Resources

Generalizability matters, but it differs between generalizing within a domain and generalizing across unrelated tasks. This blog explains why industrial robots need domain generalizability to handle the tasks and variations within their industry while meeting the speed, quality, and reliability requirements that make automation worthwhile.

Chef’s AI-enabled robots are designed specifically for food manufacturing environments. They feature NSF-certified hardware, removable food-handling components, safety-rated controls, and ergonomic design features purpose-built for food production. This blog explores how Chef robots support food safety, allergen control, sanitation, and worker safety on production lines.

Chef Robotics runs AI-enabled food assembly robots at scale across production sites in North America and Europe. Here’s how Chef's support team delivers round-the-clock coverage, real-time remote diagnostics, and on-site technician support to keep a global robot fleet running reliably.

A new survey paper by Chef Robotics Senior Staff AI Research Scientist Inkyu Sa maps the relatively new field of world models and world-action models and evaluates which modeling approaches are best suited for robotics, autonomous driving, reinforcement learning, games, and general-purpose simulation.

A new survey paper by Chef Robotics Senior Staff AI Research Scientist Inkyu Sa examines the rapidly evolving field through one of robotics' hardest challenges: bimanual manipulation, or coordinating two arms to complete tasks such as folding fabric, assembling objects, and handling deformable materials.

We built ValueFormer, a critic that watches the cameras our policy uses and provides feedback on policy performance that behavior cloning can’t provide. Folded back into policy training, ValueFormer shows early on-robot success: two different critic-derived weightings each increased successful burger assembly from 70% to 85%.