Cheaper than the $150 Google TPU Dev Board, and looks like it can do training as well as inference. Also, doesn't require you to send your model to their company. Nice!
Quad core arm, 4gb of ram and gigE!
Seems like a really nice board
Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
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Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#32I have a Jetson TX2, at the $99, I'm super tempted to buy one to see how it compares. That being said, I would definitely buy this if there is a way to make Plex server work with transcoding.
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#33I have a Jetson TX2, at the $99, I'm super tempted to buy one to see how it compares. That being said, I would definitely buy this if there is a way to make Plex server work with transcoding.
That's exactly what I want as well!
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#34why would you want to train on the device itself?
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#35Just bought one. Been a while since I played with embedded systems (or ML for that matter) :) Anyone have any cool ideas for how to make this little toy useful?
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#36I hope to put it into a pi-top https://accounts.pi-top.com/products/pi-top/ not sure if this fits
It won't work.
This doesn't look like it's the same form factor as the Pi. (Inside the pi-top are mounting points that align with the pi's form factor mounting holes.)
Also the pi-top's power switch and supply go through the Pi's GPIO pins so those would need to be a match as well.
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#37Hope it'll ship with better support that the first Jetson. The one they marketed with all that AI/Machine Vision stuff and then shipped without a camera driver. This is just following Google's Edge TPU, which probably competes with a Raspberry Pi + Movidius stick. The market there is getting interesting.
This. And all of the third party camera solutions for TX2 cost $500+ when equivalent USB cameras with the same sensor cost $50. They really need to get their act together and sell some NVIDIA-sanctioned camera solutions at scale, and at price points similar to Raspberry Pi cameras. A lot of third party carrier boards also have a complete sh_tshow of connectors. Auvidea's boards, for example, ship with a Raspberry Pi…
They've actually fixed this hopefully this time around.
According to their blog post it actually has driver support for the RPi CM2 8MP (IMX219) and they'll be releasing their own Nvidia-sanctioned cameras available from their partners.
It should hopefully just work. No lowlight options at this time however, which means external CCTV is out of the question :(
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#38I wish these tiny SBCs came with SATA or m.2 so I could hook up an SSD. I know microSD is catching up, but it's not there yet.
PCIe should be able to do SATA on here - they showed a reference design running PCIe-based SATA devices in their blog post, which was recording 8x1080p30 H.264 to a HDD.
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#39why would you want to train on the device itself?
To fine tune the model to the specific customer needs. For example, learning the parameters of they user's face.
Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts
#40the pricepoint is good, relative to the jetson tx1/2 (299-749 usd) and xavier (1099 usd). some of my notes, there is a massive heatsink on this thing, probably for both the a57 cpu and maxwell gpu, this will make your case a bit larger than say the rpi. not sure how the a57 compares to rpi’s a53, i assume both are armv8, quad-core. the inputs seem identical to rpi 3 model b+, hdmi, ethernet, 4 usb (seems 2.0), mini u…
a) a57 is the "beefy" version of a53, it's significantly faster in raw performance so this should stomp an rpi - here's ARM's performance numbers at release: https://community.arm.com/cfs-file/__key/communityserver-blo...
b) above the HDMI is displayport
c) usb is 3.0 all around, great for NAS-style devices
d) production module (for final product) uses 16gb emmc, whereas the devkit is microSD like rpi