🙀 Jetson Wuh? What Is it?
The NVIDIA Jetson Nano is, essentially, an amazing little computer. I’d describe it as a lot like a Raspberry Pi, except it has a GPU.
Combine that with its low $99 USD price tag, and AI/ML enthusiasts see a cheap device that can go from desktop to edge with perfect parity.
An ideal machine for AI in the wild!
BONUS SELLING POINTS THAT GOT ME EXCITED
- As a Mac user, I often find myself with a wimpy GPU. This little device might outperform my MacBook Pro for AI/ML training.
- Some semi-important libraries, like Dlib, aren’t built for Windows, so you need a Linux machine to get that GPU bump.
- Any good excuse for running Linux again.
My Goal?
I have an old 2012 iMac that sits to the right of my station that I don’t generally use, even though I could switch my mouse/keyboard with the press of a button.
Instead, I could replace this space with the Nano. BUT… It’s not a crafting table; I’m going to need to close it up like little computer and keep it safe.
Something like this GeekWorm case will do!
Sounds like a plan! I can just order me a $30 case on top the $99, and I’m set!
… or am I?
Dirty Secret #1 — Price in Parts
You’re not done buying. Time to load your cart up with a few extra items needed to simply get the Nano running.
SD Card: Much like the Pi, the SD card isn’t included. Most of us are used to this for edge devices. Since I want a desktop-level device, I sprang for the 256GB micro card. +$35 USD
Power: The 5v 2a USB power supply can’t handle peripherals. SURPRISE! You’ll need to get a 5v 4a barrel jack so you don’t lose your screen. +$14 USD
Fan: Some cases come with fans. The one I got did not. Throw a 5v fan in to cool the GPU. +$15 USD
Wifi + Bluetooth: Unlike the latest Pi devices, there’s no WiFi or Bluetooth, so you’ll have to buy that card separately. +$21 USD
Antenna: The WiFi card does not include antennas. I was crazy and attached an internal antenna inside on the first port, and with the second antenna, I ran it to the external of the case. +$14 USD
This sneaks the price of my desktop from $130 (device + case) up to $230.
Dirty Secret #2 — DIY Only
This device is perfect for the computer builder, the robot maker, and the all-out puzzle solver. If you’ve got a workshop, you’ll be happy!
If you don’t have a workshop or time, you’re in trouble.
The screw holes for the fan are not tapped, the parts unpacked fill a small table, and the card installation requires a little know-how. It’s like IKEA furniture. If this is your first time, it’s going to take a while, and as soon as you’re done, you’ll reflect on how you could have done it in a quarter of that time.
While I’ve done some wild stuff with Raspberry Pi’s, I’ll admit I was looking up all kinds of conversions while I was at the hardware store, and ultimately ended up over-buying just to ensure I wasn’t going to get the wrong size.
Dirty Secret #3— You’re Still Not Ready Yet?
Finally! I’ve got this little black box sitting on my desk, it’s wired up, tested, and ready to go! I load up Ubuntu, and I go to install a package, and…. pip is not installed. Python is there, but quite a few common libraries you’d expect to be on the image are completely missing.
Now I get that you might not need everything… but for those of us who do, we’ve got a big install ahead of us, and given that it’s a small CPU, we’ve got hours of installs.
Fortunately, here’s a fantastic article that enumerates the next few hours of your life:
This tutorial doesn’t get OpenCV running, so you’ll need to build that from source. Hopefully, we’ll find a good tutorial for that soon.
TL:DR; You can expect hours of setup before running your first project on the device.
The Dirty Summary
I guess the big issues here are the BTB (barriers to bench-marking). If you’re looking to simply evaluate the Jetson Nano as a tool, you’re biting off days of ancillary tasks and unknown costs to pit this device against an old laptop or phone.
The on-boarding isn’t necessarily difficult, just significant. The playful whimsicality of “trying it out” like most people do a Raspberry Pi is absent, unless your idea of trying includes having the budget and time to tinker. This begs for someone to ship a “Getting Started” kit or pre-built enclosures with all the headache removed.
Maybe I’m betraying my developer/engineer psyche by appealing to a marketing “Do it for me” approach, but as more edge devices emerge, I believe onboarding time saved is customer interest earned.
Next Steps:
I’ll be evaluating the Jetson Nano as a friendly second computer. Benchmarking it, playing with it, and hopefully writing more about the experience! Be sure to follow me on here and other social outlets for updates!
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Gant Laborde is Chief Innovation Officer at Infinite Red, published author, adjunct professor, worldwide public speaker, and mad scientist in training. Clap/follow/tweet or visit him at a conference.
See more about Machine Learning here: FunMachineLearn Twitter and here https://infinite.red/machinelearning/
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