platoseedplatoseed
Deployable Physical AI on Any Edge Device.
General Instinct provides a deployment layer for physical AI, enabling frontier models to run on any edge device with sub-100ms latency. It positions itself as a deployment solution for edge AI across diverse devices.
A deployment layer that allows any frontier AI model to be deployed on any edge device, delivering sub-100ms performance. The product focuses on enabling edge AI deployment without specifying device or model constraints, suggesting a portable runtime or orchestration layer for edge hardware.
Who it’s for: Edge AI teams and organizations needing to run frontier AI models locally on edge devices, across industries requiring low-latency on-device inference.
worked on Siemens' first multimodal foundation model, secured 2 patents on tardigrade proteins as a junior in high school, now building edge intelligence for physical AI.
Worked on robot learning and multimodal foundation models at DeepMind, UCL, and Tsinghua, with research recognized at ICML and ICRA. Now building the deployment layer for physical AI.
Deploy frontier AI models onto constrained edge hardware for robots, drones, and physical AI systems.
General Instinct distills and deploys large AI models onto resource-constrained edge hardware used in robots and drones. The platform compresses models and provides offline runtimes optimized for latency and hardware constraints.
▲ 9
Formerly “Bitstream” · why startups rename →
The default way of running on-device AI at Scale
The agent-native cloud infrastructure platform
