Why would you build a mini Mac Classic using LEGO and a Raspberry Pi? Well, why wouldn’t you?
[Jannis Hermanns] couldn’t find a reason to control this outburst of nostalgia for the good old days of small, expensive computers and long hours spent clawing through the LEGO bin to find The Perfect Piece to finish a build. It turns out that the computer part of this replica was the easy part — it’s just an e-paper display driven by a Raspberry Pi Zero. Building the case was another matter, though.
After a parti-colored prototype with whatever bricks he had on hand, a session of LEGO Digital Designer led him to just the right combination of bricks to build an accurate case, almost. It turns out that the stock selection of bricks in LDD won’t allow for the proper proportions for the case, so he ordered the all-white bricks and busted out the Dremel. LEGO purists may want to avert their eyes from the ABS gore within, but in the end the case worked out and the whole build looks great.
Fancy a full-size Mac Classic reboot? How about this iPad docking station? Or if tiny and nostalgic is really your thing, this retro-future terminal build is pretty keen too.
A few weeks ago, I was browsing Tindie on one of my daily trawls for something interesting to write about. I came across something I hadn’t seen before. The Mensch Microcomputer is a product from Western Design Center (WDC) that puts a microcontroller based on the 65xx core on a small breakout board.
I’ve played around with some of WDC’s tools and toys before, back when the sent me a few dev boards to review. They’re cool, and I have considered building a little breakout board for this weird cross between a microcontroller and a system on a chip. Life gets in the way, and that project sat on the shelf. The Mensch, however, was cheap and well into impulse purchase territory. After buying one, one of the VPs at WDC asked if I’d be interested in doing another review on their latest bit of hardware. Sure. I got this.
Continue reading “Introducing The MENSCH Microcomputer”
Modern 16:9 aspect ratio monitors may be great for watching a widescreen movie on Netflix, but for most PDFs, Word documents, and certain web pages, landscape just won’t do. But if you’re not writing the next great American novel and aren’t willing to commit to portrait mode, don’t — build an auto-rotating monitor to switch your aspect ratio on the fly.
Like many of us, [Bob] finds certain content less than suitable for the cinematic format that’s become the standard for monitors. His fix is simple in concept, but a little challenging to engineer. Using a lazy susan as a giant bearing, [Bob] built a swivel that can be powered by a NEMA 23 stepper and a 3D-printed sector of a ring gear. Due to the narrow clearance between the top and bottom of the lazy susan, [Bob] had to do considerable finagling to get through holes for the mounting hardware located, but in the end the whole thing worked great.
Our only quibble would be welding galvanized pipe for the stand, which always gives us the willies. But we will admit the tube notching turned out great with just a paper template. We doubt it would have been much better if he used an amped-up plasma-powered tubing notcher.
Continue reading “Landscape to Portrait at the Click of a Mouse”
[carykh] has a really interesting video series which can give a beginner or a pro a great insight into how neural networks operate and at the same time how evolution works. You may remember his work creating a Bach audio producing neural network, and this series again shows his talent at explaining the complex topic so anyone may understand.
He starts with 1000 “creatures”. Each has an internal clock which acts a bit like a heart beat however does not change speed throughout the creature’s life. Creatures also have nodes which cause friction with the ground but don’t collide with each other. Connecting the nodes are muscles which can stretch or contract and have different strengths.
At the beginning of the simulation the creatures are randomly generated along with their random traits. Some have longer/shorter muscles, while node and muscle positions are also randomly selected. Once this is set up they have one job: move from left to right as far as possible in 15 seconds.
Each creature has a chance to perform and 500 are then selected to evolve based on how far they managed to travel to the right of the starting position. The better the creature performs the higher the probability it will survive, although some of the high performing creatures randomly die and some lower performers randomly survive. The 500 surviving creatures reproduce asexually creating another 500 to replace the population that were killed off.
The simulation is run again and again until one or two types of species start to dominate. When this happens evolution slows down as the gene pool begins to get very similar. Occasionally a breakthrough will occur either creating a new species or improving the current best species leading to a bit of a competition for the top spot.
We think the series of four short YouTube videos (all around 5 mins each) that kick off the series demonstrate neural networks in a very visual way and make it really easy to understand. Whether you don’t know much about neural networks or you do and want to see something really cool, these are worthy of your time.
Continue reading “Learn Neural Network and Evolution Theory Fast”