Between Tesla Motors’ automobiles and SpaceX’s rockets, Elon Musk’s engineers just have to be getting something right. In part, SpaceX’s success in landing their first stage rockets is due to analysis of telemetry data. You can see some of the data from their launch vehicles on the live videos and there is surely a lot more not shown.
An article in MIT Technology Review provides similar insights in how Tesla came from behind in autonomous vehicle operation by analyzing telemetry from their cars. Since 2014 their Model S received an increasing number of sensors that all report their data over the vehicle’s always-on cellular channel. Sterling Anderson of Tesla reported they get a million miles of data every 10 hours.
The same approach can help us to improve our systems but many believe creating a log of key data is costly in time and resources. If your system is perfect (HA HA!) that would be a valid assessment. All too often such data becomes priceless if analysis explains why your drone or robot wanted to go left into a building instead of right into the open field.
Speech generation and recognition have come a long way. It wasn’t that long ago that we were in a breakfast place and endured 30 minutes of a teenaged girl screaming “CALL JUSTIN TAYLOR!” into her phone repeatedly, with no results. Now speech on phones is good enough you might never use the keyboard unless you want privacy. Every time we ask Google or Siri a question and get an answer it makes us feel like we are living in Star Trek.
[Smcameron] probably feels the same way. He’s been working on a Star Trek-inspired bridge simulator called “Space Nerds in Space” for some time. He decided to test out the current state of Linux speech support by adding speech commands and response to it. You can see the results in the video below.
Have you ever had to write a bit of code to interpret a non-linear analog reading as picked up by an ADC? When all you have to work with for your transfer function is a graph in a semiconductor datasheet that was probably written thirty years ago and prints out the size of a postage stamp, that’s a rather annoying task. Wouldn’t it be nice if you had access to the numbers behind the graph!
You can’t knock on the office door of the engineer who created it back in the ’80s, he’s probably in retirement and playing golf or growing prize petunias by now. But you can digitize the graph to get yourself a lot closer to the action, and to help you in your quest there’s a handy online tool.
WebPlotDigitizer is not new, it’s been around for quite a few years now. But it’s still worth talking about, because it’s one of those tools to keep in reserve. If you’ve ever needed it, you’ll know what we mean.
So how does it work? Load an image with a graph in it, select some points on the X and Y axis, roughly trace the curve with a marker tool, and set it in motion. Let’s give it a go. We’re going to try digitizing the current gain plot from the 2N3904 datasheet (PDF) that we examined a few days ago.
So, open the WebPlotDigitizer app, load the graph image captured from the sheet as a JPEG. It asks what type of graph you’ve loaded, in this case a 2D X-Y plot. It asks you to identify four known points on the axes and supply their values. You also tell it if the axes are logarithmic at this point. Select “Automatic mode” on the right hand side, then click “Pen” and mark the graph trace, then select the colour of the trace. Click the “Run” button, and your data points appear. Hit the “View data” button, and there you have it. A few rogue points to remove perhaps, but it does a pretty good job.
Wolfram Alpha has been “helping” students get through higher math and science classes for years. It can do almost everything from solving Laplace transforms to various differential equations. It’s a little lacking when it comes to solving circuits, though, which is where [Grant] steps in. He’s come up with a tool called OneSolver which can help anyone work out a number of electrical circuits (and a few common physics problems, too).
[Grant] has been slowly building an online database of circuit designs that has gotten up to around a hundred unique solvers. The interesting thing is that the site implements a unique algorithm where all input fields of a circuits design can also become output fields. This is unique to most other online calculators because it lets you do things that circuit simulators and commercial math packages can’t. The framework defines one system of equations, and will solve all possible combinations, and lets one quickly home in on a desired design solution.
If you’re a student or someone who constantly builds regulators or other tiny circuits (probably most of us) then give this tool a shot. [Grant] is still adding to it, so it will only get better over time. This may be the first time we’ve seen something like this here, too, but there have been other more specific pieces of software to help out with your circuit design.
