Hackaday Links: August 27, 2017

Hulk Hands! Who remembers Hulk Hands? These were a toy originally released for the 2003 Hulk movie and were basically large foam clenched fists you could wear. Hulk Hands have been consistently been re-released for various Marvel films, but now there’s something better: it’s the stupidest tool ever. Two guys thought it would be fun and not dangerous at all to create cast iron Hulk Hands and use them as demolition and renovation equipment. This is being sold as a tool comparable to a sledgehammer or a wrecking bar.

New Pogs! We’re up to 0x0C. Is your collection complete?

[Peter] is building an airplane out of foam in his basement. He’s also doing it as a five or six-part series on his YouTube channel. Part two is now up. This update covers the tail surfaces, weighing and balancing the fuselage, and a general Q&A with YouTube comments.  Yes, [Peter] still has a GoFundMe up for a parachute, and it’s already about half funded. With any luck, he’ll have the $2600 for a parachute before he builds the rest of the plane. Another option is a ballistic parachute system — a parachute for the whole plane, like a Cirrus. That would be a bit more than $4000, so we’ll see how far the GoFundMe goes.

Hey, remember the Nvidia Jetson TX1? It’s a miniATX motherboard running a fast ARM core with a GPU housing 256 CUDA cores. It’s cool, and the new version — the TX2 — is designed for ‘machine learning at the edge’. They’re on sale now, for only $199.

Primitive Technology has another video out. This time, he’s improving his bow string blower into something that kinda, sorta resembles a modern forge. This time, the experiment was a success when it comes to pottery — he’s now able to fire clay at a much higher temperature, bringing him reasonably close to modern ceramics. At least, as close as you can get starting with the technology of a pointed stick. The experiment was marginally successful when it came to creating iron. He’s using iron-bearing bacteria (!) for his source of ore and was able to smelt millimeter-sized pellets of iron. This guy needs a source of copper or tin. Zinc is also surprisingly possible given his new found capabilities for ceramics.

Hackaday Links: May 14, 2017

Maker Faire Bay Area is next weekend, and you know what that means: we’re having a meetup on Saturday night. If you’re in the area, it’s highly recommended you attend. It’s a blinky bring-a-hack with booze. You can’t beat it. I heard the OPShark is showing up. All hail the OPShark. You’re gonna want to RSVP if you’re going k thx.

It only took twelve years, but [ladyada] finally got herself on the cover of Make.

Nvidia has the Jetson, an extremely powerful single board computer + GPU meant for machine learning, imagifying, and robotics applications. If you want to do fancy ML stuff with low power devices, I’d highly recommend you check the Jetson out. Of course, the Jetson is only the brains of any Machine Learning robot; you also need some muscle. To that end, Nvidia released the Isaac robotic simulator. It’s a simulator for standard bits of hardware like quadcopters, hovercrafts (?), robotic arms, and yes, selfie drones. What does this mean? Standardized hardware means someone is going to produce 3rd party hardware, and that’s awesome.

This is just an observation, but fidget spinners are just now hitting the mainstream. We didn’t know what they were for a year ago, and we don’t know now.

A Hebocon is a shitty robot battle. DorkbotPDX just had their first Hebocon and the results were… just about as shitty as you would expect. Since this is a shitty robot battle, a MakerBot made an appearance. This robot, SpitterBot, was designed to blow extruded filament all over its opponent. Did the MakerBot win? Yes, SpitterBot won the ‘Poorest Quality’ award.

Supplyframe, Hackaday’s parent company, hosts monthly-ish electronic get-togethers in the San Fransisco office. The focus of these meetups is to find someone cool who built something awesome and get them to talk about it. The March meetup featured [Pete Bevelacqua] who built a Vector Network Analyzer from scratch. The video is worth a watch.

Hands-On Nvidia Jetson TX2: Fast Processing for Embedded Devices

The review embargo is finally over and we can share what we found in the Nvidia Jetson TX2. It’s fast. It’s very fast. While the intended use for the TX2 may be a bit niche for someone building one-off prototypes, there’s a lot of promise here for some very interesting applications.

Last week, Nvidia announced the Jetson TX2, a high-performance single board computer designed to be the brains of self-driving cars, selfie-snapping drones, Alexa-like bots for the privacy-minded, and other applications that require a lot of processing on a significant power budget.

This is the follow-up to the Nvidia Jetson TX1. Since the release of the TX1, Nvidia has made some great strides. Now we have Pascal GPUs, and there’s never been a better time to buy a graphics card. Deep learning is a hot topic that every new CS grad wants to get into, and that means racks filled with GPUs and CUDA cores. The Jetson TX1 and TX2 are Nvidia’s strike at embedded deep learningor devices that need a lot of processing power without sucking batteries dry.

