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Tesla would have been stuck at level 2/3 with Mobileye. With PX2 you have enough compute power to do much more, and a mature and rapidly developing GPGPU ecosys

by dharma1 10y ago

Tesla would have been stuck at level 2/3 with Mobileye. With PX2 you have enough compute power to do much more, and a mature and rapidly developing GPGPU ecosystem (CUDA for ML, SLAM, SfM etc). I do think Nvidia is going to have to bring the price of PX2 down significantly though if they want mass market adoption.

Fricken 10y ago
It seems Tesla and Mobileye were at one time planning on a bright future together, because Tesla didn't have any kind of a back-up plan. But Mobileye isn't sitting still, so if the relationship hadn't been terminated, Tesla would've been stuck with whatever Mobileye's latest and greatest offering might be. What's interesting is that if you compare the HW2 sensor suite to Mobileye's next-gen sensor plans, they are very similar, almost the same. They were both working on something together before the relationship went sour. Musk hinted recently that 1 PX2 is not enough, and that 2 may be necessary for L4. There's certainly no consensus as to how much compute is needed, the more the better, but I'm skeptical that the hardware costs will be low enough near term to justify putting it in privately owned autonomous cars. I think Tesla has made costly strategic errors in the Autonomy department, and that Musk in particular has repeatedly underestimated the challenge of developing a fully autonomous vehicle. I don't think he's making that mistake anymore.
argonaut 10y ago
Autonomous driving is a software engineering/research problem, not a hardware bottleneck. You couldn't train a good autonomous driving agent even if you used a massive GPU cluster. I'm not saying better hardware doesn't help, it definitely helps incrementally but it's not going to be enough to solve this problem.
- dharma1 10y ago
  Absolutely agree. However I'd wager to say that betting on a powerful Nvidia GPU/chipset (piggybacking on general ML/CUDA ecosystem progress) to be able process rapidly advancing autonomous driving algorithms is a more future proof bet for Tesla than relying on already outdated hardware/algorithms from Mobileye.

by dharma1 10y ago

Fricken 10y ago

It seems Tesla and Mobileye were at one time planning on a bright future together, because Tesla didn't have any kind of a back-up plan. But Mobileye isn't sitting still, so if the relationship hadn't been terminated, Tesla would've been stuck with whatever Mobileye's latest and greatest offering might be. What's interesting is that if you compare the HW2 sensor suite to Mobileye's next-gen sensor plans, they are very similar, almost the same. They were both working on something together before the relationship went sour. Musk hinted recently that 1 PX2 is not enough, and that 2 may be necessary for L4. There's certainly no consensus as to how much compute is needed, the more the better, but I'm skeptical that the hardware costs will be low enough near term to justify putting it in privately owned autonomous cars. I think Tesla has made costly strategic errors in the Autonomy department, and that Musk in particular has repeatedly underestimated the challenge of developing a fully autonomous vehicle. I don't think he's making that mistake anymore.

argonaut 10y ago

Autonomous driving is a software engineering/research problem, not a hardware bottleneck. You couldn't train a good autonomous driving agent even if you used a massive GPU cluster. I'm not saying better hardware doesn't help, it definitely helps incrementally but it's not going to be enough to solve this problem.

dharma1 10y ago
Absolutely agree. However I'd wager to say that betting on a powerful Nvidia GPU/chipset (piggybacking on general ML/CUDA ecosystem progress) to be able process rapidly advancing autonomous driving algorithms is a more future proof bet for Tesla than relying on already outdated hardware/algorithms from Mobileye.