The main challenges include unpredictable latency between digital decisions and physical actions, environmental calibration issues (like lighting conditions affecting vision models), integration complexities between AI inference engines and low-level hardware controllers, and trade-offs between computational intelligence and battery life/operational uptime.
The main challenges include unpredictable latency between digital decisions and physical actions, environmental calibration issues (like lighting conditions affecting vision models), integration complexities between AI inference engines and low-level hardware controllers, and trade-offs between computational intelligence and battery life/operational uptime.
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The main challenges include unpredictable latency between digital decisions and physical actions, environmental calibration issues (like lighting conditions affecting vision models), integration complexities between AI inference engines and low-level hardware controllers, and trade-offs between computational intelligence and battery life/operational uptime.
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