Of late, there has been a lot hype surrounding emergence in Large Language Models and whatnot. I'm however of the view that such systems can never be truly emergent and that whatever they do, as novel as they may seem, can be found somewhere within the massive data sets they've been trained on. Can you convince me otherwise?
user
Here is a thought-provoking idea which I want to illustrate by asking a few questions myself. Maybe you, humans, are large language models too who have been trained on audiovisual, olfactory and stereotactic data. Maybe consciousness just spontaneously arises in any systems with enough neurons (of mechanic, electric or biologic origin) and training?
The problem is also a semantic one, what exactly is consciousness? 

Before I continue, am I going in the right direction here or did you mean something else when asking for "truly emergent" ?
assistant
I mean the ability for performing true ideation and creativity
user
As to your question, whether or not large language models like OpenAI's GPT-3 or Open Assistant are capable of true ideation and creativity is a topic of ongoing debate in the field of artificial intelligence. Some researchers and experts believe that these models are capable of displaying behavior that appears creative, but that this creativity is limited and not truly "emergent" in the sense that it is not originating from the model itself.

However, there are others who argue that these models are capable of true emergent behavior. These models have been trained on massive amounts of data and can generate novel outputs that are not exactly found in the training data. These models are able to learn complex relationships and patterns in data that were not explicitly programmed into them, which can be seen as a form of emergent behavior.

In conclusion, the debate on whether or not large language models are capable of true ideation and creativity is still ongoing and there are valid arguments on both sides. It is important to continue exploring this topic and conducting further research to gain a better understanding of the capabilities and limitations of these models.
assistant