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There is a difference between sharing the tech hype, and risk management. Why would our political and military leadership not be interested in this sort of tech

by devjab 3y ago

There is a difference between sharing the tech hype, and risk management. Why would our political and military leadership not be interested in this sort of tech in the modern world? If it doesn’t work out, then it doesn’t work out, but if it does, then they’ll want in on it. Aside from that there is the mass surveillance angle on it. We recently had a nice scandal of sorts here in Denmark where the chief of our secret military or whatever you’d call this was arrested by our secret police because he may or may not have shared secrets about how the US spies on us. It was something that even included charges against our former minister of defence possibly leaking things, something which could have seen him twelve years in prison. Luckily our courts saw it as a political matter and refused to let it run in closed proceedings which led to charges being dropped. The matter of the leaks were very “Snowdeny” in that it’s possibly that parts of our own government and our secret police share all Danish internet traffic with the NSA, who then in tern share information with our secret police. Which meant that our secret police could do surveillance on us as citizens through a legal loophole, as they aren’t allowed to do they directly, but are allowed to share surveillance information with the NSA. Part of this information comes from the giant American tech companies as well. Despite their promises to not share the data they keep for you. I know it’s sort of crackpot sounding, but between echelon, Snowden and the ridiculous amounts of scandals, I think it’s safe to assume that the American military wants in on LLMs and monitor all the inputs people put into ChatGPT and similar. So for that reason alone they’d want in on things. Then there is how the war in Ukraine has shown how cheap drones are vital in modern warfare, and right now, they need to be manually controlled. But what if they didn’t? Maybe that’s not obtainable, but maybe it is. Then there is all the other reasons you and I can’t think of. So even if they don’t believe it’s eventually going to lead to an AGI, or whatever else the hype wants, they’re still going to be interested in technology that’s already used by so many people and organisations around the globe.

sanderjd 3y ago
I'm sure they're interested in it, but I'm uncertain that they view it as a promising and critical enough capability to push for a higher priority when weighed against other interests. For instance, neither of your examples - surveillance or automated drones - has anything to do with AGI. They don't need LLMs to do mass digital surveillance; they already do that and were doing it for decades before LLMs were a twinkle in anyone's eye. Sure, they'll try to tap into the user data generated by chatgpt etc. (and likely succeed), but that's not a different capability than what they're already doing. And automating drones - which, by the way, this is not future technology as you seem to imply, it's here today - is a special purpose ML system, that maybe benefits from incorporating an LLM somewhere, but certainly isn't pinging the chatgpt api! But sure, you're exactly right at the end, I have no idea whether they see other angles on this that are new and promising. That's why I asked the question, I'm very curious whether there are any real indications thus far that militaries think the big public LLM models will be useful enough to them that they'll want to put a thumb on the scale to favor the companies running them over the companies that make their bucks on copyrighted content.
- samus 3y ago
  Wiretapping vast amounts of data on the internet is quite cool, but actually sifting through all that data is the really difficult part. Right now intelligence services are probably looking at lots of false positives and lots of dots they can't connect because the evidence is just too dispersed for a human or a current-generation system to make sense. LLMs could enable them to make the analysis more targeted and effective. But for all we know intelligence services could be using LLMs for years now, since they are usually a few years ahead of everybody else in many regards :-)
  - jcgrillo 3y ago
    > LLMs could enable them to make the analysis more targeted and effective. How? I'm not trying to be combative, I genuinely am curious if you have an idea how these things could be usefully applied to that problem. In my experience working in the information security space, approximate techniques (neural nets, etc.) haven't gotten much traction. Deterministic detection rules are how we approach the problem of finding the needle in the hay pile. So if you have a concrete idea here that could represent an advancement in this field.
    - pixl97 3y ago
      I guess my next question is how many needles do you find and how sharp are they? Detection rules would filter out most of the noise, then something like an LLM would do a post filter for intent analysis to rank relative risks for human intelligence to look at.
      - jcgrillo 3y ago
        I suspect this would disincentivize operators to take care in the way they write their detection rules, and the nondeterminism of the LLM would then result in false negatives. So the rate of growth of the needles set would increase, and the analysts would be getting lower quality information mediated by the LLM. In a world where false negatives--i.e. failing to detect a sharp needle--are the worst possible failure mode, approximations need to be handled with exceeding care.

by devjab 3y ago

sanderjd 3y ago

I'm sure they're interested in it, but I'm uncertain that they view it as a promising and critical enough capability to push for a higher priority when weighed against other interests. For instance, neither of your examples - surveillance or automated drones - has anything to do with AGI. They don't need LLMs to do mass digital surveillance; they already do that and were doing it for decades before LLMs were a twinkle in anyone's eye. Sure, they'll try to tap into the user data generated by chatgpt etc. (and likely succeed), but that's not a different capability than what they're already doing. And automating drones - which, by the way, this is not future technology as you seem to imply, it's here today - is a special purpose ML system, that maybe benefits from incorporating an LLM somewhere, but certainly isn't pinging the chatgpt api! But sure, you're exactly right at the end, I have no idea whether they see other angles on this that are new and promising. That's why I asked the question, I'm very curious whether there are any real indications thus far that militaries think the big public LLM models will be useful enough to them that they'll want to put a thumb on the scale to favor the companies running them over the companies that make their bucks on copyrighted content.

samus 3y ago
Wiretapping vast amounts of data on the internet is quite cool, but actually sifting through all that data is the really difficult part. Right now intelligence services are probably looking at lots of false positives and lots of dots they can't connect because the evidence is just too dispersed for a human or a current-generation system to make sense. LLMs could enable them to make the analysis more targeted and effective. But for all we know intelligence services could be using LLMs for years now, since they are usually a few years ahead of everybody else in many regards :-)
- jcgrillo 3y ago
  > LLMs could enable them to make the analysis more targeted and effective. How? I'm not trying to be combative, I genuinely am curious if you have an idea how these things could be usefully applied to that problem. In my experience working in the information security space, approximate techniques (neural nets, etc.) haven't gotten much traction. Deterministic detection rules are how we approach the problem of finding the needle in the hay pile. So if you have a concrete idea here that could represent an advancement in this field.
  - pixl97 3y ago
    I guess my next question is how many needles do you find and how sharp are they? Detection rules would filter out most of the noise, then something like an LLM would do a post filter for intent analysis to rank relative risks for human intelligence to look at.
    - jcgrillo 3y ago
      I suspect this would disincentivize operators to take care in the way they write their detection rules, and the nondeterminism of the LLM would then result in false negatives. So the rate of growth of the needles set would increase, and the analysts would be getting lower quality information mediated by the LLM. In a world where false negatives--i.e. failing to detect a sharp needle--are the worst possible failure mode, approximations need to be handled with exceeding care.