I think you’re just reading the essay wrong. In the “executive summary” section, they explicitly state that
Our best anchor for how much compute an AGI needs is the human brain, which we estimate to perform 1e20–1e21 FLOPS.
and
In addition, we estimate that today’s computer hardware is ~5 orders of magnitude less cost efficient and energy efficient than brains.
I don’t know how you read those claims and arrived at your interpretation, and indeed I don’t know how the evidence they provide could support the interpretation you’re talking about. It would also be a strange omission to not mention the “effective” part of “effective FLOP” explicitly if that’s actually what you’re talking about.
Thanks, I see. I agree that a lot of confusion could be avoided with clearer language, but I think at least that they’re not making as simple an error as you describe in the root comment. Ted does say in the EA Forum thread that they don’t believe brains operate at the Landauer limit, but I’ll let him chime in here if he likes.
I think the “effective FLOP” concept is very muddy, but I’m even less sure what it would mean to alternatively describe what the brain is doing in “absolute” FLOPs. Meanwhile, the model they’re using gives a relatively well-defined equivalence between the logical function of the neuron and modern methods on a modern GPU.
The statement about cost and energy efficiency as they elaborate in the essay body is about getting human-equivalent task performance relative to paying a human worker $25/hour, not saying that the brain uses five orders of magnitude less energy per FLOP of any kind. Closing that gap of five orders of magnitude could come either from doing less computation than the logical-equivalent-neural-network or from decreasing the cost of computation.
I think you’re just reading the essay wrong. In the “executive summary” section, they explicitly state that
and
I don’t know how you read those claims and arrived at your interpretation, and indeed I don’t know how the evidence they provide could support the interpretation you’re talking about. It would also be a strange omission to not mention the “effective” part of “effective FLOP” explicitly if that’s actually what you’re talking about.
Thanks, I see. I agree that a lot of confusion could be avoided with clearer language, but I think at least that they’re not making as simple an error as you describe in the root comment. Ted does say in the EA Forum thread that they don’t believe brains operate at the Landauer limit, but I’ll let him chime in here if he likes.
I think the “effective FLOP” concept is very muddy, but I’m even less sure what it would mean to alternatively describe what the brain is doing in “absolute” FLOPs. Meanwhile, the model they’re using gives a relatively well-defined equivalence between the logical function of the neuron and modern methods on a modern GPU.
The statement about cost and energy efficiency as they elaborate in the essay body is about getting human-equivalent task performance relative to paying a human worker $25/hour, not saying that the brain uses five orders of magnitude less energy per FLOP of any kind. Closing that gap of five orders of magnitude could come either from doing less computation than the logical-equivalent-neural-network or from decreasing the cost of computation.