
Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts - plasticchris
https://www.engadget.com/2019/03/18/nvidia-jetson-nano-ai-computer/
======
supernova87a
I am continually amazed that we're able to buy better and cheaper processors
that no one could have dreamed about at such power/cost 50 years ago.

I estimate it would take me and you maybe 1 year to learn how to build /
assemble most things you find in your house that cost $1000 in a store -- a
couch, a rug, even a simple kitchen appliance (the dumb kind).

But a CPU / computer? I could not invent that given 10,000 years, and yet you
can buy one for $100. Amazing.

~~~
adrianN
You should read "From NAND to Tetris". You could totally build a CPU yourself
after a year of study. Not something that can compete with a modern
microprocessor of course, but then again you probably couldn't build a
compressor for a fridge with the same quality as a factory either.

~~~
doomjunky
_Look at this lead pencil. There 's not a single person in the world who could
make this pencil. [0]_

[0]: Milton Friedman
[https://www.youtube.com/watch?v=R5Gppi-O3a8](https://www.youtube.com/watch?v=R5Gppi-O3a8)

~~~
agumonkey
Sorry to differ, I think this is twisted by an era where liberal market was
held as god like status.

Take the rubber and metal out because for now. To draw a dark line on a
surface, you take the first bit of wood you find, grind it into a point and
burn it. You have a pencil.

I really believe that the free market centuries made people believe it was the
only or most efficient way to get an object done, just like people thought
java ee was the only way to make a web application in early 2000s.

~~~
todd8
You’ve moved the goal posts.

It’s not that the construction of some thing, anything, that can be used to
write with is difficult. As you point out a piece of charcoal isn’t hard to
make.

Milton Friedman’s point is that even something as simple and inexpensive as a
pencil involves people all over the world working together to create it. Some
mine graphite, some run ships to move the graphite, some manufacture paint,
some grow rubber trees, etc. All of this activity, coordinated and made
efficient by the market is behind even a simple thing like a pencil.

~~~
agumonkey
I agree on goalpost but still differ on Friedman's point. Culture shifts into
thinking you need objects to the point of making you forget what you wanted in
the first place. Friedman wants to marvel at the thought of his beloved
market.

~~~
EForEndeavour
Friedman does wax lyrical about his beloved market toward the end of that
video, but the main point I drew from his quote about the pencil is that it's
absolutely mind-blowing to stop and contemplate the incredible cooperation and
pre-existing systems required to construct so many of the mundane, dirt-cheap
objects of the modern world.

The fact that someone could eschew mass-produced lead pencils in favour of a
self-made writing implement doesn't diminish the fact that it's practically
impossible for any one individual on the planet to ever actually build a
pencil you can buy for the equivalent of a few seconds to minutes of labour.
That pencil, and so many other mundane items like it, are artifacts beyond the
crafting capabilities of any one human.

~~~
agumonkey
After viewing primitive technology and crafting videos I'm convinced of the
opposite. Culture makes you think that only mass market can do that.

~~~
EForEndeavour
I feel that again misses the point. Sure, it's perfectly possible for a
resourceful and knowledgable human to hand-engineer various tools from the
environment. But to make something very much like an ordinary pencil made of
wood, graphite, rubber, metal, and paint would be a monumental task, far
beyond the cost of a pencil in our established society.

The fact is that globalization and industrialization has democratized the
construction of literal artifacts. Consider the single-use plastic bottle,
with a precisely machined screw neck and matching lid. It's lightweight,
transparent, and will last for years. It would be exceedingly difficult to
find and process the raw material to craft such an artifact from scratch, yet
millions of them per day are used once and discarded.

Same goes for most office supplies, now that I think of it. And we haven't
even touched integrated circuits yet.

~~~
agumonkey
I kinda see, the value is in efficiency of delegation but IMO there are
drawbacks that this 'efficient' perspective hides, namely people believe you
can't do anything without the market.

~~~
WanderPanda
Yep because history has proven that believe to be correct.

------
piinbinary
> 472 gigaflops

Whenever I hear a number of gigaflops or terraflops, I like to look up the
history of super computers [0]. This $99 computer is faster (on paper) than
the world's fastest supercomputer in 1996, or a bit over 20 years ago. That's
pretty cool.

