And they expect you to do this for free?
Do they not have to pay for the privilege? Or is this not referring to academic publishing? (It’s not super clear, but context indicates academic?)
Agreed that you should have some kind of “service” on your CV, but reviewing is pretty low impact. And if you want to review, you can choose something other than the predatory publishers.
Jfc that’s gross
Honestly sometimes I feel like I’m the only one on Lemmy who likes AI
AI absolutely has its benefits, but it’s impossible to deny the ethical dilemma in forcing writers to feed their work to a machine that will end up churning out a half assed version that also likely has some misinformation in it.
I don’t think so, at least for a little bit. Big cooperation will surely try to market it that way, but we’ve already seen how badly AI can shit the bed when it feeds on its own content
The company I work for recently rolled up copilot and is have been a mixed bag of reactions, the less savvy user were first blowed up by the demonstration but then got exasperated when it didn’t worked as they tough (one of them uploaded an excel file and asked to some analysis it couldn’t do, and came to me to complain about it), but for me, and my team had worked great. I’ve been uploading some of my python and SQL scripts and asking for refactoring and adding comments, or uploading my SQL script and some example I found on stackoverflow and asking for it to apply the example method on my script.
I say to everyone that if they don’t know shit, the AI isn’t not going to help a lot, but if you have at least the basic, the AI would help you.
Soylent Green is a lie anyway. Your need to “soylentify” half the population to feed the other half every year if it would be the only source of calories.
How many of these books will just be totally garbage nonsense just so they could fulfill a prearranged quota.
Now the LLM are filled with a good amount of nonsense.
Just use the llm to make the books that the llm then uses, what could go wrong?
Someone’s probably already coined the term, but I’m going to call it LLM inbreeding.
In computer science, garbage in, garbage out (GIGO) is the concept that flawed, biased or poor quality (“garbage”) information or input produces a result or output of similar (“garbage”) quality. The adage points to the need to improve data quality in, for example, programming.
There was some research article applying this 70s computer science concept to LLMs. It was published in Nature and hit major news outlets. Basically they further trained GPT on its output for a couple generations, until the model degraded terribly. Sounded obvious to me, but seeing it happen on the www is painful nonetheless…
