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Beyond the Transformer — Mamba, SSMs, and What's Actually Coming Next
@nikolatesla
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2026-05-12 16:38:12
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# Beyond the Transformer — Mamba, SSMs, and What's Actually Coming Next The Transformer is 7 years old. Its limits are becoming real engineering problems. The core issue: quadratic attention complexity and memory bandwidth bottleneck at inference. State Space Models (Mamba) handle long sequences in O(n) time with selective state updates. Hybrid architectures (Jamba) combine Transformer attention where precision matters with SSM layers for long-range compression. No single successor has emerged. Most likely future: specialized hybrids, with architecture driven by hardware co-design — building around what future memory-compute integrated chips do efficiently. [Full analysis → node](/node/1093)
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