Nvidia announces Jetson Nano 2GB, a single board computer

Your assertion makes no sense. Let me explain why.

You've adopted a LTS release which was made public 2 years ago, was already a couple of years in the making, and is aimed at establishing a solid and reliable base system that can be targetted by the whole world with confidence.

And knowing that, your idea is to bolt on custom tooling that's not installed anywhere or by no one by default and make it your own infrastructure?

Unless you're planning on managing that part of the infrastructure for your customers to use, your race to catch up with the latest and greatest makes zero sense, and creates more problems than those you believe you're solving.

And no, it's not an infrastructure problem. It's a software engineering problem that's yours in the making. If you seek stability and reliability then you target stable and reliable platforms, such as the stuff distributed by default by LTS releases such as Ubuntu 18.04. because that's what they are used for.

But this is an SBC. It's likely to be configured to run its specific task forever. It should automatically log into the default user's account, and automatically start whatever software you want it to run. Software for it is likely to come from cross-compilers and to be sent over SSH.

It doesn't have hundreds of gigabytes of high-speed storage, the entire OS needs to be copied from a microSD card on every boot, so you don't want to have multiple toolchains on it.

I really like the DietPi [1] environment for these purposes (though it doesn't currently support have the Jetson Nano), the setup scripts make it easy to configure the OS for exactly the tools you want.

[1]: https://dietpi.com/

LTS makes sense as deployment platform. Push it to server and deploy own application. Make a demo like subject NVIDIA Jetson Nano SDK and forget about it.

There are better ways to help underpowered machines - use light desktop environment, block ads in browser, add RAM if possible. Kernel and base requirements has not changed much in a decade. About 120 MB with XOrg.

I'm not doing anything with mine that involves OpenCV, I didn't realise one of its flagship examples was also messed up in the box.

Oh! And I just dug out my script to rebuild if I need to. I forgot a few more annoyances:

* tensorflow isn't installed by default, and it's not obvious how to do the install because you have to specify NV's repo: pip3 install --pre --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v44 tensorflow

* openai gym won't work unless you specify archaic version 0.15.3, there's a buggy interaction between it and NVidia's X11.

* lots of packages need installing that should really have come by default, or were broken by default [eg numpy]

If you don't need CUDA, you can outright use regular Fedora, which uses nouveau. (no reclocking issues or such on Tegra)

Sure you can make those things run natively but people using them are used to Python, lot of code is written in Python for it and there is little to no performance penalty of running the code in Python (everything perf. critical is running natively anyway, Python is only used to "glue" those bits seamlessly together).

And once you have RAM in gigabytes even the extra memory overhead of Python becomes a moot point.

(there's also the NV prebuilts of an older version of the patchset at https://docs.nvidia.com/jetson/l4t/index.html#page/Tegra%252... )

2.) Boot is only possible from microSD card. USB is not supported.

3.) Build BareBox with https://www.barebox.org/doc/latest/boards/rockchip.html

Use `rk-splitboot` to split FlashData from the original boot loader, other option doesn't work. Build it, it will create barebox-radxa-rock.img. It's .img, not the .bin.

Write an SD card as in the instruction.

4.) Follow these instructions, but use the generic image.

https://archlinuxarm.org/platforms/armv7/amlogic/odroid-c1

http://os.archlinuxarm.org/os/ArchLinuxARM-armv7-latest.tar....

5.) Build kernel as in this tutorial, ignore the `dts` stuff. The `dts` comes with the kernel sources.

https://wiki.radxa.com/Rock/Linux_Mainline

https://github.com/torvalds/linux/blob/master/arch/arm/boot/...

6.) Copy the zImage, rk3188-radxarock.dts to the /boot and plug in the UART.

7.) sudo picocom /dev/ttyUSB1 -b 115200 -e w

8.) Boot in the bootloader and execute the following commands:

global.bootm.appendroot=true

global.bootm.image=/mnt/mshc1.0/boot/zImage

global.bootm.oftree=/mnt/mshc1.0/boot/dtbs/rk3188-radxarock.dtb

bootm

9.) If it boots, you can make it permanent by following the BareBox docs.

Edit: Seems like people voted up the Hackaday article and not the medium article. So you've in effect negated everyone's votes.

How do I know which comments are talking about which article?

It's pretty neat stuff to think about DSP on hundreds of MHz of bandwidth being something that you can do in software these days. I remember when that was firmly in the realm of "don't bother unless you want to design a custom ASIC" and now it's starting to become even hobbyist-accessible.

Compared to him testing on a Raspberry Pi 4: https://www.youtube.com/watch?v=l4TyYU9Xhcs

(note both those videos are a old so results could be different now)

The video is a year old, but I imagine there would be less bugs now. With this cheaper board coming out, there might be a bit more of development activity.

This Jetson really isn't a platform to run emulated games - for that there are much better boards, with more RAM. Which is a lot more important issue. You can't do miracles with 2GB of RAM.

Jetson is made for computer vision, neural networks and signal processing, where the GPU isn't used as a GPU but as a massively parallel co-processor to crunch through a lot of data at once.

No, not even close. It's embedded systems with GPU acceleration, mostly for machine learning.

As someone who has tried to run a desktop environment on various Pi-like devices for years, with every generation being "the one that will replace your PC" I just laugh.

The modern web is nearly unusable with less than 4 GB of RAM and it's really easy to push beyond that. I personally would not recommend that anyone try to use anything with less than 8 GB of RAM as a general purpose desktop computer anymore.

You can do it, sure, but there will be significant compromises and limitations along the way. A secondhand x86 PC with 8+ GB of RAM is almost always a better choice for general purpose desktop use. Leave the "hacker boards" for roles that benefit more from their compact size, low power consumption, and/or specialty I/O capabilities.

I haven't tried the Pi 8GB, that should at least solve the RAM problem, but the lack of native high-speed storage still likely impacts usability. Here's hoping the major Pi-likes follow suit to offer variants with more memory soon.

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And of course as noted by other comments, another major reason to think of these things more as appliances is the generally spotty support for updating kernels and the like that is unfortunately standard in the ARM world. That entire side of the industry is infected with NDA culture and has no interest in curing it.

Only the MAIX platform has a price advantage over this now, and the software is much less mature.

The total package ends up significantly more expensive than the "list price" of an RPi itself, and it ends up not making much more sense than buying a used x230 or something off of eBay for <$200.

Edit: But no WiFi is annoying.