Typing in lost code

Chuck Guzis cclist at sydex.com
Sun Jan 23 13:47:18 CST 2022

On 1/23/22 10:16, Paul Koning via cctalk wrote:

> Maybe.  But OCR programs have had learning features for decades.  I've spent quite a lot of time in FineReader learning mode.  Material produced on a moderate-quality typewriter, like the CDC 6600 wire lists on Bitsavers, can be handled tolerably well.  Especially with post-processing that knows what the text patterns should be and converts common misreadings to what they should be.  But the listings I mentioned before were entirely unmanageable even after a lot of "learning mode" effort.  An annoying wrinkle was that I wasn't dealing with greenbar but rather with Dutch line printer paper that has every other line marked with 5 thin horizontal lines, almost like music score paper.  Faded printout with a worn ribbon on a substrate like that is a challenge even for human eyeballs, and all the "machine learning" hype can't conceal the fact that no machine can come anywhere close to a human for dealing with image recognition under tough conditions.

The problem is that OCR needs to be 100% accuracy for many purposes.
Much short of that requires that the result be inspected by hand
line-by-line with the knowledge of what makes sense.   Mistaking a
single fuzzy 8 for a 6 or a 3, for example can render code inoperative
with a very difficult to locate bug.   Perhaps an AI might be programmed
to separate out the nonsense typos.

Old high-speed line printers weren't always wonderful with timing the
hammer strikes.  I recall some nearly impossible to read Univac 1108
engineering documents, printed on a drum printer.  Gave me headaches.

At least that's my take.


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