The Sequence Knowledge #878: Beyond Transformer: What We Learned
TheSequence Jesus Rodriguez
A series examining transformer alternatives concludes that the transformer architecture's dominance is ending, with four families of alternatives emerging: recurrent and linear-recurrent models, state space models, text diffusion, and liquid continuous-time models. State space models like Mamba show linear scaling and long-context handling with near O(n) compute versus attention's O(n²), though the strongest current results use hybrid architectures combining attention with other approaches. The future architecture will likely be explicitly hybrid, using attention only where exact recall justifies its quadratic cost and deploying linear-time alternatives elsewhere.
Why it matters
And a new series about Distillation
