Fascinating. I don't think you meant it this way, but it took me almost until the end to realize I had transposed the roles of human and ai. It made for a very interesting first read and second read.
This is a tough one in my opinion because the content of the article is valuable. Yes while reading it i noticed several AI tells. Almost like hearing a record scratch every other paragraph. But I was interested in the content so I kept reading mostly trying to ignore the "noise".
The problem I fear is that with enough AI generated content around, I will become desensitized to that record scratching.
Eventually between over-exposure, those who can't recognize the tells, people copying the writing they see..., we might have to accept what might become a prevalent new style of writing.
> But at the end of the day, the last 10% always takes up 90% of the time and, as always, the difference between good enough and great is the amount of love you put into the work.
I don't find open spaces noisier than cubicles but I am able to easily block out distracting sounds.
I am interrupted, and when I am is generally somebody giving me a useful quick update or an informal greeting from an office buddy when they notice I make welcoming eye contact.
I don't think I ever felt a lack of privacy in the office or expected it in any way? I wonder what kind of privacy I would need that the restroom doesn't cover, I'm sure there are some instances since it's been called out.
Is there are Dreambooth equivalent for fine-tuning ChatGPT as there is for Stable Diffusion? I have to imagine that if we can add custom data to a DL text-to-image model, we should be able to do the same with a text-to-text one.
Edit to add: There are a number of Google Colabs for fine-tuning SD and I wonder if there are (or if it is technically feasible) to accomplish the same with other txt2txt models.