If you’d have asked most people a few decades ago if they wanted a picture of every street address in the world, they would have probably looked at you like you were crazy. But turns out that Google Street View is handy for several reasons. Sure, it is easy to check out the neighborhood around that cheap hotel before you book. But it is also a great way to visit places virtually. Now one of those places is the International Space Station (ISS).
[Thomas Pesquet] in a true hack used bungee cords and existing cameras to take panoramas of all 15 ISS modules. Google did their magic, and you can enjoy the results. You can also see a video on how it was all done, below.
Continue reading “Ok Google. Navigate to the International Space Station”
Ok, so you want a radio — but not just any radio. It has to be wireless, access a variety of music services, and must have a vintage aesthetic that belies its modern innards. Oh, and a tiny screen that displays album art, because that’s always awesome. This 1938 Emerson AX212-inspired radio delivers.
Building on the backbone of a Raspberry Pi Zero W and an Adafruit MAX 98357 mono amp chip, the crux of this single-speaker radio is the program Mopidy. Mopidy is a music player that enables streaming from multiple services, with the stipulation that you have a premium Spotify account. Once signed up, [Tinkernut] helpfully outlines how to set up Mopidy to run automatically once the Pi boots up. The addition of a screen to display album art adds flair to the design, and Adafruit’s 1.8″ TFT LCD screen is small enough to fit the bill.
But wait — there’s more!
Continue reading “Retro-Styled Raspberry Pi Radio”
Google’s voice assistant has been around for a while now and when Amazon released its Alexa API and ported the PaaS Cloud code to the Raspberry Pi 2 it was just a matter of time before everyone else jumped on the fast train to maker kingdom. Google just did it in style.
Few know that the Google Assistant API for the Raspberry Pi 3 has been out there for some time now but when they decided to give away a free kit with the May 2017 issues of MagPi magazine, they made an impression on everyone. Unfortunately the world has more makers and hackers and the number of copies of the magazine are limited.
In this writeup, I layout the DIY version of the AIY kit for everyone else who wants to talk to a cardboard box. I take a closer look at the free kit, take it apart, put it together and replace it with DIY magic. To make things more convenient, I also designed an enclosure that you can 3D print to complete the kit. Lets get started.
Continue reading “How to Build Your Own Google AIY without the Kit”
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)”