Gunnar_Zarncke

Software engineering, parenting, cognition, meditation, other
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Note that while he has amazing recall, to me, it seems that he has much less synthesis than you might expect. I remember that only later in life did he start to draw some connections between data he consumed. He doesn't seem to form an integrated world model from all of the data.

In that sense, Kim Peek is more like a database with free lookup while GPT-3 is more like a human in that it provides integrated answers but can't quote verbatim in general (or tell where its knowledge is coming from).

Maybe there is a trade-off between integration and recall.

Sure. 

Do you know more about the attack surface of Tesla vs. other cars?

9000 books with one megabyte of information each. Note, that he memorized whole telephone books that way and tests have shown that he has >95% recall. 

Just a data point that support hold_my_fish's argument: Savant Kim Peek did likely memorize gigabytes of information and could access them quite reliably:

https://personal.utdallas.edu/~otoole/CGS_CV/R13_savant.pdf 

Language and concepts are locally explainable.

This means that you do not need a global context to explain new concepts but only precursor concepts or limited physical context.

This is related to Cutting Reality at its Joints which implicitly claims that reality has joints. But maybe, if there are no such joints, using local explanations is maybe all we have. At least, it is all we have until we get to a precision that allows cutting the joints.

Maybe groups of new concepts can be introduced in a way to require fewer (or an optimum number of) dependencies in each case, thus making them easier to understand.

Maybe that is the true job of philosophy - refining local concepts until you reach the joints.

All modern cars have that.

My asthma makes running difficult for me at speeds noticeably faster than the brisk walk I usually do (6 km/hour). But I use alternatives are probably close to in spirit: 

  • walk by default - for short distances and work talking to some of my friends.
  • cycle by default - for distances up to an hour, I use my bike, even if I could potentially save some time by using public transportation. 

I have multiple friends (in Germany) who eat snacks with chopsticks. I can confirm that it seems easy to learn and efficient. It has the advantage that you eat a bit slower, which makes it more likely that you do not overeat.

I have been walking back and forth a 50m trail for hours as part of a meditation exercise. It was quite a deliberate effort. I concentrated on the movement of my hip bone and learned a lot from it. But I can't say that it is "inexplicably good."

Are there different classes of learning systems that optimize for the reward in different ways?

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