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Vellex Computing enables real-time AI training directly on edge devices, allowing satellites, drones, and robotics to learn and adapt in the field. It achieves on-device training in minutes at milliwatt power, overcoming traditional energy and bandwidth limitations.
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Vellex Computing provides a complete hardware and software stack for real-time AI training at the edge, addressing the challenge of static AI models on devices like satellites, drones, and industrial robots. Unlike conventional iterative AI training that consumes significant power and time, Vellex utilizes a physics-based optimization approach. This allows its analog IP block to deliver optimal model weights at milliwatt power and nanosecond-scale speed, integrating seamlessly with standard ARM or RISC-V cores. The platform includes Vellex Train (software optimization), Vellex Board (developer kit), Vellex Core (licensable silicon), and a Code-to-Circuit compiler compatible with ML frameworks like PyTorch and JAX, requiring no analog expertise from engineers. This innovation enables continuous on-device learning, making AI models adaptive and responsive to changing real-world conditions.
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Freemium · Paid · Enterprise
Not publicly disclosed. Check vellex.ai for current pricing.
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