People have been working metal for so long that the list of tips and tricks is now nearly infinite. So it’s always a joy to pick up a new trick, especially one as simple as putting a hardened edge on mild steel using a drill bit as a filler rod.
This tip comes to us by way of [Jody], aka “The Weldmonger” on YouTube. Subscribing to his channel is a sure way to keep your welding ego in check; you may be good, but [Jody] is better, and he’s willing to share as much of his experience in video format as possible. For this tip, he starts with a cheap chipping hammer, the universal welder’s tool that helps remove the glass-like slag that forms during shielded-metal arc welding, or what’s commonly known as stick welding. The mild steel of the hammer makes it hard to keep an edge, so [Jody] pulled out his TIG welder and laid down a bead on the cutting edge using an old drill bit as a fill rod. The video below shows the process in all its simplicity.
The tool steel of the drill bit is far harder than the mild steel of the hammer, but still soft enough to take an edge, and the resulting tool is much improved. We’ve seen something similar to this before, when hard-facing filler rod was built up on the edge of a mild steel slug to make a cutter for internal weld seams. We liked that hack, but knowing the same thing can be done with something we’ve all likely got in abundance in the shop is a neat trick. Thanks, [Jody]!
Continue reading “Put A Hardened Edge On Mild Steel With Just A Drill Bit. Sort Of.”
Back in January when we announced the Train All the Things contest, we weren’t sure what kind of entries we’d see. Machine learning is a huge and rapidly evolving field, after all, and the traditional barriers that computationally intensive processes face have been falling just as rapidly. Constraints are fading away, and we want you to explore this wild new world and show us what you come up with.
Where Do You Run Your Algorithms?
To give your effort a little structure, we’ve come up with four broad categories:
- Machine Learning on the Edge
- Edge computing, where systems reach out to cloud resources but run locally, is all the rage. It allows you to leverage the power of
other people’s computers the cloud for training a model, which is then executed locally. Edge computing is a great way to keep your data local.
- Machine Learning on the Gateway
- Pi’s, old routers, what-have-yous – we’ve all got a bunch of devices laying around that bridge space between your local world and the cloud. What can you come up with that takes advantage of this unique computing environment?
- Machine Learning in the Cloud
- Forget about subtle — this category unleashes the power of the cloud for your application. Whether it’s Google, Azure, or AWS, show us what you can do with all that raw horsepower at your disposal.
- Artificial Intelligence Blinky
- Everyone’s “hardware ‘Hello, world'” is blinking an LED, and this is the machine learning version of that. We want you to use a simple microprocessor to run a machine learning algorithm. Amaze us with what you can make an Arduino do.
These Hackers Trained Their Projects, You Should Too!
We’re a little more than a month into the contest. We’ve seen some interesting entries bit of course we’re hungry for more! Here are a few that have caught our eye so far:
- Intelligent Bat Detector – [Tegwyn☠Twmffat] has bats in his… backyard, so he built this Jetson Nano-powered device to capture their calls and classify them by species. It’s a fascinating adventure at the intersection of biology and machine learning.
- Blackjack Robot – RAIN MAN 2.0 is [Evan Juras]’ cure for the casino adage of “The house always wins.” We wouldn’t try taking the Raspberry Pi card counter to Vegas, but it’s a great example of what YOLO can do.
- AI-enabled Glasses – AI meets AR in ShAIdes, [Nick Bild]’s sunglasses equipped with a camera and Nano to provide a user interface to the world. Wave your hand over a lamp and it turns off. Brilliant!
You’ve got till noon Pacific time on April 7, 2020 to get your entry in, and four winners from each of the four categories will be awarded a $100 Tindie gift card, courtesy of our sponsor Digi-Key. It’s time to ramp up your machine learning efforts and get a project entered! We’d love to see more examples of straight cloud AI applications, and the AI blinky category remains wide open at this point. Get in there and give machine learning a try!
Join us Wednesday at noon Pacific time for the AI at the Edge Hack Chat with John Welsh from NVIDIA!
Machine learning was once the business of big iron like IBM’s Watson or the nearly limitless computing power of the cloud. But the power in AI is moving away from data centers to the edge, where IoT devices are doing things once unheard of. Embedded systems capable of running modern AI workloads are now cheap enough for almost any hacker to afford, opening the door to applications and capabilities that were once only science fiction dreams.
John Welsh is a Developer Technology Engineer with NVIDIA, a leading company in the Edge computing space. He’ll be dropping by the Hack Chat to discuss NVIDIA’s Edge offerings, like the Jetson Nano we recently reviewed. Join us as we discuss NVIDIA’s complete Jetson embedded AI product line up, getting started with Edge AI, and where Edge AI is headed.
Our Hack Chats are live community events in the Hackaday.io Hack Chat group messaging. This week we’ll be sitting down on Wednesday, May 1 at noon Pacific time. If time zones have got you down, we have a handy time zone converter.
Click that speech bubble to the right, and you’ll be taken directly to the Hack Chat group on Hackaday.io. You don’t have to wait until Wednesday; join whenever you want and you can see what the community is talking about.