Just a moment...
Sometimes, gave the same task to multiple models, comparing and merging their outputs to maximize quality. It's like double bookkeeping: when you know something is prone to errors (or, in Al's case, hallucinations), it's best to give the same task to two or three different models. This significantly reduces the error rate.
The approach mirrors
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So the pertinent question is not really whether current AI systems are like you and me (they are not) but what the limits of their abilities might be. AI sceptics have argued vehemently that LLMs are forever limited by the basic design choices of AI developers, and especially that they are trained to predict (or 'guess') the next token in a
... See moreChristopher Summerfield • These Strange New Minds
When commentators deride LLMs for 'just making predictions', they have overlooked the fact that predicting immediate sensory information is literally how learning happens in all biological systems, from the humblest worms and flies to the billion-neuron brains of humans and our nearest primate cousins. Learning and predicting go hand in hand.