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NNs are just the first step in the pipeline. Their outputs (detected objects, segmentation, etc) will be piped into other software that builds higher level mode
by hemogloben 8y ago
NNs are just the first step in the pipeline. Their outputs (detected objects, segmentation, etc) will be piped into other software that builds higher level models.
Considering the path-planning requirements I would be absolutely shocked if Autopilot wasn't build history models and estimated paths for objects around the vehicle (other cars etc).
- JanSolo 8y agoAgreed; I imagine they use neural networks to detect and classify objects which are then saved into a scene-graph for use in pathing. I expect what happened was that they trained their NNs for improved detection in one area but unknowingly reduced it in another. Perhaps now it can detect tricycles 99% but road barriers went down to only 30%. Having worked with NNs it's very common to see gains in one domain which come at a cost of reduced performance in another.
- stevenjohns 8y agoThey must have known. I haven’t worked with NNs for a few years but I don’t believe the methodology has changed where you would stop testing it over different sets of training data. Barriers are a pretty big part of driving on roads and highways and the only reason it would have been unknowingly reduced would be if they just weren’t testing the NN against data with them.