Sereact introduces Cortex 1.6 with Process-Reward Operator for real-world robot learning
Evidence notes
- Sereact introduced Cortex 1.6 and its Process-Reward Operator for dense reward learning from real-world robotic deployments.
- The update converts operational signals into progress, completion-likelihood, and risk estimates for reinforcement learning.
- Sereact reported 6–9% success-rate improvement over Cortex 1.5, 1.7 times higher recovery rate over baseline, and faster training convergence.
Company context
Sereact develops embodied AI software for robotic manipulation in logistics, warehousing, and industrial environments. Its Sereact Cortex platform enables robots to understand scenes, identify objects, and execute manipulation tasks without fixed object lists or rigid pre-programming.