The general scaling laws are universal and also apply to biological brains, which naturally leads to a net-training compute timeline projection (there’s a new neurosci paper or two now applying scaling laws to animal intelligence that I’d discuss if/when I update that post)
Note I posted that a bit before GPT4, which used roughly human-brain lifetime compute for training and is proto-AGI (far more general in the sense of breadth of knowledge and mental skills than any one human, but still less capable than human experts at execution). We are probably now in the sufficient compute regime, given better software/algorithms.
The general scaling laws are universal and also apply to biological brains, which naturally leads to a net-training compute timeline projection (there’s a new neurosci paper or two now applying scaling laws to animal intelligence that I’d discuss if/when I update that post)
Note I posted that a bit before GPT4, which used roughly human-brain lifetime compute for training and is proto-AGI (far more general in the sense of breadth of knowledge and mental skills than any one human, but still less capable than human experts at execution). We are probably now in the sufficient compute regime, given better software/algorithms.