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npub1lrp4...958g
Another thought on the generative AI debate. As more and more AI slop papers come out, it becomes *more* important to actually read the papers and *more* important to gain domain expertise to spot fakes. An AI generated summary of an AI generated paper isn't going to tell you the paper is fake. #AI #AcademicChatter
There is some discourse right now on how not everything is digitized and cannot be replaced with generative AI summaries. Another point is that sometimes the data is scattered around, and you need to put it together in a standardized way. This requires expertise. I am doing this with sea level data. Be sure to check out WALIS, the project led by Alessio Rovere. Alessio has done a great deal to put together a standardized database of sea level data, compiled by experts (I contributed a couple of studies). Generative AI is not going to be able to do things like this. Generative AI is a conservative machine. It can only give you accounts of previous experts, and only then from things that are digitized. Generative AI is not particularly useful for someone who wants to gain domain expertise. You have to draw your own conclusions from what has been done previously. #AI #AcademicChatter
Nothing brings up my frustration with modern search than what I went through today. I want a translation of "analogue" (as in "analogue for future climate") in Japanese. Doing a search with both "analogue" and "ๆœชๆฅใฎๆฐ—ๅ€™" fails and machine translation brings up incorrect words. I even had a (non-expert) Japanese person helping me. After 40 minutes, we found "้กžๆŽจ" - analogy. I still am not sure if that is correct. #AcademicChatter