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A system for distributed image labelling to accelerate Tesla's AV development

How many hrs/mth would you volunteer to label own AP images to improve EAP/FSD?


  • Total voters
    7
  • Poll closed .
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I heard recently that MobilEye had planned to have 1000 people engaged full-time by end of 2016 at labelling image data gathered from their small experimental AV fleet, as the basis for training their neural network, and that they were farming this task out to cheap labor in Sri Lanka.

Bloomberg - Are you a robot?

This caused me to wonder how many people Tesla dedicates to the same task and hence the realisation that they essentially have a large cohort of uniquely motivated experts on tap who would gladly do this work for free while sitting at the SuperCharger or similar waiting situation.

My presumption is that, if such a distributed feedback system were implemented well, it could significantly advance the advent of safer EAP and/or FSD, which we all dearly wish to see ASAP, by working something like this:

1. Have volunteer owners with EAP/FSD apply/qualify for programme, commit to X hour(s) per month of labelling, receive any necessary training through local Service Centre.

2. Take as data basis the driver’s self-generated images/video (reduces up/download volumes).

3. Queue & present scenarios for labelling in an app on centre console (or phone) while SuperCharging or other idle times.

4. Send results to Tesla when finished and next connected to WiFi (no extra LTE burden).

5. Possibly add a rewards system to incentivise participation (apart from improving AP performance/safety on own local roads which may be far removed from California)


If you agree this would be a productive pastime for serious adults and would like to see it realised, please take the poll and add any further or better thoughts below, thanks!


( PS: Great minds think alike ... someone on Reddit has just had the same basic idea:
Speed Up Full Self Driving: Data Labeling While Supercharging : teslamotors )