Current machine learning models have around ~100B parameter, human brain has ~100T synapses. Assuming one DNN parameter is equivalent to 1 synapse, then the biggest models are still 1000 times smaller than human brain.
Cat or dog would have around ~10T synapses.
AlphaCode has ~50B parameters, that is 20 times less than number of synapses in a mouse brain ~1T. Honey bee has ~1B synapses.
So AlphaCode would be somewhere between a honey bee and a domestic mouse.
Current machine learning models have around ~100B parameter, human brain has ~100T synapses. Assuming one DNN parameter is equivalent to 1 synapse, then the biggest models are still 1000 times smaller than human brain.
Cat or dog would have around ~10T synapses.
AlphaCode has ~50B parameters, that is 20 times less than number of synapses in a mouse brain ~1T. Honey bee has ~1B synapses.
So AlphaCode would be somewhere between a honey bee and a domestic mouse.
https://en.wikipedia.org/wiki/List_of_animals_by_number_of_n...