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I want to believe that however obsolete these old algorithms are today, at least some aspects of the underlying code and/or logic should prove useful to LLMs as
by kmoser 1y ago
I want to believe that however obsolete these old algorithms are today, at least some aspects of the underlying code and/or logic should prove useful to LLMs as they try to generate modern code.
- klodolph 1y agoMaybe… some of these algorithms from the 1980s struggled to do basic OCR, so they may need a lot of modification to be useful.
- PaulHoule 1y agoThat whole approach of "find edges, convert to line drawing, process a line drawing" in the 1980s struggled to do anything at all.
- Retric 1y agoThere was a surprising amount of useful OCR happening in the 70’s. High error rates and significant manual rescanning can be acceptable in some applications, as long as there’s no better alternative.
- GuB-42 1y agoI find that modern OCR, audio transcription, etc... are beginning to have the opposite problem: they are too smart. It means that they make a lot fewer mistakes, but when they do, it can be subtle. For example, if the text is "the bat escaped by the window", a dumb OCR can write "dat" instead of "bat". When you read the resulting text, you notice it and using outside clues, recover the original word. An smart OCR will notice that "dat" isn't a word and can change it for "cat", and indeed "the cat escaped by the window" is a perfectly good sentence, unfortunately, it is wrong and confusing.
- devilbunny 1y agoThankfully, most speech misrecognition events are still obvious. I have seen this in OCR and, as you say, it is bad. There are enough mistakes in the sources; let us not compound them.
- taeric 1y agoI'm not sure I can sign on to this. In particular, this sounds kind of like an indictment of many algorithms. But, how many where there? And did any go on to give good results? Considers, OCR was a very new field, such that a lot of the struggle was getting data into a place you could even try recognition against it. It should be no surprise that they were not able to succeed that often. It would be more surprising if they had a lot of different algorithms.
- monkeyelite 1y agoThe idea that ML is the only way to do computer vision is a myth. Yes, it may not make sense to use classical algorithms to try to recognize a cat in a photo. But there are often virtual or synthetic images which are produced by other means or sensors for which classical algorithms are applicable and efficient.
- thatcat 1y agoAny recommendations on background reading for classical CV for radar?
- monkeyelite 1y agoI don’t know anything about radar. I have a book called “machine vision” (Shmuck, Jain, Kasturi) easy undergrad level, but also very useful. It’s $6 on Amazon.
- ipunchghosts 1y agoKasturi was my undergraduate honors advisor!
- monkeyelite 1y agoSmall world! These are always just names on a book to me.
- thatcat 1y agoAwesome, thanks!
- sceadu 1y agoDon't know about radar but here's a good book on classical CV https://udlbook.github.io/cvbook/ https://udlbook.github.io/cvbook/ even though I think Simon admits that most of it is obsolete after DL computer vision came about
- 1y ago