Agriculture as the Testbed for Physical Intelligence
Physical AI does not fail in laboratories. It fails in mud, dust, glare, vibration, biological growth, and seasonal drift. Agriculture lives permanently in these conditions. Models that work reliably on farms tend to work everywhere else; the reverse is rarely true. This discussion argues that agriculture is not downstream of physical AI. It is upstream. Defense, aviation, and autonomy demand physical AI that generalizes beyond narrow scenarios. Agriculture already forces this generalization across crops, soils, weather regimes, machinery, and human workflows. By treating agriculture not as an application layer but as a systems-level stress test, we can accelerate the development of robust, transferable physical intelligence.
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