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[DISCUSS] IBM using LLMs to convert COBOL to Java
(techcrunch.com)
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this post was submitted on 23 Aug 2023
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One would hope that IBM's selling a product that has a higher success rate than a coinflip, but the real question is long-term project cost. Given the example of a $700 million dollar project, how much does AI need to convert successfully before it pays for itself? If we end up with 20% of the original project successfully done by AI, that's massive savings.
The software's only going to get better, and in spite of how lucrative a COBOL career is, we don't exactly see a sharp increase in COBOL devs coming out of schools. We either start coming up with viable ways to move on from this language or we admit it's too essential to ever be forgotten and mandate every CompSci student learn it before graduating.
Again, my point really doesn't have anything to do with specific percentages. The point is that if some percentage of it is broken you aren't going to know exactly which parts. Sure, some problems might be obvious but some might be very rare edge cases.
If 99% of my program works, the remaining 1% might be enough to not only make the program useless but actively harmful.
Evaluating which parts are broken is also not easy. I mean, if there was already someone who understood the whole system intimately and was an expert then you wouldn't really need to rely on AI to port it.
Anyway, I'm not saying it's impossible, or necessary not going to be worth it. Just that it is not an easy thing to make successful as an overall benefit. Also, issues like "some 1 in 100,000 edge case didn't get handle successfully" are very hard to quantify since you don't really know about those problems in advance, they aren't apparent, the effects can be subtle and occur much later.
Kind of like burning petroleum. Free energy, sounds great! Just as long as you don't count all side effects of extracting, refining and burning it.
A random outcome isn't flipping a coin, it's rolling dice