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  • Integrating your software to run in a real system is hard.

    • Hardware in the loop testing and ensuring we have sufficient dev kits is a great way to mitigate these challenges.

  • Hardware will need to be upgraded as newer superior hardware is released as time progresses.

    • If we want to use hardware that supports specific software features then we need to buy that hardware. (i.e. CUDA requires specific hardware which can be bought for airside or groundside compute).

  • Hardware compute limitations will be a limiting factor for more complicated machine learning algorithms.