LifeIsBio
Joined 9 years ago
Joined 9 years ago
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).
> I have an image of a hand drawn workflow diagram. I’d like to turn it into a mermaid.js file.
(with the image attached)
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.
https://chatgpt.com/share/66ff28e2-ea74-800b-a230-86d562f60f...
It's tricky. On the one hand, it's obviously not appropriate to be flippant about patient privacy. On the other, it's clearly that advancements in human health are being hindered by our current approach to (dis)allowing researchers access to data.
You gave the example of unstructured PDF, but there are challenges with structured docs as well. We’ve run into docs that are hard to chunk because of this deeply nested and repeated structure. For example, there might be a long experimental protocol with multiple steps; at the end of each step, there’s a table “Debugging” for troubleshooting anything that might have gone wrong in that step. The debugging table is a natural chunk, except that once chunked there are a dozen such tables that are semantically similar when decoupled from their original context and position in the tree structure of the document.
This is one example, but there are many other cases where key context for a chunk is nearby in a structured sense, but far away in the flattened document, and therefore completely lost when chunking.
"SFARI’s mission is to improve the understanding, diagnosis and treatment of autism spectrum disorders by funding innovative research of the highest quality and relevance."
SFARI in turn funds a lot of foundational neurological and rare disease research, since autism is such a common phenotype.