[glitch] had a cheap EPROM eraser with very few features. Actually, that might be giving it too much credit: it’s barely more than a UV light that turns on when it’s plugged in and turns off when it’s plugged out unplugged. Of course it would be nice to implement some safety features, so he decided he’d hook it up to a software-controlled power outlet.
Of course, controlling a relay that’s wired to mains is old hat around here, and in fact, we’ve covered [glitch]’s optoisolated mains switch already. He’s gone a little beyond the normal mains relay project with this one, though. Rather than use a microcontroller to run the relay, [glitch] wrote a simple Ruby script on his computer to turn the EPROM eraser on for the precise amount of time that is required to erase the memory.The Ruby script drives the relay control directly over a USB to serial adapter’s RTS handshake pin.
[glitch]’s hack reminds us that if you just need a quick couple bits of slow output, a USB-serial converter might be just the ticket. You could imagine driving everything from standard lamps to your 3D printer’s bed heater (provided you use similar hardware), but it’s especially helpful for [glitch] who claims to forget to turn off the eraser when it’s done its job, which leaves a potentially dangerous UV source just lying about. It’s always a good idea to add safety features to a dangerous piece of equipment!
There was a discussion in the comments when the Alpha Go results were released. Some commentors were postulating that AI researchers are discounting more fluid games such as the RTS StarCraft.
The comments then devolved into a discussion of what would make the AI fair to consider against a human player. Many times, AI in RTS games win because they have direct access to the variables in the game. Rather than physically looking at the small area of the screen where a unit is located and then moving their eye to take in strategic information like exact location, health, unit level, etc, the AI just knows that it’s at 120x,2000y,76%,lvl5, etc instantly. The AI also has no click lag as it gets direct access to the game’s API, it simply changes the variables and action queue of a unit directly.
So we were interested to see [Matt]’s Star Craft AI that required the computer to actually look at the game board and click. [Matt]’s AI doesn’t see using OpenCV, which in its own way is forcing the computer to look in a way that’s unnatural to it. He instead wrote some code to intercept the behind the scenes calls to the DirectX library.
The computer is then able to make determinations about what it is looking at using the texture information and other pieces sent to the library. Unlike AI’s that get a direct look at the variables, it has to then translate this and keep its own mental picture of the map and the situation. If a building is destroyed, for example, it has to go over and look at that part of the map, test what it’s seeing against a control, and then remove the building from its list.
The AI’s one big advantage are its robot fingers. Even though this AI has to click on the interface, it doesn’t do it with a weak articulated fleshy nub like the rest of us. This allows the AI to get crazy Actions Per Minute (APM) in the range of 500 to 2000.
The AI has only been tested against StarCraft’s built in cheater bots. So far it can win most games against the hard level bots. If you want to see a video of what the AI is looking at, check after the break.
There’s some debate on which program gets the infamous title of “First Computer Virus”. There were a few for MS-DOS machines in the 80s and even one that spread through ARPANET in the 70s. Even John von Neumann theorized that programs might one day self-replicate. To compile all of these early examples of malware, and possibly settle this question once and for all, [Mikko Hypponen] has started collecting many of the early malware programs into a Museum of Malware.
While unlucky (or careless) users today are confronted with entire hard drive encryption viruses (or worse), a lot of the early viruses were relatively harmless. Examples include Brain which spread via floppy disk, the experimental ARPANET virus, or Elk Cloner which, despite many geniuses falsely claiming that Apples are immune to viruses, infected Mac computers of the 80s. [Mikko] has collected many more from this era that can be downloaded or demonstrated in a browser.
Retrocomputing is an active community, with users keeping gear of this era up and running despite it being 30+ years old. This software, while malicious at the time, is a great look into what the personal computing world was like in its infancy. And don’t forget, if you have a beige computer from a bygone era, you can always load up our Retro Page.