The device is built around Google’s AIY Voice Kit, which consists of a Raspberry Pi with some additional hardware and software to enable it to process voice queries. [Liz] combined this with a Raspberry Pi camera and the Google Cloud Vision API. This allows WhatIsThat to respond to users asking questions by taking a photo, and then identifying what it sees in the frame.
It may seem like a frivolous project to those with working vision, but there is serious potential for this technology in the accessibility space. The device can not only describe things like animals or other objects, it can also read text aloud and even identify logos. The ability of the software to go beyond is impressive – a video demonstration shows the AI correctly identifying a Boston Terrier, and attributing a quote to Albert Einstein.
Artificial intelligence has made a huge difference to the viability of voice recognition – because it’s one thing to understand the words, and another to understand what they mean when strung together. Video after the break.
A familiar spirit, or just a familiar, is a creature rumored to help people in the practice of magic. The moniker is perfect for Archimedes, the robot owl built by Alex Glow, which wields the Amazon Google AIY kit to react when it detects faces. A series of very interesting design choices a what really gives the creature life. Not all of those choices were on purpose, which is the core of her talk at the 2018 Hackaday Superconference.
You can watch the video of her talk, along with an interview with Alex after the break.
In European medieval folklore, a practitioner of magic may call for assistance from a familiar spirit who takes an animal form disguise. [Alex Glow] is our modern-day Merlin who invoked the magical incantations of 3D printing, Arduino, and Raspberry Pi to summon her familiar Archimedes: The AI Robot Owl.
The key attraction in this build is Google’s AIY Vision kit. Specifically the vision processing unit that tremendously accelerates image classification tasks running on an attached Raspberry Pi Zero W. It no longer consumes several seconds to analyze each image, classification can now run several times per second, all performed locally. No connection to Google cloud required. (See our earlier coverage for more technical details.) The default demo application of a Google AIY Vision kit is a “joy detector” that looks for faces and attempts to determine if a face is happy or sad. We’ve previously seen this functionality mounted on a robot dog.
[Alex] aimed to go beyond the default app (and default box) to create Archimedes, who was to reward happy people with a sticker. As a moving robotic owl, Archimedes had far more crowd appeal than the vision kit’s default cardboard box. All the kit components have been integrated into Archimedes’ head. One eye is the expected Pi camera, the other eye is actually the kit’s piezo buzzer. The vision kit’s LED-illuminated button now tops the dapper owl’s hat.
Archimedes was created to join in Google’s promotion efforts. Their presence at this Maker Faire consisted of two tents: one introductory “Learn to Solder” tent where people can create a blinky LED badge, and the other tent is focused on their line of AIY kits like this vision kit. Filled with demos of what the kits can do aside from really cool robot owls.
Hopefully these promotional efforts helped many AIY kits find new homes in the hands of creative makers. It’s pretty exciting that such a powerful and inexpensive neural net processor is now widely available, and we look forward to many more AI-powered hacks to come.
Humans can traverse pretty much any terrain thanks to their legs and fast-acting balancing system. So if you want a robot which should have equal flexibility, legs are a good way to go, this confirmed by all the achievements of Boston Dynamics’ robots. It was therefore natural for [Mike Rigsby] to model his robot dog after Boston Dynamics’ dog-like robot, SpotMini.
The build log on his Hackaday.io page makes for interesting reading. For example, he started out with the legs oriented like SpotMini but found that when trying to stand, the front legs worked fine but the rear ones slid or the dog shifted rearward or both happened. His solution was to take a cue from his 1990s Sony robot dog, Aibo, by reversing the orientation of the rear legs. He then upgraded his servo motors to ones with double the torque and increased the strength of the legs’ structure. In the first video below, you can see that his dog now lifts itself up to a standing position perfectly.
So far, to give it more of a dog-like personality he’s mounted Google’s AIY Vision Kit which changes a light’s color based on the degree to which a person is smiling, though we think a wagging tail would work well too. The possibilities are endless but one step at a time. See the second video below for a demonstration of the use of the Vision Kit.
Last year, Google released an artificial intelligence kit aimed at makers, with two different flavors: Vision to recognize people and objections, and Voice to create a smart speaker. Now, Google is back with a new version to make it even easier to get started.
The main difference in this year’s (v1.1) kits is that they include some basic hardware, such as a Raspberry Pi and an SD card. While this might not be very useful to most Hackaday readers, who probably have a spare Pi (or 5) lying around, this is invaluable for novice makers or the educational market. These audiences now have access to an all-in-one solution to build projects and learn more about artificial intelligence.
Google has announced their soon to be available Vision Kit, their next easy to assemble Artificial Intelligence Yourself (AIY) product. You’ll have to provide your own Raspberry Pi Zero W but that’s okay since what makes this special is Google’s VisionBonnet board that they do provide, basically a low power neural network accelerator board running TensorFlow.
The VisionBonnet is built around the Intel® Movidius™ Myriad 2 (aka MA2450) vision processing unit (VPU) chip. See the video below for an overview of this chip, but what it allows is the rapid processing of compute-intensive neural networks. We don’t think you’d use it for training the neural nets, just for doing the inference, or in human terms, for making use of the trained neural nets. It may be worth getting the kit for this board alone to use in your own hacks. An alternative is to get Modivius’s Neural Compute Stick, which has the same chip on a USB stick for around $80, not quite double the Vision Kit’s $45 price tag.
The Vision Kit isn’t out yet so we can’t be certain of the details, but based on the hardware it looks like you’ll point the camera at something, press a button and it will speak. We’ve seen this before with this talking object recognizer on a Pi 3 (full disclosure, it was made by yours truly) but without the hardware acceleration, a single object recognition took around 10 seconds. In the vision kit we expect the recognition will be in real-time. So the Vision Kit may be much more dynamic than that. And in case it wasn’t clear, a key feature is that nothing is done on the cloud here, all processing is local.
The kit comes with three different applications: an object recognition one that can recognize up to 1000 different classes of objects, another that recognizes faces and their expressions, and a third that detects people, cats, and dogs. While you can get up to a lot of mischief with just that, you can run your own neural networks too. If you need a refresher on TensorFlow then check out our introduction. And be sure to check out the Myriad 2 VPU video below the break.
A few months ago the Raspberry Pi magazine The MagPi gave away a piece of hardware, the Google AIY voice control kit. Subscribers all received one, but as always the eBay scalpers cleaned up all the in-store copies and very few lucky enthusiasts scored a kit of their own.
Among these frustrated Pi owners was [Circuitbeard], who decided instead to make his own kit. And since a cardboard case lacked style, he decided to do so in the shell of a 1980s Tomy Mr. Money toy novelty bank. Into it went a Raspberry Pi Zero W and an audio pHat, with a servo to operate the head and a microswitch connected to the toy’s arm as a trigger.
The Python code to run everything is all included in the write-up, and he’s posted a video of the device in operation which we’ve placed below the break.