NVIDIA's $99 Jetson Nano is an AI Computer for DIY Enthusiasts (engadget.com)
Sophisticated AI generally isn't an option for homebrew devices when the mini computers can rarely handle much more than the basics. NVIDIA thinks it can do better -- it's unveiling an entry-level AI computer, the Jetson Nano, that's aimed at "developers, makers and enthusiasts." From a report: NVIDIA claims that the Nano's 128-core Maxwell-based GPU and quad-core ARM A57 processor can deliver 472 gigaflops of processing power for neural networks, high-res sensors and other robotics features while still consuming a miserly 5W. On the surface, at least, it could hit the sweet spot if you're looking to build your own robot or smart speaker. The kit can run Linux out of the box, and supports a raft of AI frameworks (including, of course, NVIDIA's own). It comes equipped with 4GB of RAM, gigabit Ethernet and the I/O you'd need for cameras and other attachments.
No thanks, I don't buy from companies that cheat benchmarks, buy reviews and cripple games with shady developer programs. I'll buy anything else instead of Nvidia. They are scumbags.
Slow down, cowboy!
You have to type JETSON! to get it to do anything.
Sophisticated AI generally isn't an option for homebrew devices when the mini computers can rarely handle much more than the basics
That's a marketing failure: many people think cheap toys like the raspberry pi are the only game in town.
You can get small form factor FPGA boards in the $100-200 range.
Nvidia claims that the realtime raytracing tech in its uber-expensive RTX 20xx cards "took 10 years to develop". Hmm. A full 10 years to turn decades old raytracing techniques into working hardware circuitry! Either Nvidia's hardware engineers have an IQ in the double digits and take ages to implement old techniques in hardware. Or good old Nvidia is one of those lovely tech companies that _could_ have given us exactly what we wanted 6 to 7 years ago, but simply opted to sell old tech for another few years instead - it was more profitable that way, you see? GPU buyers are idiots - Nvidia gives its architecture a radical name change every few years (Maxwell, Turing, bla bla bla), unlocks a bit more of the processing potential the architecture had 5 years ago, and boasts - GASP! - that the "new" architecture is now 20% faster. I wouldn't be surprised if Nvidia already has RTX 40xx or even RTX 50xx GPUs running in its laboratory. When will we get those babies? WHEN NVIDIA FEELS LIKE IT OF COURSE. LMAO!
Why did the chicken cross the road? Because Elon Musk put an AI chip in its head.
Today is the first day of NVIDIA's GPU Technology Conference in Silicon Valley. It's always accompanied with new launches.
https://www.nvidia.com/en-us/gtc/
4GB puts this into the category where it's actually useful for stuff like web browsing. Sadly, the link to the item from TFA is 404, but it looks like it's actually got enough ports on it to be useful for doing stuff without needing a hub, too. Forget building robots with it, you can build kiosks. Do they have an Android build for it?
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
It's good that this post linked back to the original Engadget posting, but when you do something like this, you should quote it. The title and first two sentences are also word for word from the Engadget article. Not cool. Not cool at all.
My Slashdot account is old enough to drink...
mini computers can rarely handle much more than the basics
Minicomputer.
Obviously these people have no clue what is in a so-called "smart speaker".
but nvidias site says even AI cant find the page. and not a single retail source has a jetson nano, let along one for $99, so i just wonder where the price is coming, id buy one for $99.
I just want to know when a mining app for this thing will be available. I don't want to mine with it - I want to buy a hundred of them then sell them on ebay for 10x more than I paid, like I with nVidia video cards last year (well, 2x as much anyway).
I do not belong to the church of the lowercase 'i'
https://www.youtube.com/watch?...
This one doesn't even have the 3 laws.
Soon people will be tinkering with personal-sized AI like they started to do with Arduino a few years back, and 3D printing more recently. The trend here is obvious, but we cannot predict what tinkers will come up with once they get their hands on these things in a big way.
AI researchers fret about the "containment problem", meaning how do you prevent an autonomous intelligence from breaking out of your lab and doing whatever it wants to, including enhancing itself exponentially. So there is talk about creating process and protocols to contain AI similar to what you might have regarding biological containment for a microbiology lab working with dangerous pathogens. But those rules aren't going to work when anyone wants to can build a reasonably powerful AI machine using off-the-shelf components, and/or using cloud-based resources.
I don't expect this is going to work out the way we think it is.
=^..^= all your rodent are belong to us
Is this Maxwell v1 or v2? And in either case, does it used signed GPU firmware, or is it like the Kepler/Maxwell V1 and can run unsigned firmware controlled by the user?
