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.
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.