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A closed-loop control layer for model transformation. Actuator monitors, adjusts, and guardrails your post-training transformations in real time.

We introduce Divergent-Convergent Attention (DCA), a transformer primitive that maintains parallel attention streams at different window sizes and reconciles them through learned periodic consensus.

Autonomous ML research agent that conducts rigorous scientific research end-to-end: literature review, hypothesis generation, experiment design, execution, analysis, and documentation.

Elastic speculation delivers 30–50% lower latency and up to ~50% fewer speculative KV writes in our experiments, while preserving output quality.