I’ve been controlling rsi with upper body mobility and strength training + typing breaks for years. This mind over matter approach sounds like bullshit.
That's pretty dismissive for what seemed to be a thoughtful article. Do you think the person who wrote it somehow imagined the decrease in pain? Just because you sorted your out in that way doesn't mean other people can't manage it in different ways - as the doctor said, they don't really know what it is, so it could have a whole cluster of different causes that respond to different kinds of treatment.
Here's a python script to find the rss url on a science journal's website. It leverages smolagents and meta-llama/Llama-3.3-70B-Instruct. The journal’s html is pulled with a custom smolagent tool powered by playwright. Html parsing is handled by a CodeAgent given access to bs4.
I've tested with nature, mdpi, and sciencedirect so far.
I built it b/c I tired of manually scanning each journal's html for rss feeds, and I wanted to experiment with agents. It took a while to get the prompt right.
A thing to do with your environment setup, so a tool I suppose? There are probably different plugins out there for it. In my case it's a few lines in .bashrc that override the history processing to never delete old history, and add tags indicating which session wrote the command. This way I can reboot a computer, restart all 30 screen sessions, and have each access backward searchable history to the start of time (2013 for me).
I'm guessing newer shells may have better support for this kind of thing instead of running shell commands to wrangle text files on every prompt.
What does not work? Is there an error or just no playlist in Spotify?
Please be aware that tastemaker gets a lot better after one day, as than your full taste is loaded. At the moment of registration only a few info is loaded from your profile as otherwise the setup would take >10 minutes.
Yes. I've seen several examples of decision support since 2010. It's not easy to train models because the codes for procedures can be ambiguous. Furthermore, since hospital classifiers favor medical error recall over precision, docs can be swamped with so many warning messages that they tend to ignore them.
Take adverse drug interactions as an example. The training data for drug interactions mostly come from adults, so the resulting models do not apply in a pediatric setting. When the models are let loose in pediatric hospital, a high percentage of the drug interaction warnings are false positives, so these type of warnings tend to be ignored.
It seems that the trend is to use decision support with a lot of human oversight and investigation of the raw data to see if the model conclusions are correct.
What you describe to me seems to be a simple UI problem. I'd add a button "False Positive, Don't show this warning again" and flag the "drug interaction" for review. If I get enough of these, I'd change the behavior for all users in the next update.
