
Four Paths Beyond the Transformer Bottleneck
The article examines why dense attention in Transformers is becoming costly and difficult to scale for long-context and reasoning workloads. It highlights four emerging directions, including sparse attention, power retention, liquid foundation models, and smaller, more flexible architectures, while noting that several company claims remain unverified.
虎嗅 · 12d ago























