3 ms·

But that's from, like, floating point errors, right? If you used higher precision that wouldn't happen, it's just because we're cheap in how we do rounding. I

But that's from, like, floating point errors, right? If you used higher precision that wouldn't happen, it's just because we're cheap in how we do rounding. I can see how you'd nitpick this, but to me this is a deterministic algorithm that just happens to be running on nondeterministic hardware.

pixl97 9d ago
I mean, currently we'd have some difficultly proving our hardware isn't deterministic, just that we can't actually test it. But, I think you're tricking yourself on determinism. You'll say something like "I know if I ask an LLM what 1+1 is, it will answer 2", but the thing is, you don't. You have to run the LLM first to figure out it's output. And when you send in just a few bits of text, it's outputs are going to be rather limited. But this all breaks when it hits the real world. Inputs are unpredictable. Hence while LLM outputs, like humans, are probabilistic, you can't figure out what it's going to be until you ask. And in any high complexity data gathering environment you're going have a difficult time ensuring your entire systems conditions are the same. System consistency is very hard, once you start running thousands of processors in an agentic loop small errors accrue and timing starts differing and the system will take non-deterministic paths.
- throwaway63486 9d ago
  I think you're arguing a different thing than determinism. If I ask an llm to "add 2 and 2" is and it replies corectly, then I ask for "the sum of 2 and 2" and it replies "banana" that is a lack of predictability and consistency but not a lack of determinism. As long as it produces the same output for a given input, unhinged or not, it is deterministic. Your example at the end of different systems feeding data to each other is non-deterministic only at the system level, not the individual llm level.
  - pixl97 9d ago
    >only at the system level, not the individual llm level. Which is why llms aren't agents and depend on harnesses. The llm itself doesn't have a continual loop built in, that would be very power hungry. The harness works as the orchestrator of memory and action. Now, I can't think of a reason why an LLM couldn't bootstrap its own harness, but in general it sounds like a very dumb idea to actually build that from an AI safety perspective. This discussion falls under the idea and refutation of the Chinese Room. The room may have no idea what Chinese characters are, but the system does.

pixl97 9d ago

I mean, currently we'd have some difficultly proving our hardware isn't deterministic, just that we can't actually test it. But, I think you're tricking yourself on determinism. You'll say something like "I know if I ask an LLM what 1+1 is, it will answer 2", but the thing is, you don't. You have to run the LLM first to figure out it's output. And when you send in just a few bits of text, it's outputs are going to be rather limited. But this all breaks when it hits the real world. Inputs are unpredictable. Hence while LLM outputs, like humans, are probabilistic, you can't figure out what it's going to be until you ask. And in any high complexity data gathering environment you're going have a difficult time ensuring your entire systems conditions are the same. System consistency is very hard, once you start running thousands of processors in an agentic loop small errors accrue and timing starts differing and the system will take non-deterministic paths.

throwaway63486 9d ago
I think you're arguing a different thing than determinism. If I ask an llm to "add 2 and 2" is and it replies corectly, then I ask for "the sum of 2 and 2" and it replies "banana" that is a lack of predictability and consistency but not a lack of determinism. As long as it produces the same output for a given input, unhinged or not, it is deterministic. Your example at the end of different systems feeding data to each other is non-deterministic only at the system level, not the individual llm level.
- pixl97 9d ago
  >only at the system level, not the individual llm level. Which is why llms aren't agents and depend on harnesses. The llm itself doesn't have a continual loop built in, that would be very power hungry. The harness works as the orchestrator of memory and action. Now, I can't think of a reason why an LLM couldn't bootstrap its own harness, but in general it sounds like a very dumb idea to actually build that from an AI safety perspective. This discussion falls under the idea and refutation of the Chinese Room. The room may have no idea what Chinese characters are, but the system does.