If you've looked into GPU-accelerated machine learning projects, you're certainly familiar with NVIDIA's CUDA architecture. It also follows that you've checked the prices online, and know how expensive it can be to get a high-performance video card that supports this particular brand of parallel programming. But what if you could run machine learning tasks on a GPU using nothing more exotic than OpenGL? That's what [lnstadrum] has been working on for some time now, as it would allow devices as meager as the original Raspberry Pi Zero to run tasks like image classification far faster than they could using their CPU alone. The trick is to break down your computational task into something that can be performed using OpenGL shaders, which are generally meant to push video game graphics.

Google's AIY Projects (a clever play on "DIY" and "AI" that makes no sense when you actually think about it) pair a Raspberry Pi with the accessories, software, and requisite cardboard to make your own Google Assistant smart speaker or object-recognizing smart camera. They only launched last year, but Google is already back with new and improved versions of both the AIY Vision Kit and AIY Voice Kit (as spotted by 9to5 Google). The new kits now include a fresh Raspberry Pi Zero in the box and a preloaded SD card to make it easier to get started. Google is also now providing an AIY companion app for Android (and soon iOS and Chrome) to help with wireless setup and configuration of your new DIY smart speaker or camera -- though you can still use the Pi as a standard Linux computer with a monitor, keyboard, and mouse if that's more your style. The Vision Kit also includes the Pi Camera Module V2.

R2-D2 is a fictional astromech droid character from the Star Wars saga. It was a major character in the series and was mainly portrayed by radio-controlled props and CGI models. R2-D2 was built by Tony Dyson, designed by artist Ralph McQuarrie, and co-developed by John Stears. Raspberry PI Zero comes with 512 Mb of RAM, 1GHZ CPU and able to give an output of 1080 video adaptability, hence giving a rich computer experience at a very affordable cost. Building an R2-D2 robot using Raspberry Pi zero is done with the help of the cheapest board available, EXPLORER pHAT Board, an easy to use an experimental board. The tutorial for building your own has been explained as follows.

You've probably already seen one or more object recognition demos, where a system equipped with a camera detects the type of object using deep learning algorithms either locally or in the cloud. It's for example used in autonomous cars to detect pedestrian, pets, other cars and so on. Kochi Nakamura and his team have developed software based on GoogleNet deep neural network with a a 1000-class image classification model running on Raspberry Pi Zero and Raspberry Pi 3 and leveraging the VideoCore IV GPU found in Broadcom BCM283x processor in order to detect objects faster than with the CPU, more exactly about 3 times faster than using the four Cortex A53 cores in RPi 3. They just connected a battery, a display, and the official Raspberry Pi camera to the Raspberry Pi boards to be able to recognize various objects and animals. Not yet, but he is thinking about it, and when/if it is released it will probably be found on his github account, where there is already py-videocore Python library for GPGPU on Raspberry Pi, which was very likely used in the demos above.

Solutions for a relative's Alzheimer's disease, a time lapse camera and a gingerbread robot which dances when it detects a human face – these are just some of the projects you've been telling us about after we asked you to show off your inventiveness with Raspberry Pi and other electronics platforms such as Arduino. If you're a regular reader this idea may be familiar to you – we also asked you to show us the Raspberry Pi projects you'd been working on towards the end of 2015. Many of you responded to that by telling us how you'd adapted and incorporated Arduino into your hardware projects – so we widened the scope. As well as the highlights below, you can see all of the projects you've shared so far – and tell us about yours – at this GuardianWitness page, or, discuss the ideas in the comments. First up, one of many musical ideas you've been sharing.