Occupancy Flow Fields for Motion Forecasting in Autonomous Driving · HackerPapers discussions

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving — mentioned by cs702

Sat, 15 Oct 2022 16:19:00 GMT

> I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. I'd sum up those three points as "more data and more real-world, open-ended, large-scale testing by regular people." Big difference. > Occupancy networks: waymo has published research on this before Tesla announced this at AI day (not clear to me who got there first though https://arxiv.org/pdf/2203.03875v1.pdf) AFAIK, Tesla FSD Beta is the only system that has been using these DNNs for open-ended testing.…

Paper and discussion history. A mention is not an endorsement.

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving — mentioned by dontreact

Sat, 15 Oct 2022 15:22:11 GMT

I'd sum up your points 1,2,3 as "more data". This would be a reason to think they can one day be ahead if they can take advantage of this, but not evidence that they are currently ahead. Occupancy networks: waymo has published research on this before Tesla announced this at AI day (not clear to me who got there first though https://arxiv.org/pdf/2203.03875v1.pdf) Tesla's Dojo -> Waymo has TPUs to train on To me all of this is outweighed by the fact that Waymo has a driverless deployment and Tesla does not. I am pretty biased because as a Tesla owner I am pretty pissed off at this point at how…

Paper and discussion history. A mention is not an endorsement.