nvidia x1 Connectivity Solutions Will Not Help with Autonomo(3)

Such enormous compute power will not be avaible on mobile machines for many years to come. These days, the most powerful computer on a tractor or harvester is the terminal. The Agritechnica-2017 crop of terminals sports at most a quad-core NXP i.MX6 processor (see my post Agritechnica 2017: What’s New for Terminals?). This is the same performance class as the iPhone 4S– released in October 2011! This is ancient technology.

These terminals would not be able to run the models produced by machine learning algorithms, let alone the learning algorithms themselves. Even in 2018, voice assistants record the sentences spoken and send the recording to a powerful cloud server. The cloud server translates the spoken into written sentences and sends the text back to the phone. Even contemporary phones are not powerful enough to perform voice recognition “on board”. They would be powerful enough to recognise language with restricted vocabulary, although the battery would suffer heavily from all the computations. Fortunately, farm machines have bigger batteries than phones.

The fix for now would be to build terminals with processors or system-on-chips (SoCs) comparable to those of current high-end phones. One such SoC is the Renesas R-Car H3with four 64-bit Cortex-A57 cores, four 64-bit Cortex-A53 cores and one Cortex-R7 core for real-time and safety-critical applications. Another SoC is the NVIDIA Tegra X1with its 256 GPU cores. These SoCs have a performance similar to mid-range laptops. They are capable of running the models to perform learned tasks and to perform some learning online on the terminal.

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