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Regarding (2), automating surveillance at scale. If you manage to put a bunch of listening devices at a place you're moderately interested in, a cafeteria at a
by miki123211 3y ago
Regarding (2), automating surveillance at scale.
If you manage to put a bunch of listening devices at a place you're moderately interested in, a cafeteria at an enemy base for example, you might end up with literally hundreds of hours of conversations, most of them completely uninteresting, but a few that might possibly contain nuggets of information of the utmost importance. Listening to all these conversations requires resources. This is even more difficult if the people there speak in jargon, in their own language, and nobody but an expert in the subject can determine which conversation snippets are significant.
If you have good LLMs, you can run all your recordings through extremely high-quality speech recognition and then use something like Chat GPT for summarization, classification, finding all mentions of the nuclear reactor in <place> etc. Same goes for satellite image analysis.
- jcgrillo 3y agoI think we'd need to see these things get a lot more reliable for them to be viable in this use case. This seems like a "leaky net" as opposed to some more deterministic strategy (e.g. grepping large lists of keywords, or parallelizing the task over thousands of human analysts). When you're looking for a needle in a haystack you need to inspect every leaf and stalk. So should we put copyright through the shredder on the wager that somehow generative techniques will find applications for mass surveillance?