This is a good point, but it seems, empirically, that most parts of a standard passenger airplane have reliability approximating 100% in a predefined time window with proper inspection and maintenance, otherwise passenger transit would be impossible. When the system does start to degrade, e.g. because replacement parts and maintenance becomes unavailable or too costly (cf. the use of imported planes by Russian airlines after the sanctions hit), incidents quickly start piling up.
It's about what you do with errors. If you let them compound they lead to destruction, if instead you inspect, maintain, reinspect, replace, etc. you can manage them.
My point was that something extremely complex, like a plane, works, because the system tries hard to prevent compounding errors.
That works because each plane is (nearly) exactly the same as the one before it and we have exact specifications for the plane.
You can do maintenance, inspections, and replacement because of those specifications.
In software the equivalent of blueprints is code. The room for variation outside software “specifications” is infinite.
Human reliability when comes to assembling planes is also much higher than 99%, and LLM reliability creating code is much, much lower than 99%.
If you think human reliability when writing code is more than 99%, have I got news for you!
If you’re going by bugs per lines of code, I’m far higher than 99% reliable.
Valid point, however the promise of AI is that it will be able to manufacture a metaphorical “plane” for each and every prompt user inputs I.e. give 100% overall reliability by using all kinds of techniques (testing, decomposing etc) that intelligence can come up with.
So until these techniques are baked into the model by OpenAI, you have to come up with these ideas yourself.
Also, if you look at any human process you will realize that none of them have a 100% reliability rate. Yet, even without that we can manufacture e.g. a plane, something which takes millions of steps, each without a 100% success rate.
I actually think the article makes some good points, but especially when you are making good points it is unnecessary to stretch credibility with exaggerating your arguments.