[0]
[https://en.wikipedia.org/wiki/History_of_supercomputing#Mass...](https://en.wikipedia.org/wiki/History_of_supercomputing#Massive_processing:_the_1990s)

~~~
martinpw
Not quite. This is FP16, supercomputers are typically benchmarked using double
precision flops, so FP64. So roll in a factor of ~4 there, or a couple of
years.

~~~
johndough
FP16 has 11 bit mantiassa, whereas FP64 has 53 bits. Integer multiplication
scales quadratically with the number of bits, so a factor of ~23 might be more
accurate.

------
ipsum2
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!

~~~
make3
there is no reason to train on that thing (except for zero shot classification
demos). any cheap/lower end Nvidia gpu would do a much better job, and you
would then transfer the model to the embedded thing.

~~~
outlace
Would it do better than a CPU for training? I do my dev on a MacBook Air and
use AWS for training, if this cheap gpu will be a few times faster than my Air
CPU than I’d be willing to get it. I usually work with medium sized
models/data, too big for CPU but don’t need a multi gpu cluster.

~~~
make3
Google colab gpu instances are free and likely faster than the jetson (and
definitely faster then typical laptop or desktop cpu only training), just save
the models to your gdrive

[https://colab.research.google.com/notebooks/welcome.ipynb#re...](https://colab.research.google.com/notebooks/welcome.ipynb#recent=true)

------
akhilcacharya
$99 seems like a pretty good deal, am I missing anything? 4 gigs of RAM and
_reasonable_ eMMC + PCI expansion could allow it to be a cheap casual use
workstation, right?

How does it stack up with the RK3399 in the RockPro64? I'm assuming the GPU
and software support is better?

~~~
JudasGoat
From what I read you would have to purchase the $129 board for EMMC support.
The $99 board was micro SD only.

~~~
scottlamb
What $129 board? For the Jetson Nano, I see only the $99 module or and $99 dev
board; neither mention eMMC. Do you mean the RockPro64? I see a $79.99 board
that supports eMMC (but isn't in the same league for AI tasks as the Jetson
Nano, I think?)

------
nakedrobot2
This Jetson Nano is a crippled TX1, nothing more.

We have been building cameras with the TX1 and TX2 for 3 years now. _We have
seen things you people wouldn 't believe_ ;-)) Now, can we cut through the
hype a bit? Ready? Get your rant mask on.

The Tegra (aka Jetson) chipsets are quite buggy at a silicon level. If you
find a hardware bug, nVidia will not acknowledge it, or help you (unless
you're Nintendo for example, buying millions of pieces, of course)

The tx1, tx2, etc. are a nested maze of blackboxes, which you do not and will
not have access to. For example, the camera ISP is accessible by THREE
companies in _the whole world_. If you want to utilize the ISP, you have to go
through them. Will those companies help you? Yes, for a very large fee. Why
should they make the fee lower? They have almost no competition. OK, so you
manage to get a sensor driver from one of those three companies. The sensor
driver is, probably, also very buggy and poorly written. Maybe you can rewrite
it yourself. The company who wrote the original one might help you anyway with
ISP tuning (again for a fee).

nVidia doesn't give a damn about hobbyists or smaller companies. They will
willingly mislead you with specs that are outright false and throw your
company under a bus without the slightest second thought. We have seen this
repeatedly with nVidia - their corporate culture really tends toward arrogant
douchebaggery, second perhaps only to GoPro.

So, after all that, it seems that nVidia has produced too much TX1 silicon, so
they've crippled it, and put it in a package that they're selling for $99.

I'm not really excited about it :-)

------
yolobey
Hope 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.

~~~
dheera
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 camera
connector, but Raspberry Pi NoIR cameras don't have TX2 drivers, and there are
hardly any other cameras that ship with that connector.

Seriously, NVIDIA: Please sell a TX2 devkit that has _six_ non-weird 2-lane
CSI connectors and some IMX290 or AR0521 or any other commonly-used robotics
sensors for $100 each that plug in and "just work". It would make a lot of
people happy to have something to at least start with, and pave the way for
third party options to follow the same form factor, connectors, pinouts, board
sizes, and so forth.

~~~
remyM
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 :(

~~~
dheera
Cool. Well hopefully some third parties will now create cameras all in the
same form factor with the same pinout so that the choice of carrier board and
camera can be independently made.

------
syntaxing
I 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.

~~~
arbie
Wouldn't the Shield TV be a better fit in the same price range? It does Plex
transcoding.

