A Raspberry Pi kicking around one’s workbench is a project waiting to happen — if they remain unused long enough to be considered a ‘spare.’ If you find you’ve been pining after an Alexa or your own personal J.A.R.V.I.S., [Novaspirit Tech] might be able to help you out — provided you have a USB mic and speaker handy — with an accessible tutorial for setting up Google Assistant on your Pi.
A quick run-through on enabling a fresh API client on Google’s cloud platform, [Novaspirit] jumps over to the Raspbian console to start updating Python and a few other dependencies. Note: this is being conducted in the latest version of Raspbian, so be sure to update before you get underway with all of your sudos.
Once [Novaspirit] gets that sorted, he sets up an environment to run Google Assistant on the Pi, authenticates the process, and gets it running after offering a couple troubleshooting tips. [Novaspirit] has plans to expand on this further in the near future with some home automation implementation, but this is a great jumping-off point if you’ve been looking for a way to break into some high-tech home deliciousness — or something more stripped-down — for yourself. Check out the video version of the tutorial after the break if you like watching videos of guys typing away at the command line.
Continue reading “Sudo Google Assistant”
When Amazon released the API to their voice service Alexa, they basically forced any serious players in this domain to bring their offerings out into the hacker/maker market as well. Now Google and Raspberry Pi have come together to bring us ‘Artificial Intelligence Yourself’ or AIY.
A free hardware kit made by Google was distributed with Issue 57 of the MagPi Magazine which is targeted at makers and hobbyists which you can see in the video after the break. The kit contains a Raspberry Pi Voice Hat, a microphone board, a speaker and a number of small bits to mount the kit on a Raspberry Pi 3. Putting all of it together and following the instruction on the official site gets you a Google Voice Interaction Kit with a bunch of IOs just screaming to be put to good use.
The source code for the python app can be downloaded from GitHub and consists of a loop that awaits a trigger. This trigger can be a press of a button or a clap near the microphones. When a trigger is detected, the recorder function takes over sending the stream to the Google Cloud. Speech-to-Text conversion happens there and the result is returned via a Text-To-Speech engine that helps the system talk back. The repository suggests that the official Voice Kit SD Image (893 MB download) is based on Raspbian so don’t go reflashing a memory card right away, you should be able to add this to an existing install.
Continue reading “Google AIY: Artificial Intelligence Yourself”
Advertisers are always trying to stuff more content into a 15 or 30 second TV spot. Burger King seems to have pulled it off with a series of ads that take advantage of the Google Home device sitting in many viewers living rooms. It works like this: The friendly Burger King employee ends the ad by saying “Ok Google, what is the Whopper burger?” Google home then springs into action reading the product description from Burger King’s Wikipedia page.
Trolls across the internet jumped into the fray. The Whopper’s ingredient list soon included such items as toenail clippings, rat, cyanide, and a small child. Wikipedia has since reverted the changes and locked down the page.
Google apparently wasn’t involved in this, as they quickly updated their voice recognition algorithms to specifically ignore the commercial. Burger King responded by re-dubbing the audio of the commercial with a different voice actor, which defeated Google’s block. Where this game of cat and mouse will end is anyone’s guess.
This event marks the second time in only a few months that a broadcast has caused a voice-activated device to go rogue. Back in January a disk jockey reporting a story about Amazon’s Echo managed to order doll houses for many residents of San Diego.
With devices like Alexa and Google home always ready to accept a command, stories like this are going to become the new normal. The only way to avoid it completely is to not allow it in your home. For those who do have a voice-activated device, be very careful what devices and services you connect it to. Internet of things “smart” door locks are already providing ways to unlock one’s door with a voice command. Burglarizing a home or apartment couldn’t be easier if you just have to ask Siri to unlock the door for you. And while some complained about the lack of security in the Zelda hack, we’d rate that as a thousand times more secure than a voice recognition system with no password.
Continue reading “Burger King Scores Free Advertising from Google Home with a Whopper of a Hack”
If you’ve looked at machine learning, you may have noticed that a lot of the examples are interesting but hard to follow. That’s why [Jostmey] created Naked Tensor, a bare-minimum example of using TensorFlow. The example is simple, just doing some straight line fits on some data points. One example shows how it is done in series, one in parallel, and another for an 8-million point dataset. All the code is in Python.
