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But can you ascertain that similar dynamics won't also come into play for software? Yes, software is easier to deploy and test at scale - there are barely any p
by arcturus17 4y ago
But can you ascertain that similar dynamics won't also come into play for software? Yes, software is easier to deploy and test at scale - there are barely any physical constraints compared to driving. But on the other hand it's also a more complex domain than driving.
Taking Advent of Code as an example, GPT seems to be making mince meat of some problems, but it struggles with others.
Is it not conceivable that in software there will be a "last 10%" where AI will trip up, either because the inputs (prompts/requirements) are hard to express or parse, or the output (code) is hard to generate?
- vidarh 4y ago"Similar dynamics" requires situations where training the AI becomes bottlenecked on training opportunities. There will certainly be areas where such bottlenecks exist, and so we can assume that there will be types of problems we can't expect exponential improvement to continue once it hits those bottlenecks. But the point is that self-driving is a poor example to use to judge what we can expect to see in fields that are less constrained by turnaround times and safety. Not least because "anyone" - though certainly constrained by costs - can try to do novel things with large language models. Very few can try to do novel things with self-driving because they have nothing realistic to test it on at scale.