This line stuck out to me as well, but my follow up thought was different.
I’ve had friends who have been on cocktails like these, and one of them once said something like, “I’ve been depressed before, and this is not that. I’m not depressed. I don’t have the emotional capacity to be depressed. This is more like a total emotional blank slate.”
She was basically a robot for a few months. Incapable of really any emotions, including sadness, anxiety, frustration, etc. Suffice to say, she also didn’t have the emotional drive to push her towards positive things like deciding on how to spend her weekend free time.
Thankfully she’s changed her meds and is feeling overall better (if, admittedly, at the price of some emotional stability).
One of my favorite applications of multimodal LLMs thus far is the ability to:
1. Draw a DAG of whatever pipeline I’m working on with pen and paper.
2. Take a photo of the graph, mistakes and all.
3. Ask ChatGPT to translate the image into mermaid.js
Given how complicated the pipelines are that I’m working with and the sloppiness of the hand drawn image, it’s truly amazing how well this workflow works.
I used to run into this problem all the time in grad school. Once a month or so I'd load a data set, do some dumb Python operation on it that took significantly more memory than I predicted, and BAM! I'd have to restart my laptop.
I just kinda assumed that's how computers worked until I got a Mac a couple of months ago...
The link suggests that there might be some default parameters you could change to protect against this behavior. Does anyone have any suggestions on what settings to change?