If you haven’t run into it yet, TensorFlow is an open source library from Google. To quote from its website:
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Continue reading “Google Machine Learning Made Simple(r)”
My son approached me the other day with his best 17-year-old sales pitch: “Dad, I need a bucket of cash!” Given that I was elbow deep in suds doing the dishes he neglected to do the night before, I mentioned that it was a singularly bad time for him to ask for anything.
Never one to be dissuaded, he plunged ahead with the reason for the funding request. He had stumbled upon a series of YouTube videos about paramotoring, and it was love at first sight for him. He waxed eloquent about how cool it would be to strap a big fan to his back and soar with the birds on a nylon parasail wing. It was actually a pretty good pitch, complete with an exposition on the father-son bonding opportunities paramotoring presented. He kind of reminded me of the twelve-year-old version of myself trying to convince my dad to spend $600 on something called a “TRS-80” that I’d surely perish if I didn’t get.
Needless to say, the $2500 he needed for the opportunity to break his neck was not forthcoming. But what happened the next day kind of blew my mind. As I was reviewing my YouTube feed, there among the [Abom79] and [AvE] videos I normally find in my “Recommended” queue was a video about – paramotoring. Now how did that get there?
Continue reading “Paramotoring for the Paranoid: Google’s AI and Relationship Mining”
If we believe science fiction — from Minority Report to Iron Man, to TekWar — the future of computer interfaces belongs to gestures. There are many ways to read gestures, although often they require some sort of glove or IR emitter, which makes them less handy (no pun intended).
Some, like the Leap Motion, have not proved popular for a variety of reasons. Soli (From Google’s Advanced Technology and Projects group) is a gesture sensor that uses millimeter-wave RADAR. The device emits a broad radio beam and then collects information including return time, energy, and frequency shift to gain an understanding about the position and movement of objects in the field. You can see a video about the device, below.
You naturally think of using optical technology to look at hand gestures (the same way humans do). However, RADAR has some advantages. It is insensitive to light and can transmit through plastic materials, for example. The Soli system operates at 60 GHz, with sensors that use Frequency Modulated Continuous Wave (FMCW) and Direct-Sequence Spread Spectrum (DSSS). The inclusion of multiple beamforming antennas means the device has no moving parts.
Clearly, this is cutting-edge gear and not readily available yet. But the good news is that Infineon is slated to bring the sensors to market sometime this year. Planned early applications include a smart watch and a speaker that both respond to gestures using the technology.
Interestingly, the Soli processing stack is supposed to be RADAR agnostic. We haven’t investigated it, but we wonder if you could use the stack to process other kinds of sensor input that might be more hacker friendly? Barring that, we’d love to see what our community could come up with for solving the same problem.
We’ve seen Raspberry Pi daughter-boards (ok, hats) that recognize gestures used to control TVs. We’ve even built some crude gesture sensing using SONAR, if that gives you any ideas. Are you planning on using Soli? Or rolling your own super gesture sensor? Let us know and document your project for everyone over on Hackaday.io.
Continue reading “Millimeter Wave RADAR Tracks Gestures”
Another week goes by and another new IoT platform surfaces. Google has announced Android Things, a build of the mobile operating system designed for smart devices rather than the latest slab of mobile eye-candy. The idea is that the same Android tools, framework and APIs that will already be familiar to app developers can be used seamlessly on IoT Things as well as in the user’s palm.
Of course, if this is sounding familiar, it’s because you may have heard something of it before. Last year they announced their Project Brillo IoT platform, and this appears to be the fruit of those efforts.
So you may well be asking: what’s in it for us? Is this just another commercial IoT platform with an eye-watering barrier to entry somewhere, or can we join the fun? It turns out the news here is good, because as the project’s web site reveals, there is support for a variety of Intel, NXP, and Raspberry Pi development boards. If you have a Raspberry Pi 3 on your bench somewhere then getting started is as simple as flashing a disk image.
The Things team have produced a set of demonstration software in a GitHub repository for developers to get their teeth into. Never one to miss an opportunity, the British Raspberry Pi hardware developer Pimoroni has released an Android Things HAT laden with sensors and displays for it to run on.
The IoT-platform market feels rather crowded at times, but it is inevitable that Android Things will gain significant traction because of its tight connections with the rest of the Android world, and its backing by Google. From this OS will no doubt come a rash of devices that will become ubiquitous, and because of its low barrier to entry there is every chance that one or two of them could come from one of you. Good luck!