▲ | mlyle 2 days ago | ||||||||||||||||||||||||||||||||||
Almost anything has a utility scale which is diminishing. But we still see MR=MC pricing in industries with barriers to entry (IPR, capital costs). TSMC and Mercedes don't price cheap to avoid giving others a toehold. > There is a natural monopoly aspect given the ability to train and data mine on private usage data but in general improvements in the algorithms and training seem to be dominating advancements. There's pretty big economies of scale with inference-- the magic of how to route correctly with experts to conduct batching while keeping latency low. It's an expensive technology to create, and there's a large minimum scale where it works well. | |||||||||||||||||||||||||||||||||||
▲ | cjbgkagh a day ago | parent [-] | ||||||||||||||||||||||||||||||||||
I’m unconvinced that the lessons learned from scaling will constitute much of a moat. There is certainly an incentive for incumbents to give such an impression. | |||||||||||||||||||||||||||||||||||
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