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Two questions: (1) Do you think "developing AGI" a realistic, achievable goal? If so, what evidence do you see that we're making progress on the problem of "ge

Two questions: (1) Do you think "developing AGI" a realistic, achievable goal? If so, what evidence do you see that we're making progress on the problem of "general" intelligence? Specifically, what does any of that have to do with Large Language Models? (2) Are there any "national security" applications of Large Language Models that you're aware of? It seems to me that it would be a very difficult case to make that the national security impact from allowing the rule of law to erode would be somehow outmatched by the (speculative) wager that somehow LLMs have some relevance to the national security. It would be an even harder case to make that any of this has something to do with "general" intelligence.

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 ago
  I 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?
pixl97 3y ago
As for 1, pass an image to a multimodal LLM and simply ask 'what is going on in this image'. Robot LLM models are already turning this in to actionable data they of which they can interact with the world. As in you can send a Robot into a room it has not been before and tell it "bring back a sock, a blue one not a red one" and get an actionable response with a higher degree of success. This takes some degree of general intelligence (though maybe not human level).
- jcgrillo 3y ago
  Well the real test of all this stuff is "what can I use it for?". And I can sort my own socks, so that's not super compelling ;). More seriously, the real world is complex. Let's say I want to replace the forklift operator at my local lumberyard with a robot forklift that can ostensibly outperform a human employee. Even if there is some magical AI program which could theoretically drive the forklift around, identify boards by their dimensions, species, dryness, location, etc., there's a whole bunch of sensory problems that a human body solves easily that are super hard to solve in the environment of a lumber yard. There's dust, rain, snow, mud--so if you're relying on cameras how will you keep them clean? You can't visually determine how dry a board is, you have to put a moisture meter on it and read the result. My point is, even if you have a "brain" capable of driving the forklift you still have a massively complex robotics problem to solve in order to automate just the forklift. And we haven't even begun to replace the other things the operator does in addition to driving the forklift. He can climb out of the forklift and adjust the forks, move boards by hand, affect repairs on equipment, communicate with other equipment operators, customers, etc. Good luck replacing him in a cost-effective manner. So what am I supposed to use it for?
  - pixl97 3y ago
    https://en.wikipedia.org/wiki/Moravec%27s_paradox https://en.wikipedia.org/wiki/Moravec%27s_paradox This is an issue of 'mechanical intelligence' being hundreds of millions of years old and 'higher intelligence' being pretty new on the evolutionary spectrum. And the AGI will keep you around as a dexterous 'robot' while supervising your thoughts to make sure you're keeping in line I guess, while day after day cranking out more capable robots in which to replace you with eventually.

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 ago
I 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?

pixl97 3y ago

As for 1, pass an image to a multimodal LLM and simply ask 'what is going on in this image'. Robot LLM models are already turning this in to actionable data they of which they can interact with the world. As in you can send a Robot into a room it has not been before and tell it "bring back a sock, a blue one not a red one" and get an actionable response with a higher degree of success. This takes some degree of general intelligence (though maybe not human level).

jcgrillo 3y ago
Well the real test of all this stuff is "what can I use it for?". And I can sort my own socks, so that's not super compelling ;). More seriously, the real world is complex. Let's say I want to replace the forklift operator at my local lumberyard with a robot forklift that can ostensibly outperform a human employee. Even if there is some magical AI program which could theoretically drive the forklift around, identify boards by their dimensions, species, dryness, location, etc., there's a whole bunch of sensory problems that a human body solves easily that are super hard to solve in the environment of a lumber yard. There's dust, rain, snow, mud--so if you're relying on cameras how will you keep them clean? You can't visually determine how dry a board is, you have to put a moisture meter on it and read the result. My point is, even if you have a "brain" capable of driving the forklift you still have a massively complex robotics problem to solve in order to automate just the forklift. And we haven't even begun to replace the other things the operator does in addition to driving the forklift. He can climb out of the forklift and adjust the forks, move boards by hand, affect repairs on equipment, communicate with other equipment operators, customers, etc. Good luck replacing him in a cost-effective manner. So what am I supposed to use it for?
- pixl97 3y ago
  https://en.wikipedia.org/wiki/Moravec%27s_paradox https://en.wikipedia.org/wiki/Moravec%27s_paradox This is an issue of 'mechanical intelligence' being hundreds of millions of years old and 'higher intelligence' being pretty new on the evolutionary spectrum. And the AGI will keep you around as a dexterous 'robot' while supervising your thoughts to make sure you're keeping in line I guess, while day after day cranking out more capable robots in which to replace you with eventually.