[JSavageOne]

I wonder why OpenAI doesn't try to get more feedback and training data from its users, though I do notice that sometimes it'll give me two answers and ask me to pick the better one.

For example I've noticed that a lot of the time when I ask ChatGPT a coding question it might get 90% of the answer. When I tell it what to fix and/or add, it usually gets the answer. I wonder if they're using these refined answers to fine-tune those original prompts.

I wonder how the LLM interacts with other software like the calculator or Python interpreter. It would be great if this were modular so that the LLM OS could be more like Unix than Windows which is what OpenAI seems to be trying to emulate.

Ultimately though it seems to me like AGI is fairly straightforward from here. Just train on more quality data - in particular enabling the machine to generate this training data, increase parameter size, and the LLM just gets better and better. Seems like we don't even need any new major breakthroughs to create something resembling AGI.

[leobg]

They should be capturing the changes that people make to the ChatGPT outputs. Many people will be copying the outputs to some other application and then make changes. If open AI would make it easier to modify the outputs right within ChatGPT, they could use that as feedback. Basically, fuse the end-user UI with the UI of the annotates.

[throwuxiytayq]

I have zero faith that the average ChatGPT user will make quality edits. If anything, this invites trolling and active dataset poisoning/manipulation the moment people figure out that's what they're doing.

[rany_]

I think they learned from Tay.AI and friends.