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"With a big enough engine even a brick will fly." - famous quote about the F-4, which captures that much of early airplane development was engine development rather than aeronautics. It's no coincidence that Glenn Curtiss got his start in motorcycles before moving onto aircraft.

I think to some extent we are seeing the same thing with the latest AI models, where if you just throw enough parameters and GPU's at a problem, you can get pretty good results.

In a way, I see some parallels to aircraft, in that it was important to study birds as the best example of heavier than air flyers early on, but understanding the nuances of the biomechanics of flapping wasn't necessary to surpass them.



You can get improve the low hanging fruit through brute force ... but there is a lot of low hanging fruit.

Model architecture cleverness will eventually outpace more GPU time, but for now the roi on GPU time is higher than clever design.




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