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Almost certainly not. It will generate things that look like the text of scientific papers on a casual glance, but which will be dream-logic gibberish if you ac

by Figs 7y ago

Almost certainly not. It will generate things that look like the text of scientific papers on a casual glance, but which will be dream-logic gibberish if you actually read it. The unicorn example makes no sense if you stop and think about what it's actually saying. e.g. a "unicorn" that has four horns? Solves a 200 year old mystery... about something just discovered? So close you could touch their horns... while viewing them from the air? It doesn't make sense if you actually think about it at all, but if you're not really paying attention, the style is like a news report. It's better at making up bullshit, but it's still bullshit.

MegaButts 7y ago
This is a good point, and it's a little concerning to me that we will likely soon be inundated not just with spam from lowly-paid shills, but literal bots generating a near endless supply of confident-sounding nonsense. I am not an expert with machine learning, but it seems (at a very high level) we've done amazingly well at creating models that can recognize and sometimes recreate patterns. But they never seem to have any ability to understand the patterns. I'm sure someone much more knowledgeable could compare it to a child of whatever age (or maybe I'm just completely wrong).
derefr 7y ago
I fully believe that this is 90% of what the human brain is doing to solve the same problems, though. Brains just also have a constraint/filter layer, determining which of these bits of "made up bullshit" should be allowed to rise from the layer generating them, to the motor output layer. Or, to put that another way, flipping the perspective around: our minds could consist of an intelligent, analytical, but utterly unimaginative agent, that sits there listening to a stream of suggestions spewed out by a distinct second agent, one that is "creative" but has no idea about the constraints of things like physics. The brain's analytical agent filters this stream of suggestions, taking notice of the suggestions that seem like they'll make the world change in the ways it "wants"†; and then it does those. † Or, according to modern perceptual-control research, the agent attempts to predict the world that will occur a few seconds in the future, with a bias toward predicting world-states the reward-system has annotated as being rewarding; and then it looks at what motor commands it "would have" issued in that hypothetical world, and actually issues those. The stream of suggestions, in this model, serve as input to feed the generative model of potential world-states; the executive agent then must notice whether the potential world-state is a "possible" world or an "impossible" world (and whether the motor commands required of it are "possible" or "impossible" inputs), and filter out the "impossible" worlds. Under this hypothesis, dreaming is the state when your executive responsible for filtering out "impossible" worlds isn't online. So you just get a continuous "impossible" world generated from the streamed suggestions of the creative-but-stupid bullshit-generating agent, with nothing to tear it down—just as seen in these generative AIs. As consciousness returns, the mental predicted world-state is noticed to be impossible by the now-online analytical agent, and is torn down.
- red75prime 7y ago
  > which of these bits of "made up bullshit" should be allowed to rise from the layer generating them That will be a lot of bullshit to filter out, if such agent doesn't provide more of less detailed description of what has to be generated. People with Broca's aphasia probably demonstrate a part of such input.
  - derefr 7y ago
    Sure; the sequence of hypothetical world-states being constructed by the prediction agent would likely be fed back as stimuli to excite features within the generative network (which it would know associations for, since these hypothetical world-states are stimuli of the same "type" as the real world-state stimuli it was trained on.) In other words, it could operate just as AI generative networks like GPT2 do, first receiving training input/output pairs; and then later, receiving input prompts and "completing" them by generating outputs.
gwern 7y ago
Let's not undersell it. Yes, you can identify inconsistencies in the unicorn example (if you are reading it more carefully than many people, HNers included, read most things), and some of the other examples, like the LoTR one, are more blatantly inconsistent than that. But on the other hand, look at the anti-recycling example: is there a single inconsistency in it? (On Twitter, someone insisted to me that the anti-recycling example proved GPT-2 was merely memorizing human input and spitting it back out - specifically, copying from Reddit, because they found a post of it on Reddit, until I pointed out to them that the timestamp was after OA's announcement.) When it comes to attacks, it's not the average-case which matters.

by Figs 7y ago

MegaButts 7y ago

This is a good point, and it's a little concerning to me that we will likely soon be inundated not just with spam from lowly-paid shills, but literal bots generating a near endless supply of confident-sounding nonsense. I am not an expert with machine learning, but it seems (at a very high level) we've done amazingly well at creating models that can recognize and sometimes recreate patterns. But they never seem to have any ability to understand the patterns. I'm sure someone much more knowledgeable could compare it to a child of whatever age (or maybe I'm just completely wrong).

derefr 7y ago

I fully believe that this is 90% of what the human brain is doing to solve the same problems, though. Brains just also have a constraint/filter layer, determining which of these bits of "made up bullshit" should be allowed to rise from the layer generating them, to the motor output layer. Or, to put that another way, flipping the perspective around: our minds could consist of an intelligent, analytical, but utterly unimaginative agent, that sits there listening to a stream of suggestions spewed out by a distinct second agent, one that is "creative" but has no idea about the constraints of things like physics. The brain's analytical agent filters this stream of suggestions, taking notice of the suggestions that seem like they'll make the world change in the ways it "wants"†; and then it does those. † Or, according to modern perceptual-control research, the agent attempts to predict the world that will occur a few seconds in the future, with a bias toward predicting world-states the reward-system has annotated as being rewarding; and then it looks at what motor commands it "would have" issued in that hypothetical world, and actually issues those. The stream of suggestions, in this model, serve as input to feed the generative model of potential world-states; the executive agent then must notice whether the potential world-state is a "possible" world or an "impossible" world (and whether the motor commands required of it are "possible" or "impossible" inputs), and filter out the "impossible" worlds. Under this hypothesis, dreaming is the state when your executive responsible for filtering out "impossible" worlds isn't online. So you just get a continuous "impossible" world generated from the streamed suggestions of the creative-but-stupid bullshit-generating agent, with nothing to tear it down—just as seen in these generative AIs. As consciousness returns, the mental predicted world-state is noticed to be impossible by the now-online analytical agent, and is torn down.

red75prime 7y ago
> which of these bits of "made up bullshit" should be allowed to rise from the layer generating them That will be a lot of bullshit to filter out, if such agent doesn't provide more of less detailed description of what has to be generated. People with Broca's aphasia probably demonstrate a part of such input.
- derefr 7y ago
  Sure; the sequence of hypothetical world-states being constructed by the prediction agent would likely be fed back as stimuli to excite features within the generative network (which it would know associations for, since these hypothetical world-states are stimuli of the same "type" as the real world-state stimuli it was trained on.) In other words, it could operate just as AI generative networks like GPT2 do, first receiving training input/output pairs; and then later, receiving input prompts and "completing" them by generating outputs.

gwern 7y ago

Let's not undersell it. Yes, you can identify inconsistencies in the unicorn example (if you are reading it more carefully than many people, HNers included, read most things), and some of the other examples, like the LoTR one, are more blatantly inconsistent than that. But on the other hand, look at the anti-recycling example: is there a single inconsistency in it? (On Twitter, someone insisted to me that the anti-recycling example proved GPT-2 was merely memorizing human input and spitting it back out - specifically, copying from Reddit, because they found a post of it on Reddit, until I pointed out to them that the timestamp was after OA's announcement.) When it comes to attacks, it's not the average-case which matters.