ru... [1] https://www.ohchr.org/en/documents/country-reports/attack-fu...

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