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Brain Efficiency: Much More than You Wanted to Know — LessWrong

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What if the brain is highly efficient? To be more specific, there are several interconnected key measures of efficiency for physical learning machines: Why should we care? Brain efficiency matters a great deal for AGI timelines and takeoff speeds, as AGI is implicitly/explicitly defined in terms of brain parity. If the brain is about 6 OOM away from the practical physical limits of energy efficiency, then roughly speaking we should expect about 6 OOM of further Moore's Law hardware improvement past the point of brain parity: perhaps two decades of progress at current rates, which could be compressed into a much shorter time period by an intelligence explosion - a hard takeoff. But if the brain is already near said practical physical limits, then merely achieving brain parity in AGI at all will already require using up most of the optimizational slack, leaving not much left for a hard takeoff - thus a slower takeoff. In worlds where brains are efficient, AGI is first feasible only near

x Brain Efficiency: Much More than You Wanted to Know — LessWrong AI Takeoff Biology Physics AI Frontpage 218 Brain Efficiency: Much More than You Wanted to Know by jacob_cannell 6th Jan 2022 34 min read 103 218 What if the brain is highly efficient ? To be more specific, there are several interconnected key measures of efficiency for physical learning machines: energy efficiency in ops/J spatial efficiency in ops/mm^2 or ops/mm^3 speed efficiency in time/delay for key learned tasks circuit/compute efficiency in size and steps for key low level algorithmic tasks [1] learning/data efficiency in

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