Hacker News new | ask | show | jobs
by Xelynega 1286 days ago
One of the parts of building these generative models is building a classifier for how "good" their output is, otherwise the algorithm has no way to compare potential outputs in a generation.

That's one of the issues with these models, we say they produce "good" output but really they're producing output that is "good" from one specific point of view that happens to be expressed in code and introduces a large bias into their outputs.
1 comments
astrange 1286 days ago
“Good” isn’t expressed in code here. GPT3 was trained on a very loose problem (next word prediction). InstructGPT/ChatGPT are trained on reinforcement learning from human raters.

If it was all a computer program it’d be acting like ELIZA.

link
Xelynega 1285 days ago
"good" for gpt was expressed in the way they chose the dataset to include.

Just because generative text models in the past(like ELIZA) were bad doesn't mean that the algorithms we have now are much more than better versions of the same.

link