Re:Google DeepMind CEO Says Some Form of AGI Possible in a F...
by depr on Thursday May 04, 2023 @04:38AM
(#35812740)
Not as much as it took GPT to process all its input.
>Let us consider the GPT-3 model with 𝑃 =175 billion parameters as an example. This model was trained on 𝑇 = 300 billion tokens. On 𝑛 = 1024 A100 GPUs using batch-size 1536, we achieve 𝑋 = 140 teraFLOP/s per GPU. As a result, the time required to train this model is 34 days.
I'm not sure expressing brain capacity in FLOPs makes much sense, but I'm sure if it can be expressed in FLOPs, the amount of FLOPs going to learning for a normal human is less than that.
>Let us consider the GPT-3 model with 𝑃 =175 billion parameters as an example. This model was trained on 𝑇 = 300 billion tokens. On 𝑛 = 1024 A100 GPUs using batch-size 1536, we achieve 𝑋 = 140 teraFLOP/s per GPU. As a result, the time required to train this model is 34 days.
https://arxiv.org/pdf/2104.04473.pdf
I'm not sure expressing brain capacity in FLOPs makes much sense, but I'm sure if it can be expressed in FLOPs, the amount of FLOPs going to learning for a normal human is less than that.