My understanding is that TEPS were used to determine computing for these types operations, rather than FLOPS, as they were more useful specifically for that comparison. There metrics put them in the same order of magnitude; however, as stated before, these miss the point by quite a bit, since much of the 'computations' humans do are quite irrelevant (taste, smell, etc) to producing language or solving algorithmic problems, etc.
For example, the cerebellum is 50-80% of what people keep quoting here (Number of neurons in the brain) and is not activated much in language processing.
Wernicke's area spans just a few percent of the cortical neurons.
The amount of pre processing we do by providing text is actually quite enormous, so that already removes a remarkable amount of complexity from the model. So, despite the differences between biology and ANNs, it's not unreasonable what were seeing right now.
For example, the cerebellum is 50-80% of what people keep quoting here (Number of neurons in the brain) and is not activated much in language processing.
Wernicke's area spans just a few percent of the cortical neurons. The amount of pre processing we do by providing text is actually quite enormous, so that already removes a remarkable amount of complexity from the model. So, despite the differences between biology and ANNs, it's not unreasonable what were seeing right now.