~~~
syntaxing
I was tempted during the $100 sale late last year, but I was worried about it
becoming obsolete (I know its crazy, since its been out for less than 5
years). I like the idea of having my own Linux server though. That way I can
set up my own services as needed depending on my usage (I normally tack on a
samba server on top of my plex server).

------
mntmn
Anyone know about the binary blob / firmware situation on this one? Will it
run mainline Linux?

~~~
aninteger
It's Nvidia, so you have to decide whether you want to give ANY money at all
to a company that ships binary blobs or not (whether or not this individual
product uses them). I'm sure there are product teams at Nvidia that ship
"open" products but unfortunately there doesn't seem to be a way to support
the good parts of a corporation while neglecting the parts that ship closed
binary blobs.

~~~
duado
Which hardware companies ship zero binary blobs?

------
01100011
I 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.

~~~
mastax
This has an M.2 Key E connector which has PCIe ×2, USB 2.0, I2C, SDIO, UART
and PCM. Hypothetically an M.2 PCIe drive could work with a Key M to Key E
adapter, but I couldn't find one in a cursory search.

~~~
bb88
Unfortunately it looks like you lose wireless connectivity then.

~~~
TaylorAlexander
If USB is available it may be acceptable to use USB for wifi.

------
epynonymous
the 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 usb, there’s also an additional usb looking port on top of hdmi.

storage seems the same as rpi, except that it’s built in 16G mmc flash whereas
rpi you need to separately plugin a microsd card.

overall this has potential if you need to do more gpu intensive work, i like
the form factor.

[https://www.nvidia.com/en-us/autonomous-machines/embedded-
sy...](https://www.nvidia.com/en-us/autonomous-machines/embedded-
systems/jetson-nano/?nvid=nv-int-
mn-78464&cjevent=9065593749df11e9837400450a180512)

~~~
thisacctforreal
It would be good to know what bus the Ethernet talks on; with the Pi it's
shared over the USB bus and it hampers the performance considerably.

For this reason I went with an Odroid for a small network storage system.

Edit: it has PCIe so it shouldn't be a problem.

~~~
im_down_w_otp
The on-board Ethernet on the TX1 is USB3 integrated, IIRC. The system having
PCIe is not necessarily a sign of how it gets used or what is using it,
unfortunately.

------
voycey
We are using Rapids.Ai and unfortunately this requires Pascal as a minimum
Architecture - unfortunate as we have been looking at a cheap method to create
proof of concepts for code we would eventually push to the cloud
(functionality rather than speed for example) - this would have been ideal!

------
dmos62
I use a pretty old computer for prototyping ML models. Could I use something
like this to develop with, saving on buying an expensive laptop or renting a
VPS?

------
ortusdux
The product link in the article leads to an ironic 404 message: "Even AI can't
find this page!"

[https://www.nvidia.com/en-us/autonomous-machines/embedded-
sy...](https://www.nvidia.com/en-us/autonomous-machines/embedded-
systems/jetson-nano/?nvid=nv-int-mn-78464)

~~~
01100011
[https://developer.nvidia.com/embedded/buy/jetson-nano-
devkit](https://developer.nvidia.com/embedded/buy/jetson-nano-devkit)

[https://devblogs.nvidia.com/jetson-nano-ai-
computing/](https://devblogs.nvidia.com/jetson-nano-ai-computing/)

------
JustFinishedBSG
99$

With 50$ shipping to France.

What a great deal /s

Or straight up 130€ (150$) from Nvidia France. Not quite 99$.

~~~
nmstoker
Precisely. I would love to see this succeed but it's not $99 even in the US -
with Arrow, there's tax taking it up $120 and then the UK shipping cost is
about the same as you found for France ($42-44 depending on option).

Feels like this could have been better managed - especially with the 16 week
delivery time! Unlike the Coral which was announced, ordered and in my hands
within three days!

------
sigmaprimus
I like the barrel jack for power on the development kit version, I wonder what
sort of power requirements it has as that seems to be an issue with the RPiS.
On a side note that is a very impressive heatsink too!

