But nothing new, there's several (I'm guessing 10-20 + their clones) drones out there that follow you without any tethers for quite some time already without any fancy Tegras. Here's one "shopping guide" from last fall on drones that include the feature to follow a person http://www.dronesglobe.com/guide/follow-me/
Probably to process all the data from all those cameras used for collision avoidance, it needs a more powerful processor than whatever is common in other drones? I think the DJIs have at most one in the front, one in the back and maybe one facing down to monitor for objects to avoid? So this thing may be kind of overkill, though I guess it's going to navigate a forest better than other drones, as they show in that video of the gymnast doing flips and summersaults through the forest.
Tesla AutoPilot v2.5 PCB is showing NVIDIA Pascal and Two Parker Chips http://www.guru3d.com/news-story/te...owing-nvidia-pascal-and-two-parker-chips.html
https://wccftech.com/magic-leap-one-creator-edition-shipping-summer/ Interesting, Tegra X2 is powering the Magic Leap.
Xavier final specs revealed. https://wccftech.com/nvidia-jetson-xavier-pcie-gen-4-support-full-details/ Includes 1.3 TFlops FP32 in a SoC with max TDP of 30W. Would be interesting to know how many TFlops / Watt the chip actually has. If the GPU portion uses 20W, it would scale almost linearly, give or take a TFlop with big Volta, I think.
Bound to happen. A posterchild single application case where a dedicated ASIC makes tons of sense. (What was not bound to happen was for them to roll their own full out, which is interesting even if many blocks will be off-the-shelf IP.)
I thought the SoCs handling the driving were also being used for the cars' infotainment system. Can Tesla make SoCs that also handle video, 3d render for maps display and always-on connections?
Should be different portions of the same Soc anyway, if that's the case. Traditionally, infotaiment had the most powerful controllers in the car. You potentially may start from that when adding new functions which would require raw processing power . The inverse of that is absurd in my opinion, on the other hand. If you need/have good inference DSP/accelerators, there's 0 pressure to make them handle video playback, navigation and whatnot. As a car company with some tradition, you already have an existing solution for that, in house or off the shelf Also self driving functions should have more stringent requirements wrt to safety or availability. Separating them from infotaiment makes even more sense as such
It will be interesting to see how successful they are. To put it into perspective how many production HW designs out there successfully using tensor based architecture effectively for DL-inferencing beyond Google and Nvidia? I can only think of a couple of others that could be deemed production ready and with any semblance of a deep framework/library support, and they have been around for quite awhile with their expertise. Let alone as well integrating multiple camera/lidar/radar technology with their data-objects into the autonomous system to process.
The NVIDIA Jetson TX2 Performance Has Evolved Nicely Since Launch 29 August 2018 https://www.phoronix.com/scan.php?page=article&item=jetson-tx2-2018&num=1
Is there anything in the information/entertainment system of a car that can't be handled by run-of-the-mill Mali cores?
Not only garden variety ARM GPU IP but any relevant IP out there. But since any IP provider isn't necessarily responsible for things like software or even system stability in a final product (bundle), you might want to overthink that question; as to why NVIDIA is actually landing as many automotive deals after all.