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The discussion reminds me of Karl Sims’ Evolved Virtual Creatures. In the Siggraph talk he mentioned that they would absolutely exploit any bugs in the physics
by dahart 2y ago
The discussion reminds me of Karl Sims’ Evolved Virtual Creatures. In the Siggraph talk he mentioned that they would absolutely exploit any bugs in the physics simulation that they could. That’s all that’s happening with this article’s LLMs - the metric is dictator, and simply and predictably leads to any and all possible behaviors that achieve higher scores.
https://www.youtube.com/watch?v=RZtZia4ZkX8 https://www.youtube.com/watch?v=RZtZia4ZkX8
You know what’s really weird though? In a very long and detailed and thoughtful post about how AIs are behaving in surprising ways and doing something other than what they “say”, it is non-stop anthropomorphizing the AI in practically every sentence. The number of silly statements about what Claude “thinks”, or that it “fights”, what it’s “choosing”, how it’s “pretending”… it goes on and on and on speaking as if it’s human. It’s not human. The very problem here is projecting meaning onto a machine. LLMs are statistical token generators and they don’t have values or agenda, and don’t know what faking is. The analogies are specious and hyperbolic; they’re tempting to believe. Sure some humans do fake things sometimes, but not for the same reasons. Everything having to do with thoughts, opinions, values, and alignment, come from the training data, and specifically our interpretation of the training data, which the LLM can only fake because that’s how it was designed.
The behavior isn’t the least bit surprising when you think of it as a machine, it’s only surprising when we treat LLMs as if they’re people. And the more we buy into the anthropomorphizing, the worse this problem gets.
- energist11 2y ago[dead]
- cbzbc 2y ago> The discussion reminds me of Karl Sims’ Evolved Virtual Creatures. In the Siggraph talk he mentioned that they would absolutely exploit any bugs in the physics simulation that they could. That’s all that’s happening with this article’s LLMs - the metric is dictator, and simply and predictably leads to any and all possible behaviors that achieve higher scores. Similarly those programs that are trained to play games that end up exploiting weird corner cases in the underlying code. In each case it's just a automated processing expanding to fill available phase space.
- timmytokyo 2y agoJust a couple years ago, numerous people (including here) were ridiculing Blake Lemoine, the fired Google AI engineer, for seeing "sentience" in an LLM. Now it seems nearly everyone has become Blake Lemoine. It's fascinating to observe how prone to pareidolia we are. Our wetware pattern matchers are ready to fire off positive signals at the first sign of anything even slightly approaching "human", whether it's faces or -- more recently -- language. These primitive ape brains are fooling us into thinking we're talking to an "intelligence".