~~~
godelski
What problems are you facing on the pi? The USB power to me is a big win. I
already have a ton of cables sitting around.

~~~
sigmaprimus
My biggest problem is more of a mechanical issue, the darn micro USB connector
is difficult to align and after a while of plugging in and out(especially due
to being difficult to quickly see if it's right side up) it becomes loose. As
far as power itself, I have only run into catastrophic problems when
attempting to use a hand held solar powered battery backup bank and when I
tried to use a car cigarette lighter USB adapter. That being said it is my
understanding that RPIS use a special power management scheme that actually
throttles the processor cycles without any indicator, including the lightning
bolt so maybe that laggyness could be power issues too? (Edit: There might be
an iindicator of the low power throttle in the kernel log)

~~~
lunchables
I actually bought some small micro usb power dongles with switches on them. So
you only plug it into the pi once, then plug the dongle into the actual power
source. Also means you can turn it on/off without being forced to pull the
plug.

Something like this: [https://smile.amazon.com/LoveRPi-MicroUSB-Switch-
Raspberry-F...](https://smile.amazon.com/LoveRPi-MicroUSB-Switch-Raspberry-
Female/dp/B018BFWLRU)

~~~
godelski
I just unplug it from the wall...

~~~
lunchables
Unfortunately for me a lot of times that requires digging behind a piece of
furniture :)

------
helen___keller
It's interesting how we can see in real time the commodification of ML
hardware. From my understanding, prior to Tensorflow, most serious ML projects
involved clusters of NVIDIA GPUs, and production ML software was tightly
coupled to CUDA. Google shifted the software landscape by pushing a multi-
target ML platform.

Now, all of a sudden, NVIDIA is under intense pressure to keep up with new
compute hardware looking to eat their lunch in the AI sector.

------
dvt
Just 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?

~~~
abakker
\- Smart camera for a doorbell? Train it to detect a person or a package?

\- Smart camera to detect your posture, and message you when you slouch for
more than 3 minutes?

\- buy tons and tons of sensors and just hook them all up to see if you can
detect anything at all? VOC sensors, heat, light, noise, see if any of these
things can diagnose comfort, sleep, health issues in your life?

~~~
neop1x
for all of that you can use $30 raspberry pi... for some of that you can use
$5 raspberry zero and get wifi on board

------
FreedomToCreate
Now I just need something to DIY with it. Any ideas?

~~~
make3
self driving small car, nerf turret that shoots anyone who is not you,
following drone, cat stalking drone, cat stalking self driving "rc" car, auto
bird identification camera in your backyard "this is a bird of type X" with
voice or screen with instance detection/segmentation

~~~
yayr
what gear would one best use to make those gadgets self-recharging?

one the non-charging idea side there would be the AI network traffic analyzer
(just requires another 1G connector via USB)

~~~
shiftpgdn
Induction charging pad + receiver.

------
eismcc
Prime candidate to add to my [http://parallac.org](http://parallac.org)
collection!

------
AhtiK
This begs the question, what are the best price-quality ratio cameras
compatible with this board?

As I understand, both Jetson Nano and Google Edge TPU/Coral Dev Board would
work with the same set of cameras, having the MIPI-CSI2 interface. Is it?

Many ML inference applications are using a camera, yet it's close to
impossible to find something very affordable.

~~~
joshvm
Depends what you want. The cheapest decent machine vision cameras that I know
of are Basler's dart range, but they're still $100-300. Entry level is the
DA2500-14uc (5MP 14fps).

You can also try places like Leopard Imaging or eCon systems. Even then, most
of eCon's stuff is $150+ and their APIs feel a bit hacky.

This is all USB3. Unless you really need a mipi solution (you may need an
adaptor board to match the), USB is fine. Even a webcam might be good enough.

~~~
scottlamb
What qualities does a decent machine vision camera have, besides price? size?
resolution? lens/sensor quality? infrared? frame rate? latency? ruggedness?

I have a bunch of inexpensive IP security cameras. I imagine the latency
(~second) would be prohibitive for machine vision camera applications, where
you probably are making some control decision immediately? I'm curious how
else they'd compare.

------
frabbit
Are the drivers for the graphics, wifi, etc all FOSS? Or is it the usual
disappointingly difficult to maintain Nvidia mess?

~~~
Narishma
This is Nvidia, what do you think?

------
walrus01
I wonder how the emmc flash holds up over many writes, and what form of wear
leveling it uses compared to a consumer class m2 interface, sata3 SSD. One of
the main problems with rpi is the microsd media, even "industrial" cards
cannot tolerate anywhere near the writes that a $50 SSD can take.

------
tuxxy
No dedicated memory for the GPU?

~~~
newen
Yeah, I couldn't find any information on it. TX2 has 8GB of GPU RAM. I don't
even understand how it will work on anything reasonable without any GPU RAM..

