so for example if you are doing object detection, we have a one-stage yolo-like object detector here where we initialize a raster, and there's a binary bit per position telling you whether or not there's a car there and then in addition to that, if there is, here's a bunch of ot...
examples from the offline algorithm are used to train the approximating network which is used in inference on board. The goal here is if the good off-line optimization can't be done computationally efficiently on-board in time, but a neural approximation can. A aronth5 Long Time Follower ...
Incorporating radar return in the algorithm would go a long way in reducing this I think. Reactions: SilverString TravelFree Active Member Mar 23, 2020 1,186 1,170 Jacksonville, Florida Nov 14, 2021 #488 Knightshade said: Not quite right. For non-beta cars with radar, it's still...
The new M40 and M4 GPUs are powerful accelerators for hyperscale data centers. Combined with the NVIDIA Hyperscale Suite and GPU deployment capabilities in Apache Mesos and Docker containers, developers of data center services will be ready to handle the massive data of the world’s users. ...
we estimate the Robo-car fleet size to reach ~200k units by 2025 and to 1.4mn by 2030. The key drivers are fast-falling hardware cost, upgrading algorithm, improving infrastructure, and favourable government policy. We estimate Hesai’s Autonomous Mobility LiDAR (for Robo-cars)...
FSD Beta today is practically the result of good c++ conventional & traditional control and decision making algorithm while using their previous Neural networks. The same way their NOA worked. Nothing ground-breaking or futuristic. Definitely none of the stuff you and @mspisars hav...
Then when it does, you can pay $2,000 for firmware acceleration, that is just a bug fix in the original acceleration algorithm. I find it odd that my mid range rear drive model 3 is faster than my long range dual motor model Y. I suppose they decided to hold back performance and ...
And then a second intel/nvidia chip to run all your custom algorithm and driving policy if you wanted. Its similar to what Audi did with the L3 A8, they use an eyeq3 for all the vision stuff and then they use another chip to run their own custom algorithms for control actuation. While...
You could have the best algorithm and sensor suite on the planet, but if the car thinks it's on the service road instead of the freeway's right-hand lane due to a map or GPS error, you're doomed. (And I've seen both cases, repeatedly). I see no easy...
Everything is based on corrective algorithm. EVERYTHING. Radar doesn't need the same corrections to measure distance through fog, snow, rain, etc. Lidar has to throw away data from laser reflections on nearby objects whereas radar can go through water. Bladerskb said: AP1 radar fails all...