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Foundation Models

Articles

Skild AI Introduces S1 Robotics Foundation Model with In-Context Video Prompting
Robotics foundation model startup Skild AI has unveiled S1, a foundation model capable of learning physical manipulation tasks unseen during pretraining directly from a single video demonstration prompt without fine-tuning. Traditional robotic adaptation typically requires extensive task-specific teleoperation data, domain randomization, and model fine-tuning before a system can reliably execute novel actions. S1 employs in-context prompting to translate visual demonstrations directly into real
August 25, 20261 min
Generalist AI Releases GEN-1.5: One-Shot In-Context Learning for Robotic Manipulation
Robotics research startup Generalist AI announced GEN-1.5, an embodied foundation model capable of learning closed-loop physical manipulation tasks from a single demonstration without gradient updates or fine-tuning. The model adapts through in-context physical prompting, mirroring the few-shot learning dynamics originally identified in autoregressive language models. GEN-1.5 processes multimodal inputs including multi-view video, proprioceptive signals, sensor feeds, and natural language instr
August 20, 20261 min