The first type of AI is a regular narrow AI, the type we’ve been building for a while. The second type is an agentic AI, a strong AI, which we have yet to build. The problem is, AIs are trained using gradient descent, which basically involves running AI designs from all possible AI designs. Gradient descent will train the AI that can maximize the reward best. As a result of this, agentic AIs become more likely because they are better at complex tasks. While we can modify the reward scheme, as tasks get more and more complex, agentic AIs are pretty much the way to go, so we can’t avoid building an agentic AI, and have no real idea if we’ve even created one until it displays behaviour that indicates it.
+1 for the word agentic AI. I think that is what I was looking for.
However, I don’t believe that gradient descent alone can turn an AI agentic. No matter how long you train a language model, it is not going to suddenly want to acquire resources to get better at predicting human language (unless you specifically ask it questions about how to do that, and then implement the suggestions. Even then you are likely to only do what humans would have suggested, although maybe you can make it do research similar to and faster than humans would have done it).
The first type of AI is a regular narrow AI, the type we’ve been building for a while. The second type is an agentic AI, a strong AI, which we have yet to build. The problem is, AIs are trained using gradient descent, which basically involves running AI designs from all possible AI designs. Gradient descent will train the AI that can maximize the reward best. As a result of this, agentic AIs become more likely because they are better at complex tasks. While we can modify the reward scheme, as tasks get more and more complex, agentic AIs are pretty much the way to go, so we can’t avoid building an agentic AI, and have no real idea if we’ve even created one until it displays behaviour that indicates it.
+1 for the word agentic AI. I think that is what I was looking for.
However, I don’t believe that gradient descent alone can turn an AI agentic. No matter how long you train a language model, it is not going to suddenly want to acquire resources to get better at predicting human language (unless you specifically ask it questions about how to do that, and then implement the suggestions. Even then you are likely to only do what humans would have suggested, although maybe you can make it do research similar to and faster than humans would have done it).