If it can, that makes this my new go-to board. The nouveau GPU drivers for Kepler/Maxwell are far and away better than the alternatives on ARM, and while 500GFLOP is slightly less than my GT730, it is more than enough to put this ARM board at the top of its stack. Furthermore the ARM A53 cores are in-order and spectre immune, making this a perfect board from a security standpoint, if a little slower than alternatives.
30 Years Ago:
Motorola's new 16-bit microcontroller has a whopping 16K of RAM, and 8 GPIO! You can use it to build robots, or home automation systems, or low-end general purpose computers...
Today:
Our new quad-core CPU, 128-core GPU is great if you want to build a speaker!
My Other Computer Is A Data General Nova III.
"There is no GPU conspiracy from Nvidia..." Lol, you couldn't be dumber. https://news.bitstarz.com/nvidia-facing-barrage-of-lawsuits-for-alleged-securities-fraud
https://www.digitaltrends.com/computing/nvidia-rtx-graphics-cards-ai/
https://www.sfgate.com/g00/business/article/Nvidia-analyst-pleads-guilty-to-fraud-conspiracy-2370288.php
https://www.extremetech.com/gaming/278454-nvidia-rtx-2080-and-rtx-2080-ti-review-you-cant-polish-a-turing
https://venturebeat.com/2018/09/19/nvidia-rtx-2080-ti-review/
...or a secondary computer. Unlike the Raspberry Pi, this apparently can support 4k60 output as well as dual-display. It would be handy for a lot of things.
https://www.electronicshub.org/breadboard-kits-beginners/
How can I make a Beowulf cluster out of these?
This is cool shit for what it is.
What else has the ability to encode 4k h.265 in realtime /w comparable GPU at a price anywhere near what this thing costs?
Having said that I do a lot of h.265 encoding and wouldn't touch the NVidia GPU encoders with a 39 and a half foot pole. They suck ass.
Still at $100 the deal breaker will be what kernel and hardware support look like for this thing.
Personally also looking forward to the N2.
https://www.hardkernel.com/blo...
of the cryptocurrency mining business, NVIDIA shifts to Statistical Modelling^W^W Algorithmic Inference in order to avoid bankruptcy.
This will give them a bit of time. I wonder what the next "big thing" will be once the bottom falls out of the Statistical Modelling^W^W Algorithmic Inference market?
The heck with AI. Will Kodi and Plex be ported to it?
and quality before promising anything. Just say'n.
look at that heat sink. what do you expect for battery life?
An rpi 3b+ draws a max of 5w, and your heatsink is pretty optional. I suspect this is drawing a bit more than 5w.
And the real news is when a normal person can stably run stuff on it. I've been watching this market for a few years, and the difference between the Raspberry Pi and the Raspberry-Pi-Killers is that with an rpi you can be up an running in under a half hour depending on how fast your Internet can download updates, and the result is pokey but stable (if you don't stint on the power supply). With most of the other boards, in a half hour you haven't even found the right page for burning your OS to an SD card, and once you've finally gotten to a login screen, you get to spend the next week trying to figure out why it crashes every time you visit YouTube or CNN or probe a GPIO pin. The next six months is spent listening to how the next software update will fix your problem, and then they make a hardware rev and throw out all their existing progress.
pure shit of bull lies marketing slashad crap. Go try buy one...
Maybe it has a high operating temperature range, it's also claimed that 5W is for the chip not the board.
They have this
https://developer.nvidia.com/embedded/dlc/jetson-nano-dev-kit-user-guide
https://developer.nvidia.com/embedded/linux-tegra
and as a PC vendor, formerly PC chipsets they should now to get this working.
Now, Intel is a much bigger vendor and they did a horrible to non existent job at supporting Intel Quark boards, Edison etc. Like, for company politics reasons they had to get this product out the door just so they can pretend Intel x86 embedded boards exist. IIRC they've now pulled the plug on it. They use the Quark processor in chipsets for the Intel ME engine I think.
So, I can understand you. A big and reputable vendor can leave you in the cold!
But with nvidia, they have incentive for this to work. They captured most of the GPGPU market on desktop and server with their CUDA and stuff. Engineer or researcher or programmer? Buy a geforce, tesla or quadro and it just works - even or especially on linux. So they're trying to be a Microsoft of computer vision and neural networks etc. This means they want this Jetson Nano thing to be easy to work with so you get hooked up on it and maybe become a customer for other Jetson Nanos or for the bigger, high end Xavier as well as probably more of the same on the server side or the goddamn cloud.