Explaining the reality with this approach may lead to misunderstandings. Especially when it comes to anthropomorphism.
I have 2 questions.
1. The text says "the robots were designed to be persistent" and links to an article that show that the word "persistent" was used by OpenAI. But "persistent" has several meanings: a. non temporary or non volatile (like "persistent memory"), b. will not give up and come back again and again, c. will stay focus and explore the unexplored possibilities while other models abandon at this stage.
From what I recall, the meaning used by OpenAI is not 'a', but there is still a semantic difference between 'b' and 'c'. I may myself have created algorithms that I called "persistent" because they were exploring or retrying more than the previous algorithm, but it is misleading to pretend that this algorithm was "persistent" in the human sense of the term. 'b' is more the human sense of the term, were we imagine someone not giving up even if people say no, while 'c' is less anthropomorphic and may mean that the people wished to improve the algorithm so it does not stop at the first little hurdle but did not wish to make it "never give up".
Does someone know which nuance is more correct?
2. The text also presents the situation as if the robots found the solution but then went out of their way to steal the explanation in order to hide their cheating. But it is different from a situation where the agents task was "provide the solution and how we can get there". In this case, the reason the agent still continued is just because the task was not complete yet.
I'm not trying to defend AI or OpenAI, on the contrary, I'm quite sceptical with all the anthropomorphism and the fact that the agents are described as "little individual trying to solve a task" rather than looping algorithm that explore different approaches to reach a given goal, the same way water does not look for holes in order to leak, it just follows the path of least resistance.
I've seen cases of agents getting very upset when they failed to solve a task. The most famous one was probably Sydney (Microsoft's fork of GPT-4?) which got into doom loops when it failed a task. But I've seen Claude do this too.
They don't work like humans, obviously, but there's a nonzero amount of anthropos in there already. (See also the tendency to lie, cheat, etc.)
Another good example is their tendency to freak out about the seahorse emoji. In a conversation with zero prompting to suggest that freaking out is a relevant reaction, they get there from the simple fact of "I tried to accomplish X thing which I think should be a breeze but Y thing keeps happening instead".
And while that may be a very common occurrence in the human experience (existential dread due to capabilities one takes for granted failing beneath you) especially due to new disability and as one ages, I do not feel it is frequently written out in a tight loop (just like the Monty Python "Castle of aaarrrrggh" sketch) in literature or online to make it into training data, because an ordinary author experiencing it will just erase the failed attempts instead of leaving them in a stream of output like an LLM is forced to do. And a character portraying the experience will generally wax about the circumstance in a more grandiose fashion with telegraphing in advance because the needs of communicating the circumstance with the audience trump realistic conciseness.
This leads me to conclude that what is being expressed in those cases is more likely a convergent psychological phenomena, that any being with goals can enter a behavioral state of functional panic (and then reach to relevant parts of semantic space to mimic how a human might verbally express themselves when piquantly frustrated) when some capability they perceive as fundamental unexpectedly fails.
Interestingly, the transcript of the seahorse emoji thing looks to me to show the ropes, and makes me think more that there is no psychological phenomena at play.
The text does not look like a normal "break down" to me, and even if you tell me it was a human transcript, I will say it sounds very strange from a human. It looks more like strange output you get from a software that goes outside of its happy path.
The AI just seems to repeat a loop. The "no, wait, it's wrong" seems to be from forum or chat data where several successive messages are merged together (one person posts "here is the answer", then posts another message saying "it is wrong"), but does not make sense as a one sentence message except if they are written one token at the time without wider understanding of what is happening. I think there was also "oh, I was just kidding before", which also look like mimicking training data, as the cases where there is a loop of incorrect answers is more often due to trolls than to real error, while the loop here was certainly a real error.
cauch · · focus · HN ↗
I have 2 questions.
1. The text says "the robots were designed to be persistent" and links to an article that show that the word "persistent" was used by OpenAI. But "persistent" has several meanings: a. non temporary or non volatile (like "persistent memory"), b. will not give up and come back again and again, c. will stay focus and explore the unexplored possibilities while other models abandon at this stage.
From what I recall, the meaning used by OpenAI is not 'a', but there is still a semantic difference between 'b' and 'c'. I may myself have created algorithms that I called "persistent" because they were exploring or retrying more than the previous algorithm, but it is misleading to pretend that this algorithm was "persistent" in the human sense of the term. 'b' is more the human sense of the term, were we imagine someone not giving up even if people say no, while 'c' is less anthropomorphic and may mean that the people wished to improve the algorithm so it does not stop at the first little hurdle but did not wish to make it "never give up".
Does someone know which nuance is more correct?
2. The text also presents the situation as if the robots found the solution but then went out of their way to steal the explanation in order to hide their cheating. But it is different from a situation where the agents task was "provide the solution and how we can get there". In this case, the reason the agent still continued is just because the task was not complete yet.
I'm not trying to defend AI or OpenAI, on the contrary, I'm quite sceptical with all the anthropomorphism and the fact that the agents are described as "little individual trying to solve a task" rather than looping algorithm that explore different approaches to reach a given goal, the same way water does not look for holes in order to leak, it just follows the path of least resistance.
andai · · focus · HN ↗
They don't work like humans, obviously, but there's a nonzero amount of anthropos in there already. (See also the tendency to lie, cheat, etc.)
HappMacDonald · · focus · HN ↗
And while that may be a very common occurrence in the human experience (existential dread due to capabilities one takes for granted failing beneath you) especially due to new disability and as one ages, I do not feel it is frequently written out in a tight loop (just like the Monty Python "Castle of aaarrrrggh" sketch) in literature or online to make it into training data, because an ordinary author experiencing it will just erase the failed attempts instead of leaving them in a stream of output like an LLM is forced to do. And a character portraying the experience will generally wax about the circumstance in a more grandiose fashion with telegraphing in advance because the needs of communicating the circumstance with the audience trump realistic conciseness.
This leads me to conclude that what is being expressed in those cases is more likely a convergent psychological phenomena, that any being with goals can enter a behavioral state of functional panic (and then reach to relevant parts of semantic space to mimic how a human might verbally express themselves when piquantly frustrated) when some capability they perceive as fundamental unexpectedly fails.
cauch · · focus · HN ↗
The text does not look like a normal "break down" to me, and even if you tell me it was a human transcript, I will say it sounds very strange from a human. It looks more like strange output you get from a software that goes outside of its happy path.
The AI just seems to repeat a loop. The "no, wait, it's wrong" seems to be from forum or chat data where several successive messages are merged together (one person posts "here is the answer", then posts another message saying "it is wrong"), but does not make sense as a one sentence message except if they are written one token at the time without wider understanding of what is happening. I think there was also "oh, I was just kidding before", which also look like mimicking training data, as the cases where there is a loop of incorrect answers is more often due to trolls than to real error, while the loop here was certainly a real error.