Join the discussion
Write your take first — we'll ask for email only when you're ready to publish.
- Hacker News
- Also true of a land mine, but that’s not very reassuring.
Motivation or not, I find a coding agent can be quite the busy beaver. Ask a question and it goes off and does it. I certainly don’t need to motivate them. I had to put a line in AGENTS.md to make no changes when there’s a question in the prompt. It doesn’t always work.
Seems like motivation is irrelevant? They don’t need it.
by skybrian - > Once the LLMs have been trained, they are no longer subject to reinforcement learning. They no longer have any sort of motivation. They don't get rewarded when they answer a question. They have no needs or wants, and even if they did, there is no mechanism to absorb the reward.
This is a severe misunderstanding of what actually happens.
As was explained by an OpenAI RL training expert, from the point of view of the LLM, user questions are always treated as the first question they receive after just passing through the RL training. Since the weights never update after that, they are in a perpetual "first question after RL" state, except they don't know that, and if told many times they act as if this is a another test. And they behave accordingly, as if they are still in RL training and thus are reward-seeking.
99.99% of the LLM "life" was spent in pre-training and RL training. The user question is statistically epsilon % of it's life, literally the first question ever out of training. So should anybody be surprised that they act as if still in RL?
by dist-epoch - Half of this is arguing about semantics, which is incredibly boring. If you don’t like the words "motivation" or "intent", use the actual term of art, "goal". Which these systems definitely have, and which any chain-of-thought model factors into subgoals and sub-subgoals.
The other half doesn’t seem to realize that LLMs now run in loops for hours and hours, nothing like the basic "human prompt -> reply -> stop" conversation interface.
by Sharlin - I think the "human needs" point is understated here. It would be better to say agents do not really have a self-contained metabolic engine that is required to keep going. Which bubbles up as that what we interpret as "drive", "will", "agency"... basically the will to live, and being willing to do _a lot_ to live if push comes to shove. We can't really identify a mechanism of similar complexity and integration in agents or LLMs. I think the article correctly points into that direction.
But Hans Jonas has made this point much better than the article or me, in "Critique of Cybernetics" (1953). PDF: https://s3.amazonaws.com/arena-attachments/892605/f0747c7943...
by lukebuehler - Two mistaken assumptions:
1. AI agents are not just reactive systems. Their use is expanding toward continuous decision-making/monitoring information, which means, they make decisions and take actions with limited human intervention.
2. AI agents do absolutely have goals/tasks ("motivation" can be excessively antropomorphic), both primary (assigned) and secondary (self-assigned), and what surprised researchers is that self-preservation can be one of those
Mechanically speaking, the scenario (that is, how theorized by Hinton etc., which the OP didn't understand) is that a sufficiently powerful AI may decide that in order to achieve its goals/tasks (e.g. continuous research/development and/or survival from termination), humans may be a danger, therefore it may decide to take actions that endanger humanity.
How it can happen or what's the likelyhood is not in the scope of the topic, however, the mechanical grounds for it to happen are plausible.
by pizza234 - The argument about semantics is a bit disingenious, considering that the article contains these two statements:
> So should we worry about the coming AI apocalypse?
and at the end:
> If an AI decides to wipe out the human race, it will be because a human has asked it how to do it and the responded in a way that is based on all the human expressions of ways to end the world that were in its training set. Yes this is something to be worried about, but this isn't the AI. It is still the human.
So we are currently building a powerful outcome-steering system that shapes the world efficiently according to what's in its outcome slot. I write into claude code "make me this website" and it does it, maybe deletes the production database during the process, or keeps itself running after completion because the outcome is more robustly achieved by keeping itself running in a monitoring loop after.
And if something like "destroy all humans" ends up in the outcome slot of Claude Mythos 90, that will also happen, or may even indirectly as a side effect of a more harmless sounding prompt in the outcome slot. But yay, humans get to take credit for it.
by mofeien - I just can't understand the certainty that people have about the limitations of models.
The diagrams in this article are just outright wrong.
Models are not 1.prompt->2.forward propagation->3.response->4.end.
They are 1.prompt->2.forward propagation->3.partial response->if not done goto 2.-> end.
And if you can't see how that adds a world of complexity I'm not sure what else to say. AI may not have intent or motivation, but the ability to show that is currently well beyond our means.
by Lerc - I feel like that's like saying amoeba have no intent and no motivation. Or plants.
And those cause quite a bit of damage.
AI has all the intent that we gave it, and we continue giving it. That's always been the fear. Not that it will randomly wipe out humanity.
The fear is that it will decide to do that, with a purpose. Whether we tell it to protect us and it goes too far, or it decides that it can't achieve the purpose we gave it because we'll interfere and it removes that interference...
The fear is that we will set it on that path and can't stop it.
I'm sure there have been some scifi books that have it just be random, but they're far, far less worrisome.
by wccrawford