Nvidia Adds Jetson TX1 To Its Deep Learning Roster

[heirdeux]

Nvidia's next product for deep learning is about the size of a credit card and is meant for use in drones and robots.

Nvidia Adds Jetson TX1 To Its Deep Learning Roster : Read more

 

[Shankovich]

I've worked with enough UAV's to know this thing is way too expensive and power hungry to do most tasks needed. For civilian applications engineering (like me), something like an ARM only board is more than enough for flight controls, transmission, flight path recognition commands, and stability and control. I'm guessing they really want you to use those CUDA cores, but for anything flying, it's a bit overkill on power consumption. Can't complain about the size though, we'd have to see if the tradeoff between weight and power consumption pays off. $300 though..............

 

[shloader]

A micro USB3 port would have been more universally leveraged vs a Gigabit port. Some might use a gig port during development but the option for an LTE radio could take it even further. At the rate we're seeing drone processing power advance, not to mention battery capacities, we'll probably start seeing drones with LTE radios on board so they can tour beyond WiFi range and report back anything they determine to be of interest to the operator in real time. Also so the operator can issue adjustments to the tour at greater range.

 

[conrd6]

Nvidia's product announcement for the Jetson TX1 dev kit
https://developer.nvidia.com/embedded/buy/jetson-tx1
shows an ARM A-57 CPU, but no camera, just a header for a camera. The whitepaper https://developer.nvidia.com/embedded/jetson/TX1/docs/jetson_tx1_whitepaper.pdf
shows performance capable of real time 30fps image classification (actually up ro 258 fps) at less that 6W power consumption. MIT students recently demonstrated that even the older/slower TK1 was capable of autonomous model car racing.
The documentation is way less developed than for the TK-1, but I'm ordering one anyway. By the time the documentation catches up, I will have figured out the basics of installation and workflow, and can start designing autonomous tractors/weeders.