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The way I put this to myself is that AI gives “correct correct answers and incorrect correct answers”. They almost always generate logically correct text, but
by biophysboy 5mo ago
The way I put this to myself is that AI gives “correct correct answers and incorrect correct answers”.
They almost always generate logically correct text, but sometimes that text has a set of incorrect implicit assumptions and decisions that may not be valid for the use case.
Generating a correct correct solution requires proper definition of the problem, which is arguably more challenging than creating the solution.
- uuyy 5mo agoIt’s simpler than that - it’s a guessing machine that has superior access to a whole load of information and capacity to process at a speed at which we humans cannot compete. Does it make it better than us? No because ultimately the thing itself doesn’t ‘know’ right from wrong.
- andai 5mo agoBetter according to what standard? The standard of most employment is already to produce mediocre, plausible outputs as cheaply and rapidly as possible. It's a match made in heaven!
- iugtmkbdfil834 5mo agoI used to think otherwise, but the older I get the more I think you are correct on this one.
- attila-lendvai 5mo agoin an inflationary monetary system you need to spin the hamster wheel faster than the money printer. all the way until it all falls apart...
- andai 5mo agoYeah, very often the issue is that some context is missing. It'll say something true, but which misses the bigger point, or leads to a suboptimal result. Or it interprets an ambiguous thing in one specific way, when the other meaning makes more sense. You have to keep your wits about you to catch these things. It's an incredible tool but it's also very derpy sometimes, full of biases, blind spots etc.
- dotancohen 5mo agoThe way I phrase this to others is: Language models produce linguistically valid sentences, not factually correct sentences.
- naasking 5mo ago> which is arguably more challenging than creating the solution. This hasn't been the case in my experience. Devising a correct solution without a definition of the problem is impossible because you wouldn't recognize a correct solution without a definition. Often you discover the problem definition by exploratory programming and trial and error on solutions, but LLMs are still good for process this too. Arguably better because they type faster so you can iterate faster!