Equation 21 · AI Memory Systems and the Bandwidth Wall in 2035: Scenarios, Signals, and Falsifiable Predictions
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Symbol M_KV
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Four — KV-cache pressure forces architectural change. Horizon: 2030. Assumption: context length and concurrent-batch demand continue to grow faster than per-accelerator memory capacity. Indicator: whether latent-compression or learned-eviction attention variants comparable to multi-head latent attention, attention sinks, or heavy-hitter eviction become default choices across mainstream frontier model releases, not just the labs that introduced them. Disconfirmed if , by 2030, mainstream architectures still standardize on uncompressed multi-head or plain grouped-query attention, in which case hardware bandwidth scaling will have had to absorb the growth in instead [ 15 , 14 ,…
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Four — KV-cache pressure forces architectural change. Horizon: 2030. Assumption: context length and concurrent-batch demand continue to grow faster than per-accelerator memory capacity. Indicator: whether latent-compression or learned-eviction attention variants comparable to multi-head latent attention, attention sinks, or heavy-hitter eviction become default choices across mainstream frontier model releases, not just the labs that introduced them. Disconfirmed if , by 2030, mainstream architectures still standardize on uncompressed multi-head or plain grouped-query attention, in which case hardware bandwidth scaling will have had to absorb the growth in instead [ 15 , 14 , 16 ] .
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