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0 pointsNevermark1y ago0 comments

As apposed to humans who all derive the physics of heat transfer independently when given a question like this?

Not picking on you - this brings up something we could all get better at:

There should be a "First Rule of Critiquing Models": Define a baseline system to compare performance against. When in doubt, or for general critiques of models, compare to real world random human performance.

Without a real practical baseline to compare with, its to easy to fall into subjective or unrealistic judgements.

"Second Rule": Avoid selectively biasing judgements by down selecting performance dimensions. For instance, don't ignore difference in response times, grammatical coherence, clarity of communication, and other qualitative and quantitative differences. Lack of comprehensive performance dimension coverage is like comparing runtimes of runners, without taking into account differences in terrain, length of race, altitude, temperature, etc.

It is very easy to critique. It is harder to critique in a way that sheds light.

0 comments

selcuka1y ago

> As apposed to humans who all derive the physics of heat transfer independently when given a question like this?

Isn't that the difference between learning and memorizing, though? If you were taught Newton's Law of Cooling using this example and truly learned it, you could apply it to other problems as well. But if you only memorized it, you might be able to recite it when asked the same question, yet still be unable to apply it to anything else.

accrual1y ago

> It is very easy to critique. It is harder to critique in a way that sheds light.

Well said. This is the sort of ethos I admire and aspire to on HN.

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