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Stay updated with the latest breakthroughs in AI robotics, warehouse automation, and the future of industrial intelligence.

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Insights.

Cortex 2.0: Planning Before Acting

Cortex 2.0 adds planning to manipulation by introducing a world model that predicts outcomes before committing to motion. Fewer costly failures through rollout scoring by stability, risk, and efficiency. Video-first world modeling learns predictive dynamics in visual latent space.

Partnership Extended: Kardex & Sereact

Kardex and Sereact are extending their partnership to bring next-generation robotic intelligence to high-throughput intralogistics environments, combining proven storage systems with adaptive manipulation powered by Sereact Cortex.

The Real-World Learning Loop

We’re building general-purpose robotic intelligence by learning from live production deployments.

Cortex 1.6: Learning From the Way Things Unfold

Dense Reward Learning from Real-World Robotic Deployments. Cortex 1.6 introduces the Process-Reward Operator (PRO), a learned reward model that extracts dense, continuous learning signals directly from real-world robotic operation.

Strategic path to Generalization

General-purpose robotic intelligence depends on data coverage and distributional alignment, not model scale alone. Robust generalization requires training on interaction data that progressively covers the tasks, environments, and physical constraints encountered in deployment.

Cortex 1.5: Interactive RL Policy Patching for Real-World Robotics

A distributed framework that enables self-learning from human guidance through brief corrective interventions, supporting rapid adaptation to new task conditions while preserving previously acquired skills.

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