~~~
aseipp
Tegra systems use a unified memory controller for both GPU and CPU RAM. This
means the GPU can access essentially all system memory as video memory and
there is no meaningful distinction between the two. This has always been the
case -- similarly, the Xavier Jetson, and the TX2 do not have split GPU/CPU
RAM either. They all have unified controllers, so the "8GB of GPU RAM" for the
TX2 you mention is also "8GB of CPU RAM".

This thing essentially looks like a chopped down version of the TX1,
considering the specs are all pretty much identical. These have 4GB of memory.

Most of the time you'll be running a stripped down headless Linux 4 Tegra on
this device, so something like 80% of your memory can otherwise be dedicated
entirely to your application (both GPU and non-GPU compute portions) anyway.

------
intrasight
Truly amazing. I remember when my university purchased a CM2 for about $5
million. Was about 30 gflops.

[http://www.tamikothiel.com/cm/](http://www.tamikothiel.com/cm/)

------
billconan
I hope to put it into a pi-top

[https://accounts.pi-top.com/products/pi-top/](https://accounts.pi-
top.com/products/pi-top/)

not sure if this fits

~~~
dvhh
I kind of miss the nvidia transformer line of android tablet, I am still
running a TF101 as a light client.

~~~
morganvachon
I have a TF700T collecting dust on my workbench. It was a great machine for
its time though! Probably the best looking display available on an Android
tablet at its release, and amazing battery life.

------
amelius
How fast can it run the Inception model on a single image?

------
watersb
Fewer headphone jacks than the Creative Nomad. Lame.

------
neop1x
Sold out or pre-order with $50 shipping. But it's definitely a nice piece of
HW! Can't wait what clever people make with it.

------
fulafel
Is there hope for Nouveau on these embedded chips?

~~~
fulafel
To answer my own question, there is active work on this chip family, eg
[https://www.phoronix.com/scan.php?page=news_item&px=Tegra-X2...](https://www.phoronix.com/scan.php?page=news_item&px=Tegra-X2-Xavier-
HDMI-Audio)

So there's hope that it might be usable for f/oss enthusiasts at some point.

------
gigatexal
I’m going to get one as a dumb terminal for SSH and a random browser or two.
It could make for a really compelling HTPc device too

------
swebs
From Nvidia's site:

>NVIDIA Jetson Nano modules will be available from distributors worldwide
starting June 2019.

~~~
jki275
that's odd. The one I ordered said it was shipping at the end of march.

------
carlmcqueen
All this AI stuff is nice, but the important questions are what are the
benchmarks of a retropie?

------
mv4
I really really need to get one of these now. Is anyone at GTC right now?

------
pjmlp
Actual link for the product.

[https://www.nvidia.com/en-us/autonomous-machines/embedded-
sy...](https://www.nvidia.com/en-us/autonomous-machines/embedded-
systems/jetson-nano/)

------
goda90
Could this be used for an offline voice assistant?

~~~
TaylorAlexander
Probably. I've recently compiled Mozilla's Deepspeech for the Nvidia TX1 and
it was a painful process. They don't have precompiled binaries for ARM64 +
CUDA for Deepspeech, so you have to compile Bazel (v18!), Tensorflow from
Mozilla's repo, V1.12, and then deepspeech. If I am remembering correctly, it
ran pretty slowly on the TX1. I don't know how well it would run on this new
device, or if a lighter weight model is available somewhere.

------
Jemm
For what are people going to use the Jetson Nano.

~~~
swebs
Robotics/drones seems like the obvious market.

------
platz
why would you want to train on the device itself?

~~~
outlace
In some applications you may want to run a continual learning algorithm so it
will continually train on new data as well as make inferences.

~~~
WanderPanda
I always wonder how one would guarantee stability / convergence when learning
in the field. Sounds great, but how can this be pulled off in a reliable way?
Just dragging down the learning rate does not suffice in my oppinion, as for
effective training you should be at the boundary of stability and greedy
updates from my experience

------
bogle
So, engadget is yet another website that hasn't read the GDPR guidelines
properly. I cannot be bothered to click through all of their nonsense to read
their clickbait content.

------
aussieguy1234
Heres another potential use - Crypto mining

~~~
mdorazio
Not really. It's 472 gigaflops for $100 and not particularly energy efficient.
It's useless for bitcoin by a large margin and for Ethereum & co. you can get
a used GTX 1070 with 6.5 teraflops of compute for about $250.

