Readit Newshttps://news.ycombinator.com/item?id=33755016
You can also unironically spot most types of AI writing this way. The approaches based on training another transformer to spot "AI generated" content are wrong.
The first question is what scientific research is actually for. Is it merely for profitable technological applications? The Greek or the humanistic or the enlightenment ideal wasn't just that. Fundamental research can be its own endeavor, simply to understand more clearly something. We don't only do astronomy for example in order to build some better contraption and understanding evolution wasn't only about producing better medicine. But it's much harder to quantify elegance or aesthetics of an idea and its impact.
And if you say that this should only be a small segment, and most of it should be tech-optimization, I can accept that, but currently science runs also on this kind of aesthetic idealist prestige. In the overall epistemic economy of society, science fills a certain role. It's distinct from "mere" engineering. The Ph in PhD stands for philosophy.
Not sure that enough people understand that the vast vast majority of research papers are written in order to fulfil criteria to graduate with a PhD. It's all PhD students getting through their program. That's the bulk of the literature.
There was a time when nobody went to school. Then everyone did 4 years elementary to learn reading, writing and basic arithmetic. Then everyone did 8 years, which included more general knowledge. Then it became the default to do 12 years to get to the high school diploma. Then it became default to do a bachelor's to get even simple office jobs. Then it's a masters. Then to actually stand out now in a way that a BSc or MSc made you stand out, you need a PhD. PhD programmes are ballooning. Just as the undergrad model had to change quite a bit when it went from 30 highly-motivated nerds starting CS in a year vs. 1000. These are massive systems, the tens or hundreds of thousands of PhD students must somehow be pushed through this system like clockwork. Just for one conference you get tens of thousands of authors submitting similar amount of papers and tens of thousands of reviewers.
You can't simply halt such a huge machine with a few little clever ideas.
I spent three months perfecting the speaker diarization pipeline and I think you'll be quite pleased with the results.
In many ways, turning tech into products that are useful, good, and don't make life hell is a more interesting issue of our times than the core research itself. We probably want to avoid the valuing capturing platform problem, as otherwise we'll end up seeing governments using ham fisted tools to punish winners in ways that aren't helpful either