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The problem is manual labelling doesn't scale. Switching to an unsupervised approach is what made many huge AI advances over the past couple years possible sinc
by zaptrem 3y ago
The problem is manual labelling doesn't scale. Switching to an unsupervised approach is what made many huge AI advances over the past couple years possible since we're mostly limited by compute now. For Tesla (who have practically unlimited driving footage) this is particularly advantageous.
- andrewmcwatters 3y agoIt’s not the labeling itself, it’s whether or not you’re allowing unfiltered longitudinal control to originate from neural nets. Good but erratic lateral control at worst results in hugging a lane line. Anything less than perfect longitudinal control means the driver will toggle it on and off during portions of traffic where it won’t follow the flow of traffic closely enough, or if it follows to closely, or if you’re experiencing a high cabin jerk factor. You cannot screw up longitudinal control. It’s nearly the whole experience.
- zaptrem 3y agoI think this is what end-to-end models will be best at, since they'll be able to account for far more environmental factors than a manually written planner flipping between the stop light deceleration curve and car-ahead curve constantly, for example.