I saw several papers about LLM safety (for example Alignment faking in large language models) that show some “hidden” self preserving behaviour in LLMs. But as I know, no-one understands whether this behaviour is just trained and does mean nothing or it emerged from the model complexity.
Also, I do not use the ChatGPT app, but doesn’t it have a live chat feature where it continuously listens to user and reacts to it? It can even take pictures. So the continuity isn’t a huge problem.
And LLMs are able to interact with tools, so creating a tool that moves a robot hand shouldn’t be that complicated.
I responded to your other comment, but yes, I think you could set up an llm agent with a camera and microphone and then continuously provide sensory input for it to respond to. (In the same way I’m continuously receiving input from my “camera” and “microphones” as long as I’m awake)
I saw several papers about LLM safety (for example Alignment faking in large language models) that show some “hidden” self preserving behaviour in LLMs. But as I know, no-one understands whether this behaviour is just trained and does mean nothing or it emerged from the model complexity.
Also, I do not use the ChatGPT app, but doesn’t it have a live chat feature where it continuously listens to user and reacts to it? It can even take pictures. So the continuity isn’t a huge problem. And LLMs are able to interact with tools, so creating a tool that moves a robot hand shouldn’t be that complicated.
I responded to your other comment, but yes, I think you could set up an llm agent with a camera and microphone and then continuously provide sensory input for it to respond to. (In the same way I’m continuously receiving input from my “camera” and “microphones” as long as I’m awake)