4 ms·

Really striking what a large percentage of the words are jargon. Sometimes I understand less than 10% of the words in a sentence. I think I might now better und

• nsns 14y ago
  That's true for almost every field of academic research and work; around 70-80% of the words are not in any dictionary (or, if they are, their standard definition has nothing to do with their professional meaning).
  • tikhonj 14y ago
    What always interested me is how the ratio of new words to repurposed words varies per field. For example, in CS we use a whole bunch of words like "string", "thread", "class", "type", "object", "arrow", "map" and "macro" to denote CS-specific concepts related at best tangentially to the words' original meanings. On the other hand, biology seems to prefer to come up with new words for their technical terminology. I wonder if this is a product of different cultures or something like that.
    • repsilat 14y ago
      The worst is botany. Botanists use common culinary words to describe almost entirely non-overlapping sets of plants/fruit etc. The "Tomato a fruit?" question is nothing compared to the "berry" thing. According to the botanical definition cherries, raspberries, strawberries, boysenberries and blackberries are not berries, but bananas, watermelon, avocado and pumpkin are. Nuts are worse. According botanists, peanuts, cashews, macadamias, pistachios, walnuts, almonds, pecans, pine-nuts and Brazil nuts are not nuts. According to most lay-people, though, botanists are nuts.
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• tdicola 14y ago
  I don't understand the particle physics they're talking about, but I do find it fascinating how a lot of the work is really how to sort through a massive amount of data to remove all the noise and find the signal. It sounds like they're using some machine learning algorithms to examine and classify various interactions in the data.
  • jessriedel 14y ago
    > It sounds like they're using some machine learning algorithms to examine and classify various interactions in the data. They are.
    • waterlesscloud 14y ago
      I wonder if the people doing it are trained in computer science or physics? Not that it should matter in the end results, just curious how people got there.
      • kaybe 14y ago
        They're probably physicists. One can take IT classes during the study, and some people have a very high skill level. Data interpretation is a big part of being an experimental physicist, and these algorithms are very useful, so people will seek them out. Computer science people work in other areas, such as setting up and running the data collection and on-line processing. (A professor told us many interesting stories about the many Unix servers they build and the bugs they created..)
      • cshimmin 14y ago
        few of us are formally trained in CS. some of us are good. others are not. my understanding is that the computer engineers at CERN are mostly tasked with IT work, the rest (including DAQ software/firmware, network code, distributed+realtime data processing, etc) is made by the physicists.
      • ballooney 14y ago
        A lot of the modern research in 'big data' analysis is/was driven by physicists. Bayesian Inference is about trying to make a decision about what you can infer from an observation or series of observations, and the impetus for this came from trying to make sense of experimental results. Two of the really great text books in the field are by physicists, 1) 'Information Theory, Inference and Learning Algorithms' by David Mackay, a physics professor at Cambridge. Perhaps the most readable and enjoyable text book I own. Certainly up there. 2) 'Pattern Recognition and Machine Learning' by Chris Bishop, now a director at Microsoft Research in Cambridge but formerly a physicist. Delightfully, under the circumstances, his PhD supervisor was Higgs (yes, the one of boson fame)!