Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts • Hacker News Board

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#161

Post by Symmetry » Tue, Mar 19, 2019, 2:01 PM UTC

JustFinishedBSG wrote: post #113

trevyn wrote: post #87

Earlier quoted context omitted.

And you have to check a box that says "I agree that my model will only be used for applications that follow Google's AI Principles." Wow.

Which may or may not include automatically killing people via drones.

They're pretty clear that that isn't kosher:

Weapons or other technologies whose principal purpose or implementation is to cause or directly facilitate injury to people.

https://www.blog.google/technology/ai/ai-principles/

But drones that spy on people are ok as long as they aren't "violating internationally accepted norms" which sort of sounds like a blank check.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#162

Post by yissp » Tue, Mar 19, 2019, 2:02 PM UTC

oflannabhra wrote: post #146

supernova87a wrote: post #76

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 ye…

There was a guy that decided to make a toaster from scratch [0]. Literally from scratch: as in, mining and refining ore, etc. It was a bit of a stunt [1], but it definitely highlighted the advantage of scale and industry we typically take for granted. [0] - http://www.thetoasterproject.org/page2.htm [1] - https://gizmodo.com/one-mans-nearly-impossible-quest-to-make...

I get the point he's trying to make, but really, if I'm alone in the woods and wanted to toast some bread, I'm pretty sure I could just hold it over a fire for a few minutes.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#163

Post by scottlamb » Tue, Mar 19, 2019, 2:08 PM UTC

JudasGoat wrote: post #119

akhilcacharya wrote: post #12

$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?

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

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?)

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#164

Post by levesque » Tue, Mar 19, 2019, 2:08 PM UTC

joshvm wrote: post #114

AhtiK wrote: post #111

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.

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…

Yikes that is pricey. Camera costs more than the board, right.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#165

Post by johndough » Tue, Mar 19, 2019, 2:09 PM UTC

martinpw wrote: post #54

piinbinary wrote: post #48

> 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...

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.

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.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#166

Post by ashwinne » Tue, Mar 19, 2019, 2:15 PM UTC

ipsum2 wrote: post #30

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!

A more practical solution is to train your network on other beefy CPU/GPU/TPUs and convert+run that on the Nano using TensorRT. TensorRT supports import of models in Tensorflow (UFF) and ONNX formats.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#167

Post by samstave » Tue, Mar 19, 2019, 2:16 PM UTC

adrianN wrote: post #88

doomjunky wrote: post #86

Earlier quoted context omitted.

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

If you wish to make apple pie from scratch, you must first create the universe - Carl Sagan

I also love this showerthought from reddit:

All the materials for wverything made has existed on earth for billions of years, they just werent assembled in the right order yet.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#168

Post by ashwinne » Tue, Mar 19, 2019, 2:16 PM UTC

make3 wrote: post #42

ipsum2 wrote: post #30

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!

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.

That's correct, you can transfer any trained model to the Nano and run it there using the NVIDIA TensorRT library/toolchain.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#169

Post by scottlamb » Tue, Mar 19, 2019, 2:17 PM UTC

joshvm wrote: post #114

AhtiK wrote: post #111

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.

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…

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.

Re: Nvidia's $99 Jetson Nano Is an AI Computer for DIY Enthusiasts

#170

Post by riku_iki » Tue, Mar 19, 2019, 2:27 PM UTC

heavenlyblue wrote: post #156

samstave wrote: post #152

Earlier quoted context omitted.

I love both of these comments. I ised to talk to friends about “deep thinking” of what it took to make the sinple object in front of them, which they took for granted. My favorite example was a pen. Youre so abstracted from what it takes to actually make a simple pen. Imagine it was post-apocolypse, and youre the only person left on earth - and in addition to all other humans who have dissapeared, all pens/pencils ha…

Haven't China only a few years ago managed to produce an actual ballpoint pen? [1] [1] https://www.washingtonpost.com/news/worldviews/wp/2017/01/18...

Its probably not because they couldn't 'manage', it is likely because it was not economically interesting, they could import tips cheap enough and don't bother manufacturing their own.