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blimpyway t1_ivivcwr wrote

Reply to comment by IntelArtiGen in [D] At what tasks are models better than humans given the same amount of data? by billjames1685

Tesla collected 780M miles of driving till 2016

A human learning to drive for 16h/day at an average speed of 30mph for 18years would have a data set of ~3M miles.

So we can say humans are at least 1000 times more sample efficient than whatever Tesla and any other autonomous driving companies are doing.

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The_Real_RM t1_ivizjvu wrote

You are assuming Tesla actually needs all that data to train a competing model, you're also ignoring all of the other training a human has before ever starting to drive. It's not so clear who is more efficient, not at all.

I think a better way to compare is thorough the lense of energy, a human brain runs on about 40w of energy, Tesla's models are trained on MW scale computers, how do they compare in terms of total energy spent to achieve certain performance?

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IntelArtiGen t1_ivj6nih wrote

Probably not, because a 16 y.o. human has 16 years of interactive navigation pretraining in a real world environment in real time before learning to drive. So it depends on how you include this pretraining.

And it also depends on the accuracy of the model as a function of the size of the dataset. Let's say Tesla is 80% (random number) accurate while driving after training on 780M miles, a human is 75% accurate after 3M miles, and if you train the Tesla model on 3M miles instead of 780M it's 75% accurate, on these metrics alone Tesla would be as efficient as a human.

No comparison is perfect but we can't ignore that during the first years of our lives we train to understand the world while not being very efficient to perform tasks.

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