Moravec’s paradox doesn’t really apply anymore, so it’s worth updating in that direction. “Reasoning” as envisioned in 1976 was a very narrow thing that they thought would generalize with very little compute. They were wrong.
Even moderately accurate reasoning about the real world appears to require more compute than most people have access to today, as even GPT-4 with its probably 10^14 FLOP per answer inference costs can’t do it well.
On the other hand, complex sensorimotor tasks can be handled in portable computing devices that can be embedded in robots. The expensive part of a robot isn’t the compute, it’s all the sensors and actuators and the reasoning required to apply those sensorimotor capabilities.
That’s a good point. I conflated Moravec’s Paradox with the observation that so far, it seems as though cognitive tasks will be automated more quickly than physical tasks.
Moravec’s paradox doesn’t really apply anymore, so it’s worth updating in that direction. “Reasoning” as envisioned in 1976 was a very narrow thing that they thought would generalize with very little compute. They were wrong.
Even moderately accurate reasoning about the real world appears to require more compute than most people have access to today, as even GPT-4 with its probably 10^14 FLOP per answer inference costs can’t do it well.
On the other hand, complex sensorimotor tasks can be handled in portable computing devices that can be embedded in robots. The expensive part of a robot isn’t the compute, it’s all the sensors and actuators and the reasoning required to apply those sensorimotor capabilities.
That’s a good point. I conflated Moravec’s Paradox with the observation that so far, it seems as though cognitive tasks will be automated more quickly than physical tasks.