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Nvidia Announces Jetson TX2 High Performance Embedded Module

The last year has been great for Nvidia hardware. Nvidia released a graphics card using the Pascal architecture, 1080s are heating up server rooms the world over, and now Nvidia is making yet another move at high-performance, low-power computing. Today, Nvidia announced the Jetson TX2, a credit-card sized module that brings deep learning to the embedded world.

The Jetson TX2 is the follow up to the Jetson TX1. We took a look at it when it was released at the end of 2015, and the feelings were positive with a few caveats. The TX1 is still a very fast, very capable, very low power ARM device that runs Linux. It’s low power, too. The case Nvidia was trying to make for the TX1 wasn’t well communicated, though. This is ultimately a device you attach several cameras to and run OpenCV. This is a machine learning module. Now it appears Nvidia has the sales pitch for their embedded platform down.

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Project Zero Finds A Graphic Zero Day

After finding the infamous Heartbleed vulnerability along with a variety of other zero days, Google decided to form a full-time team dedicated to finding similar vulnerabilities. That team, dubbed Project Zero, just released a new vulnerability, and this one’s particularly graphic, consisting of a group of flaws in the Windows Nvidia Driver.

Most of the vulnerabilities found were due to poor programming techniques. From writing to user provided pointers blindly, to incorrect bounds checking, most vulnerabilities were due to simple mistakes that were quickly fixed by Nvidia. As the author put it, Nvidia’s “drivers contained a lot of code which probably shouldn’t be in the kernel, and most of the bugs discovered were very basic mistakes.”

When even our mice aren’t safe it may seem that a secure system is unattainable. However, there is light at the end of the tunnel. While the bugs found showed that Nvidia has a lot of work to do, their response to Google was “quick and positive.” Most bugs were fixed well under the deadline, and google reports that Nvidia has been finding some bugs on their own. It also appears that Nvidia is working on re-architecturing their kernel drivers for security. This isn’t the first time we’ve heard from Google’s Project Zero, and in all honesty, it probably won’t be last.

Make Any PC A Thousand Dollar Gaming Rig With Cloud Gaming

The best gaming platform is a cloud server with a $4,000 dollar graphics card you can rent when you need it.

[Larry] has  done this sort of thing before with Amazon’s EC2, but recently Microsoft has been offering a beta access to some of NVIDIA’s Tesla M60 graphics cards. As long as you have a fairly beefy connection that can support 30 Mbps of streaming data, you can play just about any imaginable game at 60fps on the ultimate settings.

It takes a bit of configuration magic and quite a few different utilities to get it all going, but in the end [Larry] is able to play Overwatch on max settings at a nice 60fps for $1.56 an hour. Considering that just buying the graphics card alone will set you back 2500 hours of play time, for the casual gamer, this is a great deal.

It’s interesting to see computers start to become a rentable resource. People have been attempting streaming computers for a while now, but this one is seriously impressive. With such a powerful graphics card you could use this for anything intensive, need a super high-powered video editing station for a day or two? A CAD station to make anyone jealous? Just pay a few dollars of cloud time and get to it!

The Coming Age of 3D Integrated Circuits

The pedagogical model of the integrated circuit goes something like this: take a silicone wafer, etch out a few wells, dope some of the silicon with phosphorous, mask some of the chip off, dope some more silicon with boron, and lay down some metal in between everything. That’s an extraordinarily basic model of how the modern semiconductor plant works, but it’s not terribly inaccurate. The conclusion anyone would make after learning this is that chips are inherently three-dimensional devices. But the layers are exceedingly small, and the overall thickness of the active layers of a chip are thinner than a human hair. A bit of study and thought and you’ll realize the structure of an integrated circuit really isn’t in three dimensions.

Recently, rumors and educated guesses coming from silicon insiders have pointed towards true three-dimensional chips as the future of the industry. These chips aren’t a few layers thick like the example above. Instead of just a few dozen layers, 100 or more layers of transistors will be crammed into a single piece of silicon. The reasons for this transition range from shortening the distance signals must travel, reducing resistance (and therefore heat), and optimizing performance and power in a single design.

The ideas that are influencing the current generation of three-dimensional chips aren’t new; these concepts have been around since the beginnings of the semiconductor industry. What is new is how these devices will eventually make it to market, the challenges currently being faced at Intel and other semiconductor companies, and what it will mean for a generation of chips several years down the road.

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