Interesting. There was a study put out some time ago that had 40 or so game theorists develop algorithms to compete against each other. The most successful algorithm cooperated with the opponent until they defected, at which point they would defect the next round.
They never performed a first strike. Only one retaliation strike for each attack their opponent performed. After the retaliation, it was back to cooperating with no long term ill will.
I think I saw something about it that. It was an extended prisoner’s dilemma game, right? I wouldn’t say that’s directly applicable to every gaming genre.
Without being in the room, we can only go off what the article lays out. These are wargaming scenarios though, so escalation is a very real concern. If both sides are running these models to provide recommendations and both are pushing for greater conflict, you find yourself in a prisoner’s dilemma real quick.
These aren’t simulations that are estimating results, they’re language models that are extrapolating off a ton of human knowledge embedded as artifacts into text. It’s not necessarily going to pick the best long term solution.
I want to be careful about how the word reasoning is used because when it comes to AI there’s a lot of nuance. LLMs can recall text that has reasoning in it as an artifact of human knowledge stored into that text. It’s a subtle but important distinction that’s important for how we deploy LLMs.
The writers of the article are reporting on use of these models by the military. They aren’t using the models. If I remember right they called out some models developed by one of the defense contractors like palantir
You’re right. I was focused on this part above. I made like an AI and jumped the gun
These results come at a time when the US military has been testing such chatbots based on a type of AI called a large language model (LLM) to assist with military planning during simulated conflicts, enlisting the expertise of companies such as Palantir and Scale AI. Palantir declined to comment and Scale AI did not respond to requests for comment.
I’m not sure where our disconnect is. We have a situation where both sides can cooperate, one side can defect, or both sides can defect. Call it whatever you want, it’s the same scenario.
Here it’s with planning for military force. Do you risk a nuclear strike to save yourself from one? If you can get a first strike (defect), then you win. If you both refrain (cooperate), then you stay alive. If you both attempt a first strike (defect), you all lose.
Change the words around and it’s the same.
Both suspects don’t tell (cooperate), both get minimum or no jail time. One tells on the other (defects), that one gets off but the other gets maximum. Both tell on each other (defect), both get some jail time.
Interesting. There was a study put out some time ago that had 40 or so game theorists develop algorithms to compete against each other. The most successful algorithm cooperated with the opponent until they defected, at which point they would defect the next round.
They never performed a first strike. Only one retaliation strike for each attack their opponent performed. After the retaliation, it was back to cooperating with no long term ill will.
I think I saw something about it that. It was an extended prisoner’s dilemma game, right? I wouldn’t say that’s directly applicable to every gaming genre.
Without being in the room, we can only go off what the article lays out. These are wargaming scenarios though, so escalation is a very real concern. If both sides are running these models to provide recommendations and both are pushing for greater conflict, you find yourself in a prisoner’s dilemma real quick.
These aren’t simulations that are estimating results, they’re language models that are extrapolating off a ton of human knowledge embedded as artifacts into text. It’s not necessarily going to pick the best long term solution.
Language models can extrapolate but they can also reason (by extrapolating human reasoning).
I want to be careful about how the word reasoning is used because when it comes to AI there’s a lot of nuance. LLMs can recall text that has reasoning in it as an artifact of human knowledge stored into that text. It’s a subtle but important distinction that’s important for how we deploy LLMs.
The models used by the writers of the article and those used by the military are going to be radically different.
The writers of the article are reporting on use of these models by the military. They aren’t using the models. If I remember right they called out some models developed by one of the defense contractors like palantir
Also, they’re reporting on a Stanford study of how these platforms could be used militaristically, not the military’s actual use of them.
You’re right. I was focused on this part above. I made like an AI and jumped the gun
The way you said that tells me you don’t know what a prisoner’s dilemma is. It’s not “a situation where both sides have escalated”.
I’m not sure where our disconnect is. We have a situation where both sides can cooperate, one side can defect, or both sides can defect. Call it whatever you want, it’s the same scenario.
Here it’s with planning for military force. Do you risk a nuclear strike to save yourself from one? If you can get a first strike (defect), then you win. If you both refrain (cooperate), then you stay alive. If you both attempt a first strike (defect), you all lose.
Change the words around and it’s the same.
Both suspects don’t tell (cooperate), both get minimum or no jail time. One tells on the other (defects), that one gets off but the other gets maximum. Both tell on each other (defect), both get some jail time.