1.2 KiB
| name | description | metadata | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| all-on-platform | User requires INFERENCE fully on KNP/AltAI (pixel → answer); training may be off-platform. Demo goal: UAV object recognition, live |
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Inference must run entirely on the platform (KNP/AltAI neurons, pixel → answer); no part of recognition may be computed in Python or our own simulator. Training does NOT need to be on AltAI (clarified 2026-10-15: "нам важен именно инференс на алтае, а обучение не важно") — train offline with whatever gives the best accuracy, then load weights into KNP.
Why: the live demo (week after 2026-10-15) must show AltAI can replace a neural network for object recognition in UAV systems; that claim is about running recognition on the neuromorphic processor. How to apply: don't spend time on on-chip learning rules; fold preprocessing into neuron weights, verify accuracy with KNP itself, report which numbers come from KNP. Prefer drone-relevant classes (CIFAR-10 vehicles). Related: knp-mnist-altai-work.